U.S. patent application number 11/765443 was filed with the patent office on 2008-04-03 for system and method for optimized fuel efficiency and emission output of a diesel powered system.
Invention is credited to WOLFGANG DAUM, Eric Dillen, David Ducharme, Steven James Gray, Ed Hall, Ajith Kuttannair Kumar, Roy Primus, Glenn Robert Shaffer.
Application Number | 20080082223 11/765443 |
Document ID | / |
Family ID | 39244553 |
Filed Date | 2008-04-03 |
United States Patent
Application |
20080082223 |
Kind Code |
A1 |
DAUM; WOLFGANG ; et
al. |
April 3, 2008 |
SYSTEM AND METHOD FOR OPTIMIZED FUEL EFFICIENCY AND EMISSION OUTPUT
OF A DIESEL POWERED SYSTEM
Abstract
A method for minimizing emission output from a diesel powered
system having at least one diesel-fueled power generating unit, the
method including determining at least one power level required from
the diesel powered system in order to accomplish a specified
mission, determining an emission output based on the power level
required, and using at least one other power level that results in
a lower emission output wherein the overall resulting power is
proximate the power required.
Inventors: |
DAUM; WOLFGANG; (Erie,
PA) ; Kumar; Ajith Kuttannair; (Erie, PA) ;
Dillen; Eric; (Edinboro, PA) ; Ducharme; David;
(McKean, PA) ; Shaffer; Glenn Robert; (Erie,
PA) ; Primus; Roy; (Niskayuna, NY) ; Gray;
Steven James; (Erie, PA) ; Hall; Ed;
(Fairview, PA) |
Correspondence
Address: |
BEUSSE WOLTER SANKS MORA & MAIRE, P. A.
390 NORTH ORANGE AVENUE, SUITE 2500
ORLANDO
FL
32801
US
|
Family ID: |
39244553 |
Appl. No.: |
11/765443 |
Filed: |
June 19, 2007 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11669364 |
Jan 31, 2007 |
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11765443 |
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60849100 |
Oct 2, 2006 |
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60850885 |
Oct 10, 2006 |
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60894039 |
Mar 9, 2007 |
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60939852 |
May 24, 2007 |
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Current U.S.
Class: |
701/19 ; 701/101;
701/102; 701/21 |
Current CPC
Class: |
B61C 5/00 20130101; G05D
1/00 20130101; B61L 2205/00 20130101; B61L 2205/04 20130101; B61L
3/006 20130101; B61C 1/00 20130101 |
Class at
Publication: |
701/19 ; 701/101;
701/102; 701/21 |
International
Class: |
G06F 19/00 20060101
G06F019/00 |
Claims
1. A method for minimizing emission output from a diesel powered
system having at least one diesel-fueled power generating unit, the
method comprising: (a) determining at least one power level
required from the diesel powered system in order to accomplish a
specified mission; (b) determining an emission output based on the
power level required; and (c) using at least one other power level
that results in a lower emission output wherein the overall
resulting power is proximate the power required.
2. The method according to claim 1, wherein the diesel powered
system comprises a railway transportation system, and wherein the
diesel-fueled power generating unit comprises at least one
locomotive powered by at least one diesel internal combustion
engine.
3. The method according to claim 1, wherein the diesel powered
system comprises a marine vessel, and wherein the diesel-fueled
power generating unit comprises at least one diesel internal
combustion engine.
4. The method according to claim 1, wherein the diesel powered
system comprises an off-highway vehicle, and wherein the
diesel-fueled power generating unit comprises at least one diesel
internal combustion engine.
5. The method according to claim 1, wherein the diesel powered
system comprises a stationary power generating station, and wherein
the diesel-fueled power generating unit comprises at least one
diesel internal combustion engine.
6. The method according to claim 1, wherein the diesel powered
system comprises a network of stationary power generating stations,
and wherein the diesel-fueled power generating unit comprises at
least one diesel internal combustion engine.
7. The method according to claim 1, wherein the at least one other
power level is based on at least one of a notch level, traction
power, and engine speed level.
8. The method according to claim 1, wherein the step of using
further comprises determining a rate of using based on at least one
of emission output from operating in the at one other power level,
engine operating characteristics, and operator sensitivity.
9. The method according to claim 1, wherein the at least one other
power level is determined based on at least one of engine speed, an
engine control setting, and power setting, engine performance, and
mission operating time.
10. The method according to claim 1, wherein the step of using
further comprises determining at least one other power level based
on at least one of engine power information, power level
information, vehicle information to determine the at least one
other power level.
11. The method according to claim 1, wherein the step of using
further comprises automatically controlling operation of the diesel
powered system by automatically using the at least one other power
level based on at least one of engine power information, power
level information, and vehicle information.
12. The method according to claim 1, wherein the step of using
further comprises determining the at least one other power level
based on at least one of engine power information, power level
information, and vehicle information for manual implementing.
13. A computer software code for minimizing emission output from a
diesel powered system having a computer and at least one
diesel-fueled power generating unit, the computer software code
comprising: (a) a computer software module for determining at least
one power level required from the diesel powered system in order to
accomplish a specified mission; (b) a computer software module for
determining an emission output based on the at least one power
level required; and (c) a computer software module for using at
least one other power level that results in a lower emission output
wherein the overall resulting power is proximate the power
required.
14. The computer software code according to claim 13, wherein the
computer software module for using further comprises a computer
software module for determining a rate of using based on at least
one of emission output from when operating in the at one other
power level, engine operating characteristics, and operator
sensitivity.
15. The computer software code according to claim 13, further
comprises a computer software module for determining the at least
one other power level based on at least one of engine speed, an
engine control setting, and power setting, engine performance, and
mission operating time.
16. The computer software code according to claim 13, wherein the
computer software module for using further comprises a computer
software module for evaluating at least one of engine power
information, power level information, vehicle information to
determine the at least one other power level to determining at
least one of a using rate and the at least one other power
level.
18. A system for minimizing emission output from a diesel powered
system having at least one diesel-fueled power generating unit, the
system comprising: (a) a device configured to determine an emission
output based on a power level required; (b) a power level
controller configured to use at least one other power level so that
the resulting power level is nearly equivalent to the power level
required while emission output from the at least one other power
level is less than the emission output from the desired power
level; and (c) a processor configured to at least one of determine
the minimum power level required from the diesel powered system in
order to accomplish a specified mission and determine when to use
the at least one other power level.
18. The system according to claim 17, wherein the processor
determines a trade-off between emission output and vehicle power
settings to maximize higher operation settings where the emissions
from the exhaust after-treatment devices are optimized.
19. The system according to claim 17, wherein the diesel powered
system comprises a railway transportation system, and wherein the
diesel-fueled power generating unit comprises at least one
locomotive powered by at least one diesel internal combustion
engine.
20. The system according to claim 17, wherein the diesel powered
system comprises a marine vessel, and wherein the diesel-fueled
power generating unit comprises at least one diesel internal
combustion engine.
21. The system according to claim 17, wherein the diesel powered
system comprises an off-highway vehicle, and wherein the
diesel-powered generating unit comprises at least one diesel
internal combustion engine.
22. The system according to claim 17, wherein the diesel powered
system comprises a stationary power generating station, and wherein
the diesel-fueled power generating unit comprises at least one
diesel internal combustion engine.
23. The system according to claim 17, wherein the diesel powered
system comprises a network of stationary power generating stations,
and wherein the diesel-fueled power generating unit comprises at
least one diesel internal combustion engine.
24. The system according to claim 17, further comprises an
optimizer connected to the processor.
25. The system according to claim 24, wherein the optimizer is
configured to evaluate at least one of engine power information,
power level information, vehicle information to determine the at
least two power levels.
26. A system for minimizing emission output from a diesel powered
system having at least one diesel-fueled power generating unit, the
system comprising: (a) a processor configured to determine a power
level required from the diesel powered system in order to
accomplish a specified mission; (b) a first device configured to
determine an emission output based on the power level required; (c)
an emission comparison device configured to compare emission
outputs for other power levels with the emission output based on
the power level required; and (d) a second device configured to use
at least one other power level so that a resulting power level is
proximate the required power level so that an emission level
resulting when using the at least one other power level is less
than the power level required.
27. The system according to claim 26, wherein the processor
determines a trade-off between emission output and vehicle power
settings to maximize higher operation settings where the emissions
from the exhaust after-treatment devices are optimized.
28. The system according to claim 26, wherein the diesel powered
system comprises a railway transportation system, and wherein the
diesel-fueled power generating unit comprises at least one
locomotive powered by at least one diesel internal combustion
engine.
29. The system according to claim 26, wherein the diesel powered
system comprises a marine vessel, and wherein the diesel-fueled
power generating unit comprises at least one diesel internal
combustion engine.
30. The system according to claim 26, wherein the diesel powered
system comprises an off-highway vehicle, and wherein the
diesel-powered generating unit comprises at least one diesel
internal combustion engine.
31. The system according to claim 26, wherein the diesel powered
system comprises a stationary power generating station, and wherein
the diesel-fueled power generating unit comprises at least one
diesel internal combustion engine.
32. The system according to claim 26, wherein the diesel powered
system comprises a network of stationary power generating stations,
and wherein the diesel-fueled power generating unit comprises at
least one diesel internal combustion engine.
33. The system according to claim 26, further comprises an
optimizer connected to the processor.
34. The system according to claim 33, wherein the optimizer is
configured to evaluate at least one of engine power information,
power level information, vehicle information to determine the at
least two power levels.
35. In a fleet of diesel powered systems where each diesel powered
system of the fleet has at least one diesel-fueled power generating
unit, a method for minimizing overall emission output from at least
one of the fleet and an individual diesel powered system, the
method comprising: (a) determining overall fleet emission output
level; (b) determining a desired overall fleet emission output
level; (c) comparing the overall fleet emission output to the
desired overall fleet emission output level; (d) if the desired
overall fleet emission output level exceeds the overall fleet
emission output level, determining at least one other power level
that results in a lower emission output to use with an required
operating power level that has a higher emission output for each
respective diesel powered system within the fleet; (e) using the at
least one other power level for each respective diesel powered
system to meet the desired overall fleet emission output level
wherein the overall resulting power level for each respective
diesel powered system is proximate the power level required.
36. The method according to claim 35 wherein the step of
determining and the step of using continue until the overall
emission output is within a range of the desired overall emission
output level.
37. A method for minimizing emission output from a diesel powered
system having at least one diesel-fueled power generating unit that
may have exceeded an emission level during a first part of a
specific period, the method comprising: (a) determining overall
emission output level for the specific period; (b) determining a
desired overall emission output level for the specific period; (c)
comparing the overall emission output to the desired overall
emission output level; (d) if the overall emission output level
exceeds the desired overall emission output level, determining at
least one other power level that results in a lower emission output
to use with a required operating power level that has a higher
emission output; and (e) using the at least one other power level
to meet the desired overall emission output level wherein the
overall resulting power level is proximate the power level
required.
38. The method according to claim 37 wherein the step of
determining and the step of using continue until the overall
emission output is within the a range of the desired overall
emission output level.
39. The method according to claim 37 wherein period comprises at
least one of a time period and a specific mission.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a Continuation-In-Part of U.S.
application Ser. No. 11/669,364 filed Jan. 31, 2007, which claims
priority to U.S. Provisional Application No. 60/849,100 filed Oct.
2, 2006, and U.S. Provisional Application No. 60/850,885 filed Oct.
10, 2006. This application also claims priority to U.S. Provisional
Application No. 60/894,039 filed Mar. 9, 2007, and U.S. Provisional
Application No. 60/939,852.
FIELD OF THE INVENTION
[0002] This invention relates to a diesel powered system, such as a
train, off highway vehicle, marine and/or stationary diesel powered
system and, more particularly to a system, method, and computer
software code for optimized fuel efficiency and emission output of
the diesel powered system.
BACKGROUND OF THE INVENTION
[0003] Diesel powered systems such as, but not limited to,
off-highway vehicles, marine diesel powered propulsion plants,
stationary diesel powered system and rail vehicle systems, or
trains, usually are powered by a diesel power unit. With respect to
rail vehicle systems, the diesel power unit is part of at least one
locomotive and the train further includes a plurality of rail cars,
such as freight cars. Usually more than one locomotive is provided
wherein the locomotives are considered a locomotive consist.
Locomotives are complex systems with numerous subsystems, with each
subsystem being interdependent on other subsystems.
[0004] An operator is usually aboard a locomotive to insure the
proper operation of the locomotive, and when there is a locomotive
consist, the operator is usually aboard a lead locomotive. A
locomotive consist is a group of locomotives that operate together
in operating a train. In addition to insuring proper operations of
the locomotive, or locomotive consist, the operator also is
responsible for determining operating speeds of the train and
forces within the train that the locomotives are part of. To
perform this function, the operator generally must have extensive
experience with operating the locomotive and various trains over
the specified terrain. This knowledge is needed to comply with
prescribeable operating speeds that may vary with the train
location along the track. Moreover, the operator is also
responsible for assuring in-train forces remain within acceptable
limits.
[0005] However, even with knowledge to assure safe operation, the
operator cannot usually operate the locomotive so that the fuel
consumption and emissions is minimized for each trip. For example,
other factors that must be considered may include emission output,
operator's environmental conditions like noise/vibration, a
weighted combination of fuel consumption and emissions output, etc.
This is difficult to do since, as an example, the size and loading
of trains vary, locomotives and their fuel/emissions
characteristics are different, and weather and traffic conditions
vary.
[0006] Based on a particular train mission, when building a train,
it is common practice to provide a range of locomotives in the
train make-up to power the train, based in part on available
locomotives with varied power and run trip mission history. This
typically leads to a large variation of locomotive power available
for an individual train. Additionally, for critical trains, such as
Z-trains, backup power, typically backup locomotives, is typically
provided to cover an event of equipment failure, and to ensure the
train reaches its destination on time.
[0007] Furthermore, when building a train, locomotive emission
outputs are usually determined by establishing a weighted average
for total emission output based on the locomotives in the train
while the train is in idle. These averages are expected to be below
a certain emission output when the train is in idle. However,
typically, there is no further determination made regarding the
actual emission output while the train is in idle. Thus, though
established calculation methods may suggest that the emission
output is acceptable, in actuality the locomotive may be emitting
more emissions than calculated.
[0008] When operating a train, train operators typically call for
the same notch settings when operating the train, which in turn may
lead to a large variation in fuel consumption and/or emission
output, such as, but not limited to, No.sub.x, CO.sub.2, etc.,
depending on a number of locomotives powering the train. Thus, the
operator usually cannot operate the locomotives so that the fuel
consumption is minimized and emission output is minimized for each
trip since the size and loading of trains vary, and locomotives and
their power availability may vary by model type.
[0009] A train owner usually owns a plurality of trains wherein the
trains operate over a network of railroad tracks. Because of the
integration of multiple trains running concurrently within the
network of railroad tracks, wherein scheduling issues must also be
considered with respect to train operations, train owners would
benefit from a way to optimize fuel efficiency and emission output
so as to save on overall fuel consumption while minimizing emission
output of multiple trains while meeting mission trip time
constraints.
[0010] Likewise, owners and/or operators of off-highway vehicles,
marine diesel powered propulsion plants, and/or stationary diesel
powered systems would appreciate the financial benefits realized
when these diesel powered system produce optimize fuel efficiency
and emission output so as to save on overall fuel consumption while
minimizing emission output of while meeting operating constraints,
such as but not limited to mission time constraints.
BRIEF DESCRIPTION OF THE INVENTION
[0011] Exemplary embodiments of the invention disclose a system,
method and computer software code for minimizing emission output
from a diesel powered system having at least one diesel-fueled
power generating unit. Towards this end, a method for minimizing
emission output from a diesel powered system having at least one
diesel-fueled power generating unit is disclosed. The method has a
step for determining at least one power level required from the
diesel powered system in order to accomplish a specified mission.
Another step involves determining an emission output based on the
power level required. Yet another step provides for using at least
one other power level that results in a lower emission output
wherein the overall resulting power is proximate the power
required.
[0012] In another exemplary embodiment, a computer software code
for minimizing emission output from a diesel powered system having
a computer and at least one diesel-fueled power generating unit is
disclosed. The computer software code includes a computer software
module for determining at least one power level required from the
diesel powered system in order to accomplish a specified mission. A
computer software module for determining an emission output based
on the at least one power level required is further disclosed
Another computer software module is for using at least one other
power level that results in a lower emission output wherein the
overall resulting power is proximate the power required.
[0013] In yet another exemplary embodiment, a system for minimizing
emission output from a diesel powered system having at least one
diesel-fueled power generating unit is disclosed. The system has a
device configured to determine an emission output based on a power
level required. A power level controller configured to use at least
one other power level so that the resulting power level is nearly
equivalent to the power level required while emission output from
the at least one other power level is less than the emission output
from the desired power level is further disclosed. Also disclosed
is a processor configured to at least one of determine the minimum
power level required from the diesel powered system in order to
accomplish a specified mission and determine when to use the at
least one other power level.
[0014] A system for minimizing emission output from a diesel
powered system having at least one diesel-fueled power generating
unit is disclosed in another embodiment. The system includes a
processor configured to determine a power level required from the
diesel powered system in order to accomplish a specified mission. A
first device configured to determine an emission output based on
the power level required is provided. Another element provides for
is an emission comparison device that is configured to compare
emission outputs for other power levels with the emission output
based on the power level required. A second device is also included
that is configured to use at least one other power level so that a
resulting power level is proximate the required power level so that
an emission level resulting when using the at least one other power
level is less than the power level required.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] A more particular description of the invention briefly
described above will be rendered by reference to specific
embodiments thereof that are illustrated in the appended drawings.
Understanding that these drawings depict only typical embodiments
of the invention and are not therefore to be considered to be
limiting of its scope, exemplary embodiments of the invention will
be described and explained with additional specificity and detail
through the use of the accompanying drawings in which:
[0016] FIG. 1 depicts an exemplary illustration of a flow chart
trip optimization;
[0017] FIG. 2 depicts a simplified model of the train that may be
employed;
[0018] FIG. 3 depicts an exemplary embodiment of elements for trip
optimization;
[0019] FIG. 4 depicts an exemplary embodiment of a fuel-use/travel
time curve;
[0020] FIG. 5 depicts an exemplary embodiment of segmentation
decomposition for trip planning;
[0021] FIG. 6 depicts an exemplary embodiment of a segmentation
example;
[0022] FIG. 7 depicts another exemplary flow chart trip
optimization;
[0023] FIG. 8 depicts an exemplary illustration of a dynamic
display for use by an operator;
[0024] FIG. 9 depicts another exemplary illustration of a dynamic
display for use by the operator;
[0025] FIG. 10 depicts another exemplary illustration of a dynamic
display for use by the operator;
[0026] FIG. 11 depicts an exemplary embodiment of a network of
railway tracks with multiple trains;
[0027] FIG. 12 depicts an exemplary embodiment of a flowchart
illustrating steps for improving fuel efficiency of a train through
optimized train power makeup;
[0028] FIG. 13 depicts a block diagram of exemplary elements
included in a system for optimized train power makeup;
[0029] FIG. 14 depicts a block diagram of a transfer function for
determining a fuel efficiency and emissions for a diesel powered
system;
[0030] FIG. 15 depicts an exemplary embodiment of a flow chart
illustrating steps for determining a configuration of a diesel
powered system having at least one diesel-fueled power generating
unit;
[0031] FIG. 16 depicts an exemplary embodiment of a closed-loop
system for operating a rail vehicle;
[0032] FIG. 17 depicts the closed loop system of FIG. 16 integrated
with a master control unit;
[0033] FIG. 18 depicts an exemplary embodiment of a closed-loop
system for operating a rail vehicle integrated with another input
operational subsystem of the rail vehicle;
[0034] FIG. 19 depicts another exemplary embodiment of the
closed-loop system with a converter which may command operation of
the master controller;
[0035] FIG. 20 depicts an exemplary flowchart of steps for
operating a rail vehicle in a closed-loop process;
[0036] FIG. 21 depicts an embodiment of a speed versus time graph
comparing current operations to emissions optimized operation
[0037] FIG. 22 depicts a modulation pattern compared to a given
notch level;
[0038] FIG. 23 depicts an exemplary flowchart of steps for
determining a configuration of a diesel powered system;
[0039] FIG. 24 depicts a system for minimizing emission output;
and
[0040] FIG. 25 depicts a system for minimizing emission output from
a diesel powered system.
DETAILED DESCRIPTION OF THE INVENTION
[0041] Reference will now be made in detail to the embodiments
consistent with the invention, examples of which are illustrated in
the accompanying drawings. Wherever possible, the same reference
numerals used throughout the drawings refer to the same or like
parts.
[0042] Though exemplary embodiments of the present invention are
described with respect to rail vehicles, specifically trains and
locomotives having diesel engines, exemplary embodiments of the
invention are also applicable for other uses, such as but not
limited to off-highway vehicles, marine vessels, and stationary
units, each which may use a diesel engine. Towards this end, when
discussing a specified mission, this includes a task or requirement
to be performed by the diesel powered system. Therefore, with
respect to railway, marine or off-highway vehicle applications this
may refer to the movement of the system from a present location to
a destination. In the case of stationary applications, such as but
not limited to a stationary power generating station or network of
power generating stations, a specified mission may refer to an
amount of wattage (e.g., MW/hr) or other parameter or requirement
to be satisfied by the diesel powered system. Likewise, operating
condition of the diesel-fueled power generating unit may include
one or more of speed, load, fueling value, timing, etc.
[0043] In one exemplary example involving marine vessels, a
plurality of tugs may be operating together where all are moving
the same larger vessel, where each tug is linked in time to
accomplish the mission of moving the larger vessel. In another
exemplary example a single marine vessel may have a plurality of
engines. Off Highway Vehicle (OHV) may involve a fleet of vehicles
that have a same mission to move earth, from location A to location
B, where each OHV is linked in time to accomplish the mission. With
respect to a stationary power generating station, a plurality of
stations may be grouped together collectively generating power for
a specific location and/or purpose. In another exemplary
embodiment, a single station is provided, but with a plurality of
generators making up the single station.
[0044] Exemplary embodiments of the invention solves the problems
in the art by providing a system, method, and computer implemented
method, such as a computer software code, for improving overall
fuel efficiency and emissions through optimized power makeup. With
respect to locomotives, exemplary embodiments of the present
invention are also operable when the locomotive consist is in
distributed power operations.
[0045] Persons skilled in the art will recognize that an apparatus,
such as a data processing system, including a CPU, memory, I/O,
program storage, a connecting bus, and other appropriate
components, could be programmed or otherwise designed to facilitate
the practice of the method of the invention. Such a system would
include appropriate program means for executing the method of the
invention.
[0046] Also, an article of manufacture, such as a pre-recorded disk
or other similar computer program product, for use with a data
processing system, could include a storage medium and program means
recorded thereon for directing the data processing system to
facilitate the practice of the method of the invention. Such
apparatus and articles of manufacture also fall within the spirit
and scope of the invention.
[0047] Broadly speaking, the technical effect is an improvement of
fuel efficiency and emission output through optimized power makeup.
To facilitate an understanding of the exemplary embodiments of the
invention, it is described hereinafter with reference to specific
implementations thereof. Exemplary embodiments of the invention may
be described in the general context of computer-executable
instructions, such as program modules, being executed by a
computer. Generally, program modules include routines, programs,
objects, components, data structures, etc. that perform particular
tasks or implement particular abstract data types. For example, the
software programs that underlie exemplary embodiments of the
invention can be coded in different languages, for use with
different platforms. In the description that follows, examples of
the invention may be described in the context of a web portal that
employs a web browser. It will be appreciated, however, that the
principles that underlie exemplary embodiments of the invention can
be implemented with other types of computer software technologies
as well.
[0048] Moreover, those skilled in the art will appreciate that
exemplary embodiments of the invention may be practiced with other
computer system configurations, including hand-held devices,
multiprocessor systems, microprocessor-based or programmable
consumer electronics, minicomputers, mainframe computers, and the
like. Exemplary embodiments of the invention may also be practiced
in distributed computing environments where tasks are performed by
remote processing devices that are linked through a communications
network. In a distributed computing environment, program modules
may be located in both local and remote computer storage media
including memory storage devices. These local and remote computing
environments may be contained entirely within the locomotive, or
adjacent locomotives in consist, or off-board in wayside or central
offices where wireless communication is used.
[0049] Throughout this document the term locomotive consist is
used. As used herein, a locomotive consist may be described as
having one or more locomotives in succession, connected together so
as to provide motoring and/or braking capability. The locomotives
are connected together where no train cars are in between the
locomotives. The train can have more than one locomotive consists
in its composition. Specifically, there can be a lead consist and
more than one remote consists, such as midway in the line of cars
and another remote consist at the end of the train. Each locomotive
consist may have a first locomotive and trail locomotive(s). Though
a first locomotive is usually viewed as the lead locomotive, those
skilled in the art will readily recognize that the first locomotive
in a multi locomotive consist may be physically located in a
physically trailing position. Though a locomotive consist is
usually viewed as successive locomotives, those skilled in the art
will readily recognize that a consist group of locomotives may also
be recognized as a consist even when at least a car separates the
locomotives, such as when the locomotive consist is configured for
distributed power operation, wherein throttle and braking commands
are relayed from the lead locomotive to the remote trains by a
radio link or physical cable. Towards this end, the term locomotive
consist should be not be considered a limiting factor when
discussing multiple locomotives within the same train.
[0050] Referring now to the drawings, embodiments of the present
invention will be described. Exemplary embodiments of the invention
can be implemented in numerous ways, including as a system
(including a computer processing system), a method (including a
computerized method), an apparatus, a computer readable medium, a
computer program product, a graphical user interface, including a
web portal, or a data structure tangibly fixed in a computer
readable memory. Several embodiments of the invention are discussed
below.
[0051] FIG. 1 depicts an exemplary illustration of a flow chart of
an exemplary embodiment of the present invention. As illustrated,
instructions are input specific to planning a trip either on board
or from a remote location, such as a dispatch center 10. Such input
information includes, but is not limited to, train position,
consist description (such as locomotive models), locomotive power
description, performance of locomotive traction transmission,
consumption of engine fuel as a function of output power, cooling
characteristics, the intended trip route (effective track grade and
curvature as function of milepost or an "effective grade" component
to reflect curvature following standard railroad practices), the
train represented by car makeup and loading together with effective
drag coefficients, trip desired parameters including, but not
limited to, start time and location, end location, desired travel
time, crew (user and/or operator) identification, crew shift
expiration time, and route.
[0052] This data may be provided to the locomotive 42 in a number
of ways, such as, but not limited to, an operator manually entering
this data into the locomotive 42 via an onboard display, inserting
a memory device such as a hard card and/or USB drive containing the
data into a receptacle aboard the locomotive, and transmitting the
information via wireless communication from a central or wayside
location 41, such as a track signaling device and/or a wayside
device, to the locomotive 42. Locomotive 42 and train 31 load
characteristics (e.g., drag) may also change over the route (e.g.,
with altitude, ambient temperature and condition of the rails and
rail-cars), and the plan may be updated to reflect such changes as
needed by any of the methods discussed above and/or by real-time
autonomous collection of locomotive/train conditions. This includes
for example, changes in locomotive or train characteristics
detected by monitoring equipment on or off board the locomotive(s)
42.
[0053] The track signal system determines the allowable speed of
the train. There are many types of track signal systems and the
operating rules associated with each of the signals. For example,
some signals have a single light (on/off), some signals have a
single lens with multiple colors, and some signals have multiple
lights and colors. These signals can indicate the track is clear
and the train may proceed at max allowable speed. They can also
indicate a reduced speed or stop is required. This reduced speed
may need to be achieved immediately, or at a certain location (e.g.
prior to the next signal or crossing).
[0054] The signal status is communicated to the train and/or
operator through various means. Some systems have circuits in the
track and inductive pick-up coils on the locomotives. Other systems
have wireless communications systems. Signal systems can also
require the operator to visually inspect the signal and take the
appropriate actions.
[0055] The signaling system may interface with the on-board signal
system and adjust the locomotive speed according to the inputs and
the appropriate operating rules. For signal systems that require
the operator to visually inspect the signal status, the operator
screen will present the appropriate signal options for the operator
to enter based on the train's location. The type of signal systems
and operating rules, as a function of location, may be stored in an
onboard database 63.
[0056] Based on the specification data input into the exemplary
embodiment of the present invention, an optimal plan which
minimizes fuel use and/or emissions produced subject to speed limit
constraints along the route with desired start and end times is
computed to produce a trip profile 12. The profile contains the
optimal speed and power (notch) settings the train is to follow,
expressed as a function of distance and/or time, and such train
operating limits, including but not limited to, the maximum notch
power and brake settings, and speed limits as a function of
location, and the expected fuel used and emissions generated. In an
exemplary embodiment, the value for the notch setting is selected
to obtain throttle change decisions about once every 10 to 30
seconds. Those skilled in the art will readily recognize that the
throttle change decisions may occur at a longer or shorter
duration, if needed and/or desired to follow an optimal speed
profile. In a broader sense, it should be evident to ones skilled
in the art the profiles provide power settings for the train,
either at the train level, consist level and/or individual train
level. Power comprises braking power, motoring power, and airbrake
power. In another preferred embodiment, instead of operating at the
traditional discrete notch power settings, the exemplary embodiment
of the present invention is able to select a continuous power
setting determined as optimal for the profile selected. Thus, for
example, if an optimal profile specifies a notch setting of 6.8,
instead of operating at notch setting 7, the locomotive 42 can
operate at 6.8. Allowing such intermediate power settings may bring
additional efficiency benefits as described below.
[0057] The procedure used to compute the optimal profile can be any
number of methods for computing a power sequence that drives the
train 31 to minimize fuel and/or emissions subject to locomotive
operating and schedule constraints, as summarized below. In some
cases the required optimal profile may be close enough to one
previously determined, owing to the similarity of the train
configuration, route and environmental conditions. In these cases
it may be sufficient to look up the driving trajectory within a
database 63 and attempt to follow it. When no previously computed
plan is suitable, methods to compute a new one include, but are not
limited to, direct calculation of the optimal profile using
differential equation models which approximate the train physics of
motion. The setup involves selection of a quantitative objective
function, commonly a weighted sum (integral) of model variables
that correspond to rate of fuel consumption and emissions
generation plus a term to penalize excessive throttle
variation.
[0058] An optimal control formulation is set up to minimize the
quantitative objective function subject to constraints including
but not limited to, speed limits and minimum and maximum power
(throttle) settings and maximum cumulative and instantaneous
emissions. Depending on planning objectives at any time, the
problem may be setup flexibly to minimize fuel subject to
constraints on emissions and speed limits, or to minimize
emissions, subject to constraints on fuel use and arrival time. It
is also possible to setup, for example, a goal to minimize the
total travel time without constraints on total emissions or fuel
use where such relaxation of constraints would be permitted or
required for the mission.
[0059] Throughout the document exemplary equations and objective
functions are presented for minimizing locomotive fuel consumption.
These equations and functions are for illustration only as other
equations and objective functions can be employed to optimize fuel
consumption or to optimize other locomotive/train operating
parameters.
[0060] Mathematically, the problem to be solved may be stated more
precisely. The basic physics are expressed by:
x t = v ; x ( 0 ) = 0.0 ; x ( T f ) = D ##EQU00001## v t = T e ( u
, v ) - G a ( x ) - R ( v ) ; v ( 0 ) - 0.0 ; v ( T f ) = 0.0
##EQU00001.2##
[0061] Where x is the position of the train, v its velocity and t
is time (in miles, miles per hour and minutes or hours as
appropriate) and u is the notch (throttle) command input. Further,
D denotes the distance to be traveled, T.sub.f the desired arrival
time at distance D along the track, T.sub.e is the tractive effort
produced by the locomotive consist, G.sub.a is the gravitational
drag which depends on the train length, train makeup and terrain on
which the train is located, R is the net speed dependent drag of
the locomotive consist and train combination. The initial and final
speeds can also be specified, but without loss of generality are
taken to be zero here (train stopped at beginning and end).
Finally, the model is readily modified to include other important
dynamics such the lag between a change in throttle, u, and the
resulting tractive effort or braking. Using this model, an optimal
control formulation is set up to minimize the quantitative
objective function subject to constraints including but not limited
to, speed limits and minimum and maximum power (throttle) settings.
Depending on planning objectives at any time, the problem may be
setup flexibly to minimize fuel subject to constraints on emissions
and speed limits, or to minimize emissions, subject to constraints
on fuel use and arrival time.
[0062] It is also possible to setup, for example, a goal to
minimize the total travel time without constraints on total
emissions or fuel use where such relaxation of constraints would be
permitted or required for the mission. All these performance
measures can be expressed as a linear combination of any of the
following:
min u ( t ) .intg. 0 T f F ( u ( t ) ) t - Minimize total fuel
consumption ##EQU00002## min u ( t ) T f - Minimize Travel Time
##EQU00002.2## min u i i = 2 n d ( u i - u i - 1 ) 2 - Minimize
notch jockeying ( piecewise constant input ) ##EQU00002.3## min u (
t ) .intg. 0 T f ( u / t ) 2 t - Minimize notch jockeying (
continuous input ) ##EQU00002.4##
[0063] Replace the fuel term F in (1) with a term corresponding to
emissions production. For example for emissions
min u ( t ) .intg. 0 T f E ( u ( t ) ) t - Minimize total emissions
consumption . ##EQU00003##
In this equation E is the quantity of emissions in gm/hphr for each
of the notches (or power settings). In addition a minimization
could be done based on a weighted total of fuel and emissions.
[0064] A commonly used and representative objective function is
thus
min u ( t ) .alpha. 1 .intg. 0 T f F ( u ( t ) ) t + .alpha. 3 T f
+ .alpha. 2 .intg. 0 T f ( u / t ) 2 t ( OP ) ##EQU00004##
[0065] The coefficients of the linear combination depend on the
importance (weight) given to each of the terms. Note that in
equation (OP), u(t) is the optimizing variable that is the
continuous notch position. If discrete notch is required, e.g. for
older locomotives, the solution to equation (OP) is discretized,
which may result in lower fuel savings. Finding a minimum time
solution (.alpha..sub.1 set to zero and .alpha..sub.2 set to zero
or a relatively small value) is used to find a lower bound for the
achievable travel time (T.sub.f=T.sub.fmin). In this case, both
u(t) and T.sub.f are optimizing variables. The preferred embodiment
solves the equation (OP) for various values of T.sub.f with
T.sub.f>T.sub.fmin with .alpha..sub.3 set to zero. In this
latter case, T.sub.f is treated as a constraint.
[0066] For those familiar with solutions to such optimal problems,
it may be necessary to adjoin constraints, e.g. the speed limits
along the path:
0.ltoreq.v.ltoreq.SL(x) i.
[0067] Or when using minimum time as the objective, that an end
point constraint must hold, e.g. total fuel consumed must be less
than what is in the tank, e.g. via:
i . 0 < .intg. 0 T f F ( u ( t ) ) t .ltoreq. W F
##EQU00005##
[0068] Where W.sub.F is the fuel remaining in the tank at T.sub.f.
Those skilled in the art will readily recognize that equation (OP)
can be in other forms as well and that what is presented above is
an exemplary equation for use in the exemplary embodiment of the
present invention.
[0069] Reference to emissions in the context of the exemplary
embodiment of the present invention is actually directed towards
cumulative emissions produced in the form of oxides of nitrogen
(NOx), carbon oxides (CO.sub.x), unburned hydrocarbons (HC), and
particulate matter (PM), etc. However, other emissions may include,
but not be limited to a maximum value of electromagnetic emission,
such as a limit on radio frequency (RF) power output, measured in
watts, for respective frequencies emitted by the locomotive. Yet
another form of emission is the noise produced by the locomotive,
typically measured in decibels (dB). An emission requirement may be
variable based on a time of day, a time of year, and/or atmospheric
conditions such as weather or pollutant level in the atmosphere.
Emission regulations may vary geographically across a railroad
system. For example, an operating area such as a city or state may
have specified emission objectives, and an adjacent area may have
different emission objectives, for example a lower amount of
allowed emissions or a higher fee charged for a given level of
emissions.
[0070] Accordingly, an emission profile for a certain geographic
area may be tailored to include maximum emission values for each of
the regulated emissions including in the profile to meet a
predetermined emission objective required for that area. Typically,
for a locomotive, these emission parameters are determined by, but
not limited to, the power (Notch) setting, ambient conditions,
engine control method, etc. By design, every locomotive must be
compliant with EPA emission standards, and thus in an embodiment of
the present invention that optimizes emissions this may refer to
mission-total emissions, for which there is no current EPA
specification. Operation of the locomotive according to the
optimized trip plan is at all times compliant with EPA emission
standards. Those skilled in the art will readily recognize that
because diesel engines are used in other applications, other
regulations may also be applicable. For example, CO.sub.2 emissions
are considered in international treaties.
[0071] If a key objective during a trip mission is to reduce
emissions, the optimal control formulation, equation (OP), would be
amended to consider this trip objective. A key flexibility in the
optimization setup is that any or all of the trip objectives can
vary by geographic region or mission. For example, for a high
priority train, minimum time may be the only objective on one route
because it is high priority traffic. In another example emission
output could vary from state to state along the planned train
route.
[0072] To solve the resulting optimization problem, in an exemplary
embodiment the present invention transcribes a dynamic optimal
control problem in the time domain to an equivalent static
mathematical programming problem with N decision variables, where
the number `N` depends on the frequency at invention distributes
travel time amongst all the segments of the trip in an optimal way
so that the total trip time required is satisfied and total fuel
consumed over all the segments is as small as possible. An
exemplary 3 segment trip is disclosed in FIG. 6 and discussed
below. Those skilled in the art will recognize however, through
segments are discussed, the trip plan may comprise a single segment
representing the complete trip.
[0073] FIG. 4 depicts an exemplary embodiment of a fuel-use/travel
time curve. As mentioned previously, such a curve 50 is created
when calculating an optimal trip profile for various travel times
for each segment. That is, for a given travel time 49, fuel used 53
is the result of a detailed driving profile computed as described
above. Once travel times for each segment are allocated, a
power/speed plan is determined for each segment from the previously
computed solutions. If there are any waypoint constraints on speed
between the segments, such as, but not limited to, a change in a
speed limit, they are matched up during creation of the optimal
trip profile. If speed restrictions change in only a single
segment, the fuel use/travel-time curve 50 has to be re-computed
for only the segment changed. This reduces time for having to
re-calculate more parts, or segments, of the trip. If the
locomotive consist or train changes significantly along the route,
e.g. from loss of a locomotive or pickup or set-out of cars, then
driving profiles for all subsequent segments must be recomputed
creating new instances of the curve 50. These new curves 50 would
then be used along with new schedule objectives to plan the
remaining trip.
[0074] Once a trip plan is created as discussed above, a trajectory
of speed and power versus distance is used to reach a destination
with minimum fuel and/or emissions at the required trip time. There
are several ways in which to execute the trip plan. As provided
below in more detail, in an exemplary embodiment, when in a
coaching mode information is displayed to the operator for the
operator to follow to achieve the required power and speed
determined according to the optimal trip plan. In this mode, the
operating information is suggested operating conditions that the
operator should use. In another exemplary embodiment, acceleration
and maintaining a constant speed are which throttle and braking
adjustments are made and the duration of the trip. For typical
problems, this N can be in the thousands. For example in an
exemplary embodiment, suppose a train is traveling a 172-mile
stretch of track in the southwest United States. Utilizing the
exemplary embodiment of the present invention, an exemplary 7.6%
saving in fuel used may be realized when comparing a trip
determined and followed using the exemplary embodiment of the
present invention versus an actual driver throttle/speed history
where the trip was determined by an operator. The improved savings
is realized because the optimization realized by using the
exemplary embodiment of the present invention produces a driving
strategy with both less drag loss and little or no braking loss
compared to the trip plan of the operator.
[0075] To make the optimization described above computationally
tractable, a simplified model of the train may be employed, such as
illustrated in FIG. 2 and the equations discussed above. A key
refinement to the optimal profile is produced by driving a more
detailed model with the optimal power sequence generated, to test
if other thermal, electrical and mechanical constraints are
violated, leading to a modified profile with speed versus distance
that is closest to a run that can be achieved without harming
locomotive or train equipment, i.e. satisfying additional implied
constraints such thermal and electrical limits on the locomotive
and inter-car forces in the train.
[0076] Referring back to FIG. 1, once the trip is started 12, power
commands are generated 14 to put the plan in motion. Depending on
the operational set-up of the exemplary embodiment of the present
invention, one command is for the locomotive to follow the
optimized power command 16 so as to achieve the optimal speed. The
exemplary embodiment of the present invention obtains actual speed
and power information from the locomotive consist of the train 18.
Owing to the inevitable approximations in the models used for the
optimization, a closed-loop calculation of corrections to optimized
power is obtained to track the desired optimal speed. Such
corrections of train operating limits can be made automatically or
by the operator, who always has ultimate control of the train.
[0077] In some cases, the model used in the optimization may differ
significantly from the actual train. This can occur for many
reasons, including but not limited to, extra cargo pickups or
setouts, locomotives that fail in route, and errors in the initial
database 63 or data entry by the operator. For these reasons a
monitoring system is in place that uses real-time train data to
estimate locomotive and/or train parameters in real time 20. The
estimated parameters are then compared to the assumed parameters
used when the trip was initially created 22. Based on any
differences in the assumed and estimated values, the trip may be
re-planned 24, should large enough savings accrue from a new
plan.
[0078] Other reasons a trip may be re-planned include directives
from a remote location, such as dispatch and/or the operator
requesting a change in objectives to be consistent with more global
movement planning objectives. More global movement planning
objectives may include, but are not limited to, other train
schedules, allowing exhaust to dissipate from a tunnel, maintenance
operations, etc. Another reason may be due to an onboard failure of
a component. Strategies for re-planning may be grouped into
incremental and major adjustments depending on the severity of the
disruption, as discussed in more detail below. In general, a "new"
plan must be derived from a solution to the optimization problem
equation (OP) described above, but frequently faster approximate
solutions can be found, as described herein.
[0079] In operation, the locomotive 42 will continuously monitor
system efficiency and continuously update the trip plan based on
the actual efficiency measured, whenever such an update would
improve trip performance. Re-planning computations may be carried
out entirely within the locomotive(s) or fully or partially moved
to a remote location, such as dispatch or wayside processing
facilities where wireless technology is used to communicate the
plans to the locomotive 42. The exemplary embodiment of the present
invention may also generate efficiency trends that can be used to
develop locomotive fleet data regarding efficiency transfer
functions. The fleet-wide data may be used when determining the
initial trip plan, and may be used for network-wide optimization
tradeoff when considering locations of a plurality of trains. For
example, the travel-time fuel use tradeoff curve as illustrated in
FIG. 4 reflects a capability of a train on a particular route at a
current time, updated from ensemble averages collected for many
similar trains on the same route. Thus, a central dispatch facility
collecting curves like FIG. 4 from many locomotives could use that
information to better coordinate overall train movements to achieve
a system-wide advantage in fuel use or throughput. Those skilled in
the art will recognize that various fuel types, such as but not
limited to diesel fuel, heavy marine fuels, palm oil, bio-diesel,
etc., may be used.
[0080] Many events in daily operations can lead to a need to
generate or modify a currently executing plan, where it desired to
keep the same trip objectives, for when a train is not on schedule
for planned meet or pass with another train and it needs to make up
time. Using the actual speed, power and location of the locomotive,
a comparison is made between a planned arrival time and the
currently estimated (predicted) arrival time 25. Based on a
difference in the times, as well as the difference in parameters
(detected or changed by dispatch or the operator), the plan is
adjusted 26. This adjustment may be made automatically following a
railroad company's desire for how such departures from plan should
be handled or manually propose alternatives for the on-board
operator and dispatcher to jointly decide the best way to get back
on plan. Whenever a plan is updated but where the original
objectives, such as but not limited to arrival time remain the
same, additional changes may be factored in concurrently, e.g. new
future speed limit changes, which could affect the feasibility of
ever recovering the original plan. In such instances if the
original trip plan cannot be maintained, or in other words the
train is unable to meet the original trip plan objectives, as
discussed herein other trip plan(s) may be presented to the
operator and/or remote facility, or dispatch.
[0081] A re-plan may also be made when it is desired to change the
original objectives. Such re-planning can be done at either fixed
preplanned times, manually at the discretion of the operator or
dispatcher, or autonomously when predefined limits, such a train
operating limits, are exceeded. For example, if the current plan
execution is running late by more than a specified threshold, such
as thirty minutes, the exemplary embodiment of the present
invention can re-plan the trip to accommodate the delay at expense
of increased fuel as described above or to alert the operator and
dispatcher how much of the time can be made up at all (i.e. what
minimum time to go or the maximum fuel that can be saved within a
time constraint). Other triggers for re-plan can also be envisioned
based on fuel consumed or the health of the power consist,
including but not limited time of arrival, loss of horsepower due
to equipment failure and/or equipment temporary malfunction (such
as operating too hot or too cold), and/or detection of gross setup
errors, such in the assumed train load. That is, if the change
reflects impairment in the locomotive performance for the current
trip, these may be factored into the models and/or equations used
in the optimization.
[0082] Changes in plan objectives can also arise from a need to
coordinate events where the plan for one train compromises the
ability of another train to meet objectives and arbitration at a
different level, e.g. the dispatch office is required. For example,
the coordination of meets and passes may be further optimized
through train-to-train communications. Thus, as an example, if a
train knows that it is behind in reaching a location for a meet
and/or pass, communications from the other train can notify the
late train (and/or dispatch). The operator can then enter
information pertaining to being late into the exemplary embodiment
of the present invention wherein the exemplary embodiment will
recalculate the train's trip plan. The exemplary embodiment of the
present invention can also be used at a high level, or
network-level, to allow a dispatch to determine which train should
slow down or speed up should a scheduled meet and/or pass time
constraint may not be met. As discussed herein, this is
accomplished by trains transmitting data to the dispatch to
prioritize how each train should change its planning objective. A
choice could depend either from schedule or fuel saving benefits,
depending on the situation.
[0083] For any of the manually or automatically initiated re-plans,
exemplary embodiments of the present invention may present more
than one trip plan to the operator. In an exemplary embodiment the
present invention will present different profiles to the operator,
allowing the operator to select the arrival time and understand the
corresponding fuel and/or emission impact. Such information can
also be provided to the dispatch for similar consideration, either
as a simple list of alternatives or as a plurality of tradeoff
curves such as illustrated in FIG. 4.
[0084] The exemplary embodiment of the present invention has the
ability of learning and adapting to key changes in the train and
power consist which can be incorporated either in the current plan
and/or for future plans. For example, one of the triggers discussed
above is loss of horsepower. When building up horsepower over time,
either after a loss of horsepower or when beginning a trip,
transition logic is utilized to determine when desired horsepower
is achieved. This information can be saved in the locomotive
database 61 for use in optimizing either future trips or the
current trip should loss of horsepower occur again.
[0085] FIG. 3 depicts an exemplary embodiment of elements of that
may part of an exemplary system. A locator element 30 to determine
a location of the train 31 is provided. The locator element 30 can
be a GPS sensor, or a system of sensors, that determine a location
of the train 31. Examples of such other systems may include, but
are not limited to, wayside devices, such as radio frequency
automatic equipment identification (RF AEI) Tags, dispatch, and/or
video determination. Another system may include the tachometer(s)
aboard a locomotive and distance calculations from a reference
point. As discussed previously, a wireless communication system 47
may also be provided to allow for communications between trains
and/or with a remote location, such as dispatch. Information about
travel locations may also be transferred from other trains.
[0086] A track characterization element 33 to provide information
about a track, principally grade and elevation and curvature
information, is also provided. The track characterization element
33 may include an on-board track integrity database 36. Sensors 38
are used to measure a tractive effort 40 being hauled by the
locomotive consist 42, throttle setting of the locomotive consist
42, locomotive consist 42 configuration information, speed of the
locomotive consist 42, individual locomotive configuration,
individual locomotive capability, etc. In an exemplary embodiment
the locomotive consist 42 configuration information may be loaded
without the use of a sensor 38, but is input by other approaches as
discussed above. Furthermore, the health of the locomotives in the
consist may also be considered. For example, if one locomotive in
the consist is unable to operate above power notch level 5, this
information is used when optimizing the trip plan.
[0087] Information from the locator element may also be used to
determine an appropriate arrival time of the train 31. For example,
if there is a train 31 moving along a track 34 towards a
destination and no train is following behind it, and the train has
no fixed arrival deadline to adhere to, the locator element,
including but not limited to radio frequency automatic equipment
identification (RF AEI) Tags, dispatch, and/or video determination,
may be used to gage the exact location of the train 31.
Furthermore, inputs from these signaling systems may be used to
adjust the train speed. Using the on-board track database,
discussed below, and the locator element, such as GPS, the
exemplary embodiment of the present invention can adjust the
operator interface to reflect the signaling system state at the
given locomotive location. In a situation where signal states would
indicate restrictive speeds ahead, the planner may elect to slow
the train to conserve fuel consumption.
[0088] Information from the locator element 30 may also be used to
change planning objectives as a function of distance to
destination. For example, owing to inevitable uncertainties about
congestion along the route, "faster" time objectives on the early
part of a route may be employed as hedge against delays that
statistically occur later. If it happens on a particular trip that
delays do not occur, the objectives on a latter part of the journey
can be modified to exploit the built-in slack time that was banked
earlier, and thereby recover some fuel efficiency. A similar
strategy could be invoked with respect to emissions restrictive
objectives, e.g. approaching an urban area.
[0089] As an example of the hedging strategy, if a trip is planned
from New York to Chicago, the system may have an option to operate
the train slower at either the beginning of the trip or at the
middle of the trip or at the end of the trip. The exemplary
embodiment of the present invention would optimize the trip plan to
allow for slower operation at the end of the trip since unknown
constraints, such as but not limited to weather conditions, track
maintenance, etc., may develop and become known during the trip. As
another consideration, if traditionally congested areas are known,
the plan is developed with an option to have more flexibility
around these traditionally congested regions. Therefore, the
exemplary embodiment of the present invention may also consider
weighting/penalty as a function of time/distance into the future
and/or based on known/past experience. Those skilled in the art
will readily recognize that such planning and re-planning to take
into consideration weather conditions, track conditions, other
trains on the track, etc., may be taking into consideration at any
time during the trip wherein the trip plan is adjust
accordingly.
[0090] FIG. 3 further discloses other elements that may be part of
the exemplary embodiment of the present invention. A processor 44
is provided that is operable to receive information from the
locator element 30, track characterizing element 33, and sensors
38. An algorithm 46 operates within the processor 44. The algorithm
46 is used to compute an optimized trip plan based on parameters
involving the locomotive 42, train 31, track 34, and objectives of
the mission as described above. In an exemplary embodiment, the
trip plan is established based on models for train behavior as the
train 31 moves along the track 34 as a solution of non-linear
differential equations derived from physics with simplifying
assumptions that are provided in the algorithm. The algorithm 46
has access to the information from the locator element 30, track
characterizing element 33 and/or sensors 38 to create a trip plan
minimizing fuel consumption of a locomotive consist 42, minimizing
emissions of a locomotive consist 42, establishing a desired trip
time, and/or ensuring proper crew operating time aboard the
locomotive consist 42. In an exemplary embodiment, a driver, or
controller element, 51 is also provided. As discussed herein the
controller element 51 is used for controlling the train as it
follows the trip plan. In an exemplary embodiment discussed further
herein, the controller element 51 makes train operating decisions
autonomously. In another exemplary embodiment the operator may be
involved with directing the train to follow the trip plan.
[0091] A requirement of the exemplary embodiment of the present
invention is the ability to initially create and quickly modify on
the fly any plan that is being executed. This includes creating the
initial plan when a long distance is involved, owing to the
complexity of the plan optimization algorithm. When a total length
of a trip profile exceeds a given distance, an algorithm 46 may be
used to segment the mission wherein the mission may be divided by
waypoints. Though only a single algorithm 46 is discussed, those
skilled in the art will readily recognize that more than one
algorithm may be used where the algorithms may be connected
together. The waypoint may include natural locations where the
train 31 stops, such as, but not limited to, sidings where a meet
with opposing traffic, or pass with a train behind the current
train is scheduled to occur on single-track rail, or at yard
sidings or industry where cars are to be picked up and set out, and
locations of planned work. At such waypoints, the train 31 may be
required to be at the location at a scheduled time and be stopped
or moving with speed in a specified range. The time duration from
arrival to departure at waypoints is called dwell time.
[0092] In an exemplary embodiment, the present invention is able to
break down a longer trip into smaller segments in a special
systematic way. Each segment can be somewhat arbitrary in length,
but is typically picked at a natural location such as a stop or
significant speed restriction, or at key mileposts that define
junctions with other routes. Given a partition, or segment,
selected in this way, a driving profile is created for each segment
of track as a function of travel time taken as an independent
variable, such as shown in FIG. 4. The fuel used/travel-time
tradeoff associated with each segment can be computed prior to the
train 31 reaching that segment of track. A total trip plan can be
created from the driving profiles created for each segment. The
exemplary embodiment of the performed. However, when the train 31
must be slowed, the operator is responsible for applying a braking
system 52. In another exemplary embodiment of the present invention
commands for powering and braking are provided as required to
follow the desired speed-distance path.
[0093] Feedback control strategies are used to provide corrections
to the power control sequence in the profile to correct for such
events as, but not limited to, train load variations caused by
fluctuating head winds and/or tail winds. Another such error may be
caused by an error in train parameters, such as, but not limited
to, train mass and/or drag, when compared to assumptions in the
optimized trip plan. A third type of error may occur with
information contained in the track database 36. Another possible
error may involve un-modeled performance differences due to the
locomotive engine, traction motor thermal deration and/or other
factors. Feedback control strategies compare the actual speed as a
function of position to the speed in the desired optimal profile.
Based on this difference, a correction to the optimal power profile
is added to drive the actual velocity toward the optimal profile.
To assure stable regulation, a compensation algorithm may be
provided which filters the feedback speeds into power corrections
to assure closed-performance stability is assured. Compensation may
include standard dynamic compensation as used by those skilled in
the art of control system design to meet performance
objectives.
[0094] Exemplary embodiments of the present invention allow the
simplest and therefore fastest means to accommodate changes in trip
objectives, which is the rule, rather than the exception in
railroad operations. In an exemplary embodiment to determine the
fuel-optimal trip from point A to point B where there are stops
along the way, and for updating the trip for the remainder of the
trip once the trip has begun, a sub-optimal decomposition method is
usable for finding an optimal trip profile. Using modeling methods
the computation method can find the trip plan with specified travel
time and initial and final speeds, so as to satisfy all the speed
limits and locomotive capability constraints when there are stops.
Though the following discussion is directed towards optimizing fuel
use, it can also be applied to optimize other factors, such as, but
not limited to, emissions, schedule, crew comfort, and load impact.
The method may be used at the outset in developing a trip plan, and
more importantly to adapting to changes in objectives after
initiating a trip.
[0095] As discussed herein, exemplary embodiments of the present
invention may employ a setup as illustrated in the exemplary flow
chart depicted in FIG. 5, and as an exemplary 3 segment example
depicted in detail in FIG. 6. As illustrated, the trip may be
broken into two or more segments, T1, T2, and T3. Though as
discussed herein, it is possible to consider the trip as a single
segment. As discussed herein, the segment boundaries may not result
in equal segments. Instead the segments use natural or mission
specific boundaries. Optimal trip plans are pre-computed for each
segment. If fuel use versus trip time is the trip object to be met,
fuel versus trip time curves are built for each segment. As
discussed herein, the curves may be based on other factors, wherein
the factors are objectives to be met with a trip plan. When trip
time is the parameter being determined, trip time for each segment
is computed while satisfying the overall trip time constraints.
FIG. 6 illustrates speed limits for an exemplary 3 segment 200 mile
trip 97. Further illustrated are grade changes over the 200 mile
trip 98. A combined chart 99 illustrating curves for each segment
of the trip of fuel used over the travel time is also shown.
[0096] Using the optimal control setup described previously, the
present computation method can find the trip plan with specified
travel time and initial and final speeds, so as to satisfy all the
speed limits and locomotive capability constraints when there are
stops. Though the following detailed discussion is directed towards
optimizing fuel use, it can also be applied to optimize other
factors as discussed herein, such as, but not limited to,
emissions. A key flexibility is to accommodate desired dwell time
at stops and to consider constraints on earliest arrival and
departure at a location as may be required, for example, in
single-track operations where the time to be in or get by a siding
is critical.
[0097] Exemplary embodiments of the present invention find a
fuel-optimal trip from distance D.sub.0 to D.sub.M, traveled in
time T, with M-1 intermediate stops at D.sub.1, . . . , D.sub.M-1,
and with the arrival and departure times at these stops constrained
by
t.sub.min(i).ltoreq.t.sub.arr(D.sub.i).ltoreq.t.sub.max(i)-.DELTA.t.sub.-
i
t.sub.arr(D.sub.i)+.DELTA.t.sub.i.ltoreq.t.sub.dep(D.sub.i).ltoreq.t.sub-
.max(i) i=1, . . . , M-1
[0098] where t.sub.arr(D.sub.i), t.sub.dep(D.sub.i), and
.DELTA.t.sub.i are the arrival, departure, and minimum stop time at
the i.sup.th stop, respectively. Assuming that fuel-optimality
implies minimizing stop time, therefore
t.sub.dep(D.sub.i)=t.sub.arr(D.sub.i)+.DELTA.t.sub.i which
eliminates the second inequality above. Suppose for each i=1, . . .
, M, the fuel-optimal trip from D.sub.i-1 to D.sub.i for travel
time t, T.sub.min(i).ltoreq.t.ltoreq.T.sub.max(i), is known. Let
F.sub.i(t) be the fuel-use corresponding to this trip. If the
travel time from D.sub.j-1 to D.sub.j is denoted T.sub.j, then the
arrival time at D.sub.i is given by
i . t arr ( D i ) = j = 1 i ( T j + .DELTA. t j - 1 )
##EQU00006##
where .DELTA.t.sub.0 is defined to be zero. The fuel-optimal trip
from D.sub.0 to D.sub.M for travel time T is then obtained by
finding T.sub.i, i=1, . . . , M, which minimize
ii . i = 1 M F i ( T i ) T min ( i ) .ltoreq. T i .ltoreq. T max (
i ) ##EQU00007##
subject to
iii . t min ( i ) .ltoreq. j = 1 i ( T j + .DELTA. t j - 1 )
.ltoreq. t max ( i ) - .DELTA. t i i = 1 , , M - 1 iv . j = 1 M ( T
j + .DELTA. t j - 1 ) = T ##EQU00008##
[0099] Once a trip is underway, the issue is re-determining the
fuel-optimal solution for the remainder of a trip (originally from
D.sub.0 to D.sub.M in time T) as the trip is traveled, but where
disturbances preclude following the fuel-optimal solution. Let the
current distance and speed be x and v, respectively, where
D.sub.i-1<x.ltoreq.D.sub.i. Also, let the current time since the
beginning of the trip be t.sub.act. Then the fuel-optimal solution
for the remainder of the trip from x to D.sub.M, which retains the
original arrival time at D.sub.M, is obtained by finding {tilde
over (T)}.sub.i, T.sub.j, j=i+1, . . . M, which minimize
i . F ~ i ( T ~ i , x , v ) + j = i + 1 M F j ( T j )
##EQU00009##
subject to
ii . t min ( i ) .ltoreq. t act + T ~ i .ltoreq. t max ( i ) -
.DELTA. t i iii . t min ( k ) .ltoreq. t act + T ~ i + j = i + 1 k
( T j + .DELTA. t j - 1 ) .ltoreq. t max ( k ) - .DELTA. t k k = i
+ 1 , , M - 1 iv . t act + T ~ i + j = i + 1 M ( T j + .DELTA. t j
- 1 ) = T ##EQU00010##
[0100] Here, {tilde over (F)}.sub.i(t,x,v) is the fuel-used of the
optimal trip from x to D.sub.i, traveled in time t, with initial
speed at x of v.
[0101] As discussed above, an exemplary way to enable more
efficient re-planning is to construct the optimal solution for a
stop-to-stop trip from partitioned segments. For the trip from
D.sub.i-1 to D.sub.i, with travel time T.sub.i, choose a set of
intermediate points D.sub.ij, j=1, . . . , N.sub.i-1. Let
D.sub.i0=D.sub.i-1 and D.sub.iN.sub.i=D.sub.i. Then express the
fuel-use for the optimal trip from D.sub.i-1 to D.sub.i as
i . F i ( t ) = j = 1 N i f ij ( t ij - t i , j - 1 , v i , j - 1 ,
v ij ) ##EQU00011##
where f.sub.ij(t,v.sub.i,j-1,v.sub.ij) is the fuel-use for the
optimal trip from D.sub.i,j-1 to D.sub.ij, traveled in time t, with
initial and final speeds of v.sub.i,j-1 and v.sub.ij. Furthermore,
t.sub.ij is the time in the optimal trip corresponding to distance
D.sub.ij. By definition, t.sub.iN.sub.i-t.sub.i0=T.sub.i. Since the
train is stopped at D.sub.i0 and D.sub.iN.sub.i,
v.sub.i0=v.sub.iN.sub.i=0.
[0102] The above expression enables the function F.sub.i(t) to be
alternatively determined by first determining the functions
f.sub.ij(.cndot.), 1.ltoreq.j.ltoreq.N.sub.i, then finding
.tau..sub.ij, 1.ltoreq.j.ltoreq.N.sub.i and v.sub.ij,
1.ltoreq.j<N.sub.i, which minimize
i . F i ( t ) = j = 1 N i f ij ( .tau. ij , v i , j - 1 , v ij )
##EQU00012##
subject to
ii . j = 1 N i .tau. ij = T i iii . v min ( i , j ) .ltoreq. v ij
.ltoreq. v max ( i , j ) j = 1 , , N i - 1 iv . v i 0 = v iN i = 0
##EQU00013##
[0103] By choosing D.sub.ij (e.g., at speed restrictions or meeting
points), v.sub.max(i,j)-v.sub.min(i,j) can be minimized, thus
minimizing the domain over which f.sub.ij( ) needs to be known.
[0104] Based on the partitioning above, a simpler suboptimal
re-planning approach than that described above is to restrict
re-planning to times when the train is at distance points D.sub.ij,
1.ltoreq.i.ltoreq.M, 1.ltoreq.j.ltoreq.N.sub.i. At point D.sub.ij,
the new optimal trip from D.sub.ij to D.sub.M can be determined by
finding .tau..sub.ik, j<k.ltoreq.N.sub.i, v.sub.ik,
j<k<N.sub.i, and .tau..sub.mn, i<m.ltoreq.M,
1.ltoreq.n.ltoreq.N.sub.m, v.sub.mn, i<m.ltoreq.M,
1.ltoreq.n<N.sub.m, which minimize
i . k = j + 1 N i f ik ( .tau. ik , v i , k - 1 , v ik ) + m = i +
1 M n = 1 N m f mn ( .tau. mn , v m , n - 1 , v mn )
##EQU00014##
subject to
ii . t min ( i ) .ltoreq. t act + k = j + 1 N i .tau. ik .ltoreq. t
max ( i ) - .DELTA.t i iii . t min ( n ) .ltoreq. t act + k = j + 1
N i .tau. ik + m = i + 1 n ( T m + .DELTA. t m - 1 ) .ltoreq. t max
( n ) - .DELTA. t n n = i + 1 , , M - 1 iv . t act + k = j + 1 N i
.tau. ik + m = i + 1 M ( T m + .DELTA. t m - 1 ) = T
##EQU00015##
where
v . T m = n = 1 N m .tau. mn ##EQU00016##
[0105] A further simplification is obtained by waiting on the
re-computation of T.sub.m, i<m.ltoreq.M, until distance point
D.sub.i is reached. In this way, at points D.sub.ij between
D.sub.i-1 and D.sub.i, the minimization above needs only be
performed over .tau..sub.ik, j<k.ltoreq.N.sub.i, v.sub.ik,
j<k<N.sub.i. T.sub.i is increased as needed to accommodate
any longer actual travel time from D.sub.i-1 to D.sub.ij than
planned. This increase is later compensated, if possible, by the
re-computation of T.sub.m, i<m.ltoreq.M, at distance point
D.sub.i.
[0106] With respect to the closed-loop configuration disclosed
above, the total input energy required to move a train 31 from
point A to point B consists of the sum of four components,
specifically difference in kinetic energy between points A and B;
difference in potential energy between points A and B; energy loss
due to friction and other drag losses; and energy dissipated by the
application of brakes. Assuming the start and end speeds to be
equal (e.g., stationary), the first component is zero. Furthermore,
the second component is independent of driving strategy. Thus, it
suffices to minimize the sum of the last two components.
[0107] Following a constant speed profile minimizes drag loss.
Following a constant speed profile also minimizes total energy
input when braking is not needed to maintain constant speed.
However, if braking is required to maintain constant speed,
applying braking just to maintain constant speed will most likely
increase total required energy because of the need to replenish the
energy dissipated by the brakes. A possibility exists that some
braking may actually reduce total energy usage if the additional
brake loss is more than offset by the resultant decrease in drag
loss caused by braking, by reducing speed variation.
[0108] After completing a re-plan from the collection of events
described above, the new optimal notch/speed plan can be followed
using the closed loop control described herein. However, in some
situations there may not be enough time to carry out the segment
decomposed planning described above, and particularly when there
are critical speed restrictions that must be respected, an
alternative is needed. Exemplary embodiments of the present
invention accomplish this with an algorithm referred to as "smart
cruise control". The smart cruise control algorithm is an efficient
way to generate, on the fly, an energy-efficient (hence
fuel-efficient) sub-optimal prescription for driving the train 31
over a known terrain. This algorithm assumes knowledge of the
position of the train 31 along the track 34 at all times, as well
as knowledge of the grade and curvature of the track versus
position. The method relies on a point-mass model for the motion of
the train 31, whose parameters may be adaptively estimated from
online measurements of train motion as described earlier.
[0109] The smart cruise control algorithm has three principal
components, specifically a modified speed limit profile that serves
as an energy-efficient (and/or emissions efficient or any other
objective function) guide around speed limit reductions; an ideal
throttle or dynamic brake setting profile that attempts to balance
between minimizing speed variation and braking; and a mechanism for
combining the latter two components to produce a notch command,
employing a speed feedback loop to compensate for mismatches of
modeled parameters when compared to reality parameters. Smart
cruise control can accommodate strategies in exemplary embodiments
of the present invention that do no active braking (i.e. the driver
is signaled and assumed to provide the requisite braking) or a
variant that does active braking.
[0110] With respect to the cruise control algorithm that does not
control dynamic braking, the three exemplary components are a
modified speed limit profile that serves as an energy-efficient
guide around speed limit reductions, a notification signal directed
to notify the operator when braking should be applied, an ideal
throttle profile that attempts to balance between minimizing speed
variations and notifying the operator to apply braking, a mechanism
employing a feedback loop to compensate for mismatches of model
parameters to reality parameters.
[0111] Also included in exemplary embodiments of the present
invention is an approach to identify key parameter values of the
train 31. For example, with respect to estimating train mass, a
Kalman filter and a recursive least-squares approach may be
utilized to detect errors that may develop over time.
[0112] FIG. 7 depicts an exemplary flow chart of the present
invention. As discussed previously, a remote facility, such as a
dispatch 60 can provide information. As illustrated, such
information is provided to an executive control element 62. Also
supplied to the executive control element 62 is locomotive modeling
information database 63, information from a track database 36 such
as, but not limited to, track grade information and speed limit
information, estimated train parameters such as, but not limited
to, train weight and drag coefficients, and fuel rate tables from a
fuel rate estimator 64. The executive control element 62 supplies
information to the planner 12, which is disclosed in more detail in
FIG. 1. Once a trip plan has been calculated, the plan is supplied
to a driving advisor, driver or controller element 51. The trip
plan is also supplied to the executive control element 62 so that
it can compare the trip when other new data is provided.
[0113] As discussed above, the driving advisor 51 can automatically
set a notch power, either a pre-established notch setting or an
optimum continuous notch power. In addition to supplying a speed
command to the locomotive 31, a display 68 is provided so that the
operator can view what the planner has recommended. The operator
also has access to a control panel 69. Through the control panel 69
the operator can decide whether to apply the notch power
recommended. Towards this end, the operator may limit a targeted or
recommended power. That is, at any time the operator always has
final authority over what power setting the locomotive consist will
operate at. This includes deciding whether to apply braking if the
trip plan recommends slowing the train 31. For example, if
operating in dark territory, or where information from wayside
equipment cannot electronically transmit information to a train and
instead the operator views visual signals from the wayside
equipment, the operator inputs commands based on information
contained in track database and visual signals from the wayside
equipment. Based on how the train 31 is functioning, information
regarding fuel measurement is supplied to the fuel rate estimator
64. Since direct measurement of fuel flows is not typically
available in a locomotive consist, all information on fuel consumed
so far within a trip and projections into the future following
optimal plans is carried out using calibrated physics models such
as those used in developing the optimal plans. For example, such
predictions may include but are not limited to, the use of measured
gross horse-power and known fuel characteristics and emissions
characteristics to derive the cumulative fuel used and emissions
generated.
[0114] The train 31 also has a locator device 30 such as a GPS
sensor, as discussed above. Information is supplied to the train
parameters estimator 65. Such information may include, but is not
limited to, GPS sensor data, tractive/braking effort data, braking
status data, speed and any changes in speed data. With information
regarding grade and speed limit information, train weight and drag
coefficients information is supplied to the executive control
element 62.
[0115] Exemplary embodiments of the present invention may also
allow for the use of continuously variable power throughout the
optimization planning and closed loop control implementation. In a
conventional locomotive, power is typically quantized to eight
discrete levels. Modern locomotives can realize continuous
variation in horsepower which may be incorporated into the
previously described optimization methods. With continuous power,
the locomotive 42 can further optimize operating conditions, e.g.,
by minimizing auxiliary loads and power transmission losses, and
fine tuning engine horsepower regions of optimum efficiency, or to
points of increased emissions margins. Example include, but are not
limited to, minimizing cooling system losses, adjusting alternator
voltages, adjusting engine speeds, and reducing number of powered
axles. Further, the locomotive 42 may use the on-board track
database 36 and the forecasted performance requirements to minimize
auxiliary loads and power transmission losses to provide optimum
efficiency for the target fuel consumption/emissions. Examples
include, but are not limited to, reducing a number of powered axles
on flat terrain and pre-cooling the locomotive engine prior to
entering a tunnel.
[0116] Exemplary embodiments of the present invention may also use
the on-board track database 36 and the forecasted performance to
adjust the locomotive performance, such as to insure that the train
has sufficient speed as it approaches a hill and/or tunnel. For
example, this could be expressed as a speed constraint at a
particular location that becomes part of the optimal plan
generation created solving the equation (OP). Additionally,
exemplary embodiments of the present invention may incorporate
train-handling rules, such as, but not limited to, tractive effort
ramp rates, maximum braking effort ramp rates. These may be
incorporated directly into the formulation for optimum trip profile
or alternatively incorporated into the closed loop regulator used
to control power application to achieve the target speed.
[0117] In a preferred embodiment the present invention is only
installed on a lead locomotive of the train consist. Even though
exemplary embodiments of the present invention are not dependant on
data or interactions with other locomotives, it may be integrated
with a consist manager, as disclosed in U.S. Pat. No. 6,691,957 and
U.S. Pat. No. 7,021,588 (owned by the Assignee and both
incorporated by reference), functionality and/or a consist
optimizer functionality to improve efficiency. Interaction with
multiple trains is not precluded as illustrated by the example of
dispatch arbitrating two "independently optimized" trains described
herein.
[0118] Trains with distributed power systems can be operated in
different modes. One mode is where all locomotives in the train
operate at the same notch command. So if the lead locomotive is
commanding motoring--N8, all units in the train will be commanded
to generate motoring--N8 power. Another mode of operation is
"independent" control. In this mode, locomotives or sets of
locomotives distributed throughout the train can be operated at
different motoring or braking powers. For example, as a train
crests a mountaintop, the lead locomotives (on the down slope of
mountain) may be placed in braking, while the locomotives in the
middle or at the end of the train (on the up slope of mountain) may
be in motoring. This is done to minimize tensile forces on the
mechanical couplers that connect the railcars and locomotives.
Traditionally, operating the distributed power system in
"independent" mode required the operator to manually command each
remote locomotive or set of locomotives via a display in the lead
locomotive. Using the physics based planning model, train set-up
information, on-board track database, on-board operating rules,
location determination system, real-time closed loop power/brake
control, and sensor feedback, the system shall automatically
operate the distributed power system in "independent" mode.
[0119] When operating in distributed power, the operator in a lead
locomotive can control operating functions of remote locomotives in
the remote consists via a control system, such as a distributed
power control element. Thus when operating in distributed power,
the operator can command each locomotive consist to operate at a
different notch power level (or one consist could be in motoring
and other could be in braking) wherein each individual locomotive
in the locomotive consist operates at the same notch power. In an
exemplary embodiment, with an exemplary embodiment of the present
invention installed on the train, preferably in communication with
the distributed power control element, when a notch power level for
a remote locomotive consist is desired as recommended by the
optimized trip plan, the exemplary embodiment of the present
invention will communicate this power setting to the remote
locomotive consists for implementation. As discussed below, the
same is true regarding braking.
[0120] Exemplary embodiments of the present invention may be used
with consists in which the locomotives are not contiguous, e.g.,
with 1 or more locomotives up front, others in the middle and at
the rear for train. Such configurations are called distributed
power wherein the standard connection between the locomotives is
replaced by radio link or auxiliary cable to link the locomotives
externally. When operating in distributed power, the operator in a
lead locomotive can control operating functions of remote
locomotives in the consist via a control system, such as a
distributed power control element. In particular, when operating in
distributed power, the operator can command each locomotive consist
to operate at a different notch power level (or one consist could
be in motoring and other could be in braking) wherein each
individual in the locomotive consist operates at the same notch
power.
[0121] In an exemplary embodiment, with an exemplary embodiment of
the present invention installed on the train, preferably in
communication with the distributed power control element, when a
notch power level for a remote locomotive consist is desired as
recommended by the optimized trip plan, the exemplary embodiment of
the present invention will communicate this power setting to the
remote locomotive consists for implementation. As discussed below,
the same is true regarding braking. When operating with distributed
power, the optimization problem previously described can be
enhanced to allow additional degrees of freedom, in that each of
the remote units can be independently controlled from the lead
unit. The value of this is that additional objectives or
constraints relating to in-train forces may be incorporated into
the performance function, assuming the model to reflect the
in-train forces is also included. Thus exemplary embodiments of the
present invention may include the use of multiple throttle controls
to better manage in-train forces as well as fuel consumption and
emissions.
[0122] In a train utilizing a consist manager, the lead locomotive
in a locomotive consist may operate at a different notch power
setting than other locomotives in that consist. The other
locomotives in the consist operate at the same notch power setting.
Exemplary embodiments of the present invention may be utilized in
conjunction with the consist manager to command notch power
settings for the locomotives in the consist. Thus based on
exemplary embodiments of the present invention, since the consist
manager divides a locomotive consist into two groups, lead
locomotive and trail units, the lead locomotive will be commanded
to operate at a certain notch power and the trail locomotives are
commanded to operate at another certain notch power. In an
exemplary embodiment the distributed power control element may be
the system and/or apparatus where this operation is housed.
[0123] Likewise, when a consist optimizer is used with a locomotive
consist, exemplary embodiments of the present invention can be used
in conjunction with the consist optimizer to determine notch power
for each locomotive in the locomotive consist. For example, suppose
that a trip plan recommends a notch power setting of 4 for the
locomotive consist. Based on the location of the train, the consist
optimizer will take this information and then determine the notch
power setting for each locomotive in the consist. In this
implementation, the efficiency of setting notch power settings over
intra-train communication channels is improved. Furthermore, as
discussed above, implementation of this configuration may be
performed utilizing the distributed control system.
[0124] Furthermore, as discussed previously, exemplary embodiment
of the present invention may be used for continuous corrections and
re-planning with respect to when the train consist uses braking
based on upcoming items of interest, such as but not limited to
railroad crossings, grade changes, approaching sidings, approaching
depot yards, and approaching fuel stations where each locomotive in
the consist may require a different braking option. For example, if
the train is coming over a hill, the lead locomotive may have to
enter a braking condition whereas the remote locomotives, having
not reached the peak of the hill may have to remain in a motoring
state.
[0125] FIGS. 8, 9 and 10 depict exemplary illustrations of dynamic
displays for use by the operator. As provided, FIG. 8, a trip
profile is provided 72. Within the profile a location 73 of the
locomotive is provided. Such information as train length 105 and
the number of cars 106 in the train is provided. Elements are also
provided regarding track grade 107, curve and wayside elements 108,
including bridge location 109, and train speed 110. The display 68
allows the operator to view such information and also see where the
train is along the route. Information pertaining to distance and/or
estimate time of arrival to such locations as crossings 112,
signals 114, speed changes 116, landmarks 118, and destinations 120
is provided. An arrival time management tool 125 is also provided
to allow the user to determine the fuel savings that is being
realized during the trip. The operator has the ability to vary
arrival times 127 and witness how this affects the fuel savings. As
discussed herein, those skilled in the art will recognize that fuel
saving is an exemplary example of only one objective that can be
reviewed with a management tool. Towards this end, depending on the
parameter being viewed, other parameters, discussed herein can be
viewed and evaluated with a management tool that is visible to the
operator. The operator is also provided information about how long
the crew has been operating the train. In exemplary embodiments
time and distance information may either be illustrated as the time
and/or distance until a particular event and/or location or it may
provide a total elapsed time.
[0126] As illustrated in FIG. 9 an exemplary display provides
information about consist data 130, an events and situation graphic
132, an arrival time management tool 134, and action keys 136.
Similar information as discussed above is provided in this display
as well. This display 68 also provides action keys 138 to allow the
operator to re-plan as well as to disengage 140 exemplary
embodiments of the present invention.
[0127] FIG. 10 depicts another exemplary embodiment of the display.
Data typical of a modern locomotive including air-brake status 72,
analog speedometer with digital inset 74, and information about
tractive effort in pounds force (or traction amps for DC
locomotives) is visible. An indicator 74 is provided to show the
current optimal speed in the plan being executed as well as an
accelerometer graphic to supplement the readout in mph/minute.
Important new data for optimal plan execution is in the center of
the screen, including a rolling strip graphic 76 with optimal speed
and notch setting versus distance compared to the current history
of these variables. In this exemplary embodiment, location of the
train is derived using the locator element. As illustrated, the
location is provided by identifying how far the train is away from
its final destination, an absolute position, an initial
destination, an intermediate point, and/or an operator input.
[0128] The strip chart provides a look-ahead to changes in speed
required to follow the optimal plan, which is useful in manual
control, and monitors plan versus actual during automatic control.
As discussed herein, such as when in the coaching mode, the
operator can either follow the notch or speed suggested by
exemplary embodiments of the present invention. The vertical bar
gives a graphic of desired and actual notch, which are also
displayed digitally below the strip chart. When continuous notch
power is utilized, as discussed above, the display will simply
round to closest discrete equivalent, the display may be an analog
display so that an analog equivalent or a percentage or actual
horse power/tractive effort is displayed.
[0129] Critical information on trip status is displayed on the
screen, and shows the current grade the train is encountering 88,
either by the lead locomotive, a location elsewhere along the train
or an average over the train length. A distance traveled so far in
the plan 90, cumulative fuel used 92, where or the distance away
the next stop is planned 94, current and projected arrival time 96
expected time to be at next stop are also disclosed. The display 68
also shows the maximum possible time to destination possible with
the computed plans available. If a later arrival was required, a
re-plan would be carried out. Delta plan data shows status for fuel
and schedule ahead or behind the current optimal plan. Negative
numbers mean less fuel or early compared to plan, positive numbers
mean more fuel or late compared to plan, and typically trade-off in
opposite directions (slowing down to save fuel makes the train late
and conversely).
[0130] At all times these displays 68 gives the operator a snapshot
of where he stands with respect to the currently instituted driving
plan. This display is for illustrative purpose only as there are
many other ways of displaying/conveying this information to the
operator and/or dispatch. Towards this end, the information
disclosed above could be intermixed to provide a display different
than the ones disclosed.
[0131] Other features that may be included in exemplary embodiments
of the present invention include, but are not limited to, allowing
for the generating of data logs and reports. This information may
be stored on the train and downloaded to an off-board system at
some point in time. The downloads may occur via manual and/or
wireless transmission. This information may also be viewable by the
operator via the locomotive display. The data may include such
information as, but not limited to, operator inputs, time system is
operational, fuel saved, fuel imbalance across locomotives in the
train, train journey off course, system diagnostic issues such as
if GPS sensor is malfunctioning.
[0132] Since trip plans must also take into consideration allowable
crew operation time, exemplary embodiments of the present invention
may take such information into consideration as a trip is planned.
For example, if the maximum time a crew may operate is eight hours,
then the trip shall be fashioned to include stopping location for a
new crew to take the place of the present crew. Such specified
stopping locations may include, but are not limited to rail yards,
meet/pass locations, etc. If, as the trip progresses, the trip time
may be exceeded, exemplary embodiments of the present invention may
be overridden by the operator to meet criteria as determined by the
operator. Ultimately, regardless of the operating conditions of the
train, such as but not limited to high load, low speed, train
stretch conditions, etc., the operator remains in control to
command a speed and/or operating condition of the train.
[0133] Using exemplary embodiments of the present invention, the
train may operate in a plurality of operations. In one operational
concept, an exemplary embodiment of the present invention may
provide commands for commanding propulsion, dynamic braking. The
operator then handles all other train functions. In another
operational concept, an exemplary embodiment of the present
invention may provide commands for commanding propulsion only. The
operator then handles dynamic braking and all other train
functions. In yet another operational concept, an exemplary
embodiment of the present invention may provide commands for
commanding propulsion, dynamic braking and application of the
airbrake. The operator then handles all other train functions.
[0134] Exemplary embodiments of the present invention may also be
used by notify the operator of upcoming items of interest of
actions to be taken. Specifically, the forecasting logic of
exemplary embodiments of the present invention, the continuous
corrections and re-planning to the optimized trip plan, the track
database, the operator can be notified of upcoming crossings,
signals, grade changes, brake actions, sidings, rail yards, fuel
stations, etc. This notification may occur audibly and/or through
the operator interface.
[0135] Specifically using the physics based planning model, train
set-up information, on-board track database, on-board operating
rules, location determination system, real-time closed loop
power/brake control, and sensor feedback, the system shall present
and/or notify the operator of required actions. The notification
can be visual and/or audible. Examples include notifying of
crossings that require the operator activate the locomotive horn
and/or bell, notifying of "silent" crossings that do not require
the operator activate the locomotive horn or bell.
[0136] In another exemplary embodiment, using the physics based
planning model discussed above, train set-up information, on-board
track database, on-board operating rules, location determination
system, real-time closed power/brake control, and sensor feedback,
exemplary embodiments of the present invention may present the
operator information (e.g. a gauge on display) that allows the
operator to see when the train will arrive at various locations as
illustrated in FIG. 9. The system shall allow the operator to
adjust the trip plan (target arrival time). This information
(actual estimated arrival time or information needed to derive
off-board) can also be communicated to the dispatch center to allow
the dispatcher or dispatch system to adjust the target arrival
times. This allows the system to quickly adjust and optimize for
the appropriate target function (for example trading off speed and
fuel usage).
[0137] FIG. 11 depicts an exemplary embodiment of a network of
railway tracks with multiple trains. In the railroad network 200,
it is desirable to obtain an optimized fuel efficiency and time of
arrival for the overall network of multiple interacting tracks 210,
220, 230, and trains 235, 236, 237. As illustrated multiple tracks
210, 220, 230 are shown with a train 235, 236, 237 on each
respective track. Though locomotive consists 42 are illustrated as
part of the trains 235, 236, 237, those skilled in the art will
readily recognize that any train may only have a single locomotive
consist having a single locomotive. As disclosed herein, a remote
facility 240 may also be involved with improving fuel efficiency
and reducing emissions of a train through optimized train power
makeup. This may be accomplished with a processor 245, such as a
computer, located at the remote facility 240. In another exemplary
embodiment a hand-held device 250 may be used to facilitate
improving fuel efficiency of the train 235, 236, 237 through
optimized train power makeup. Typically in either of these
approaches, configuring the train 235, 236, 237 usually occurs at a
hump, or rail, yard, more specifically when the train is being
compiled.
[0138] However as discussed below, the processor 245 may be located
on the train 235, 236, 237 or aboard another train wherein train
setup may be accomplished using inputs from the other train. For
example, if a train has recently completed a mission over the same
tracks, input from that train's mission may be supplied to the
current train as it either is performing and/or is about to begin
its mission. Thus configuring the train may occur at train run
time, and even during the run time. For example, real time
configuration data may be utilized to configure the train
locomotives. One such example is provided above with respect to
using data from another train. Another exemplary example entails
using other data associated with trip optimization of the train as
discussed above. Additionally the train setup may be performed
using input from a plurality of sources, such as, but not limited
to, a dispatch system, a wayside system 270, an operator, an
off-line real time system, an external setup, a distributed
network, a local network, and/or a centralized network.
[0139] FIG. 12 depicts an exemplary embodiment of a flowchart
illustrating steps for improving fuel efficiency and reducing
emission output through optimized train power makeup. As disclosed
above to minimize fuel use and emissions while preserving time
arrival, in an exemplary embodiment acceleration and matched
breaking needs to be minimized. Undesired emissions may also be
minimized by powering a minimal set of locomotives. For example, in
a train with several locomotives or locomotive consists, powering a
minimal set of locomotives at a higher power setting while putting
the remaining locomotives into idle, unpowered standby, or an
automatic engine start-stop ("AESS) mode as discussed below, will
reduce emissions. This is due, in part, because at lower power
setting such as notch 1-3, exhaust emissions after-treatment
devices, such as but not limited to catalytic converters, located
on the locomotives are at a temperature below which these systems'
operations are optimal. Therefore, using the minimum number of
locomotives or locomotive consists to make the mission on time,
operating at high power settings will allow for the exhaust
emission treatment devices, such as but not limited to catalytic
converters, to operate at optimal temperatures thus further
reducing emissions.
[0140] As illustrated one step in the flow chart 500 provides for
determining a train load, step 510. When the engine is used in
other applications, the load is determined based on the engine
configuration. The train load may be determined with a load, or
train load, estimator 560, as illustrated in FIG. 13. In an
exemplary embodiment the train load is estimated based on
information obtained as disclosed in a train makeup docket 480, as
illustrated in FIG. 11. For example, the train makeup docket 480
may be contained in the computer 245 (illustrated in FIGS. 11 &
13) wherein the processor 245 makes the estimation, or may be on
paper wherein an operator makes the estimation. The train makeup
docket 480 may include such information as, but not limited to,
number of cars, weight of the cars, content of the cars, age of
cars, etc. In another exemplary embodiment the train load is
estimated using historical data, such as but not limited to prior
train missions making the same trip, similar train car
configurations, etc. As discussed above, using historical data may
be accomplished with a processor or manually. In yet another
exemplary embodiment, the train load is estimated using a rule of
thumb or table data. For example, the operator configuring the
train 235, 236, 237 may determine the train load required based on
established guideline such as, but not limited to, a number of cars
in the train, types of cars in the train, weight of the cars in the
train, an amount of products being transported by the train, etc.
This same rule of thumb determination may also be accomplished
using the processor 245.
[0141] Another step includes identifying a mission time and/or
duration for the diesel power system, step 520. With respect to
engines used in other applications, this step equates to defining
the mission time which the engine configuration is expected to
accomplish the mission. A determination is made about a minimum
total amount of power required based on the train load, step 530.
The locomotive is selected to satisfy the minimum required power
while yielding improved fuel efficiency and/or minimized emission
output, step 540. The locomotive may be selected based on a type of
locomotive (based on its engine) needed and/or a number of
locomotives (based on a number of engines) needed. Similarly, with
respect to diesel engines used in other power applications, such as
but not limited to marine, OHV, and stationary power stations,
where multiple units of each are used to accomplish an intended
mission unique for the specific application.
[0142] Towards this end, a trip mission time determinator 570, as
illustrated in FIG. 13, may be used to determine the mission time.
Such information that may be used includes, but not limited to,
weather conditions, track conditions, etc. The locomotive makeup
may be based on types of locomotives needed, such as based on power
output, and/or a minimum number of locomotives needed. For example,
based on the available locomotives, a selection is made of those
locomotives that just meet the total power required. Towards this
end, as an example, if ten locomotives are available, a
determination of the power output from each locomotive is made.
Based on this information, the fewest number and type of
locomotives needed to meet the total power requirements are
selected. For example the locomotives may have different horse
power (HP) ratings or starting Tractive Effort (TE) ratings. In
addition to the total power required, the distribution of power and
type of power in the train can be determined. For example on heavy
trains to limit the maximum coupler forces, the locomotives may be
distributed within the train. Another consideration is the
capability of the locomotive. It may be possible to put 4 DC
locomotives on the head end of a train, however 4 AC units with the
same HP may not be used at the headend since the total drawbar
forces may exceed the limits.
[0143] In another exemplary embodiment, the selection of
locomotives may not be based solely on reducing a number of
locomotives used in a train. For example, if the total power
requirement is minimally met by five of the available locomotives
when compared to also meeting the power requirement by the use of
three of the available locomotives, the five locomotives are used
instead of the three. In view of these options, those skilled in
the art will readily recognize that minimum number of locomotives
may be selected from a sequential (and random) set of available
locomotives. Such an approach may be used when the train 235, 236,
237 is already compiled and a decision is being made at run time
and/or during a mission wherein the remaining locomotives are not
used to power the train 235, 236, 237, as discussed in further
detail below.
[0144] While compiling the train 235, 236, 237, if the train 235,
236, 237 requires backup power, incremental locomotive 255, or
locomotives, may be added. However this additional locomotive 255
is isolated to minimize fuel use, emission output, and power
variation, but may be used to provide backup power in case an
operating locomotive fails, and/or to provide additional power to
accomplish the trip within an established mission time. The
isolated locomotive 255 may be put into an AESS mode to minimize
fuel use and having the locomotive available when needed. In an
exemplary embodiment, if a backup, or isolated, locomotive 255 is
provided, its dimensions, such as weight, may be taken into
consideration when determining the train load.
[0145] Thus, as discussed above in more detail, determining minimum
power needed to power the train 235, 236, 237 may occur at train
run time and/or during a run (or mission). In this instance once a
determination is made as to optimized train power and the
locomotives or locomotive consists 42 in the train 235, 236, 237
are identified to provide the requisite power needed, the
additional locomotive(s) 255 not identified for use are put in the
idle, or AESS, mode.
[0146] In an exemplary embodiment, the total mission run may be
broken into a plurality of sections, or segments, such as but not
limited to at least 2 segments, such as segment A and segment B as
illustrated in FIG. 11. Based on the amount of time taken to
complete any segment the backup power, provided by the isolated
locomotive 255, is provided in case incremental power is needed to
meet the trip mission objective. Towards this end, the isolated
locomotive 255 may be utilized for a specific trip segment to get
the train 235, 236, 237 back on schedule and then switched off for
the following segments, if the train 235, 236, 237 remains on
schedule.
[0147] Thus in operation, the lead locomotive may put the
locomotive 255 provided for incremental power into an isolate mode
until the power is needed. This may be accomplished by use of wired
or wireless modems or communications from the operator, usually on
the lead locomotive, to the isolated locomotive 255. In another
exemplary embodiment the locomotives operate in a distributed power
configuration and the isolated locomotive 255 is already integrated
in the distributed power configuration, but is idle, and is
switched on when the additional power is required. In yet another
embodiment the operator puts the isolated locomotive 255 into the
appropriate mode.
[0148] In an exemplary embodiment the initial setup of the
locomotives, based on train load and mission time, is updated by
the trip optimizer, as disclosed in above, and adjustments to the
number and type of powered locomotives are made. As an exemplary
illustration, consider a locomotive consist 42 of 3 locomotives
having relative available maximum power of 1, 1.5 and 0.75,
respectively. Relative available power is relative to a reference
locomotive; railroads use `reference` locomotives to determine the
total consist power; this could be a `3000 HP` reference
locomotive; hence, in this example the first locomotive has 3000
HP, the second 4500 HP and the third 2250 HP). Suppose that the
mission is broken into seven segments. Given the above scenario the
following combinations are available and can be matched to the
track section load, 0.75, 1, 1.5, 1.75, 2.25, 2.5, 3.25, which is
the combination of maximum relative HP settings for the consist.
Thus for each respective relative HP setting mentioned above, for
0.75 the third locomotive is on and the first and second are off,
for 1 the first locomotive is on and the second and third are off,
etc. In a preferred embodiment the trip optimizer selects the
maximum required load and adjusts via notch calls while minimizing
an overlap of power settings. Hence, if a segment calls for between
2 and 2.5 (times 3000 HP) then locomotive 1 and locomotive 2 are
used while locomotive 3 is in either idle or in standby mode,
depending on the time it is in this segment and the restart time of
the locomotive.
[0149] In another exemplary embodiment, an analysis may be
performed to determine a trade off between emission output and
locomotive power settings to maximize higher notch operation where
the emissions from the exhaust after treatment devices are more
optimal. This analysis may also take into consideration one of the
other parameters discussed above regarding train operation
optimization. This analysis may be performed for an entire mission
run, segments of a mission run, and/or combinations of both.
[0150] FIG. 13 depicts a block diagram of exemplary elements
included in a system for optimized train power makeup. As
illustrated and discussed above, a train load estimator 560 is
provided. A trip mission time determinator 570 is also provided. A
processor 240 is also provided. As disclosed above, though directed
at a train, similar elements may be used for other engines not
being used within a rail vehicle, such as but not limited to
off-highway vehicles, marine vessels, and stationary units. The
processor 240 calculates a total amount of power required to power
the train 235, 236, 237 based on the train load determined by the
train load estimator 560 and a trip mission time determined by the
trip mission time determinator 570. A determination is further made
of a type of locomotive needed and/or a number of locomotives
needed, based on each locomotive power output, to minimally achieve
the minimum total amount of power required based on the train load
and trip mission time.
[0151] The trip mission time determinator 570 may segment the
mission into a plurality of mission segments, such as but not
limited to segment A and segment B, as discussed above. The total
amount of power may then be individually determined for each
segment of the mission. As further discussed above, an additional
locomotive 255 is part of the train 235, 236, 237 and is provided
for back up power. The power from the back-up locomotive 255 may be
used incrementally as a required is identified, such as but not
limited to providing power to get the train 235, 236, 237 back on
schedule for a particular trip segment. In this situation, the
train 235, 236, 237 is operated to achieve and/or meet the trip
mission time.
[0152] The train load estimator 560 may estimate the train load
based on information contained in the train makeup docket 480,
historical data, a rule of thumb estimation, and/or table data.
Furthermore, the processor 245 may determine a trade off between
emission output and locomotive power settings to maximize higher
notch operation where the emissions from the exhaust
after-treatment devices are optimized.
[0153] FIG. 14 depicts a block diagram of a transfer function for
determining a fuel efficiency and emissions for a diesel powered
system. Such diesel powered systems include, but are not limited to
locomotives, marine vessels, OHV, and/or stationary generating
stations. As illustrated, information pertaining to input energy
580 (such as but not limited to power, waste heat, etc.) and
information about an after treatment process 583 are provided to a
transfer function 585. The transfer function 585 utilizes this
information to determine an optimum fuel efficiency 587 and
emission output 590.
[0154] FIG. 15 depicts a an exemplary embodiment of a flow chart
illustrating steps for determining a configuration of a diesel
powered system having at least one diesel-fueled power generating
unit. The flow chart 600 includes a step for determining a minimum
power required from the diesel powered system in order to
accomplish a specified mission, step 605. A step for determining an
operating condition of the diesel-fueled power generating unit such
that the minimum power requirement is satisfied while yielding at
least one of lower fuel consumption and lower emissions for the
diesel powered system, step 610 is also disclosed. As disclosed
above, this flow chart 600 is applicable for a plurality of
diesel-fueled power generating units, such as but not limited to a
locomotive, marine vessel, OHV, and/or stationary generating
stations. Additionally, this flowchart 600 may be implemented using
a computer software program.
[0155] FIG. 16 depicts an exemplary embodiment of a closed-loop
system for operating a rail vehicle. As illustrated, an optimizer
650, converter 652, rail vehicle 653, and at least one output 654,
such as but not limited to speed, emissions, tractive effort, horse
power, sand, etc., are part of the closed-loop control
communication system 657. The output 654 may be determined by a
sensor 656 which is part of the rail vehicle 653, or in another
exemplary embodiment independent of the rail vehicle 653.
Information initially derived from information generated from the
trip optimizer 650 and/or a regulator is provided to the rail
vehicle 653 through the converter 652. Locomotive data gathered by
the sensor 654 from the rail vehicle is then communicated 657 back
to the optimizer 650.
[0156] The optimizer 650 determines operating characteristics for
at least one factor that is to be regulated, such as but not
limited to speed, fuel, emissions, etc. The optimizer 650
determines at least one of a power and/or torque setting based on a
determined optimized value. The converter 652 is provided to
convert the power, torque, speed, emissions, sanding, setup,
configurations etc., control inputs for the rail vehicle 653,
usually a locomotive. Specifically, this information or data about
power, torque, speed, emissions, sanding, setup, configurations
etc., and/or control inputs is converted to an electrical
signal.
[0157] FIG. 17 depicts the closed loop system integrated with a
master control unit. As illustrated in further detail below, the
converter 652 may interface with any one of a plurality of devices,
such as but not limited to a master controller, remote control
locomotive controller, a distributed power drive controller, a
train line modem, analog input, etc. The converter, for example,
may disconnect the output of the master controller 651. The master
controller 651 is normally used by the operator to command the
locomotive, such as but not limited to power, horsepower, tractive
effort, sanding, braking (including at least one of dynamic
braking, air brakes, hand brakes, etc.), propulsion, etc. levels to
the locomotive. Those skilled in the art will readily recognize
that the master controller may be used to control both hard
switches and software based switches used in controlling the
locomotive. The converter 652 then injects signals into the master
controller 651. The disconnection of the master controller 651 may
be electrical wires or software switches or configurable input
selection process etc. A switching device 655 is illustrated to
perform this function.
[0158] As discussed above, the same technique may be used for other
devices, such as but not limited to a control locomotive
controller, a distributed power drive controller, a train line
modem, analog input, etc. Though not illustrated, those skilled in
the art readily recognize that the master controller similarly
could use these devices and their associated connections to the
locomotive and use the input signals. The Communication system 657
for these other devices may be either wireless or wired.
[0159] FIG. 18 depicts an exemplary embodiment of a closed-loop
system for operating a rail vehicle integrated with another input
operational subsystem of the rail vehicle. For example the
distributed power drive controller 659 may receive inputs from
various sources 661, such as but not limited to the operator, train
lines, locomotive controllers and transmit the information to
locomotives in the remote positions. The converter 652 may provide
information directly to input of the DP controller 659 (as an
additional input) or break one of the input connections and
transmit the information to the DP controller 659. A switch 655 is
provided to direct how the converter 652 provides information to
the DP controller 659 as discussed above. The switch 655 may be a
software-based switch and/or a wired switch. Additionally, the
switch 655 is not necessarily a two-way switch. The switch may have
a plurality of switching directions based on the number of signals
it is controlling.
[0160] In another exemplary embodiment the converter may command
operation of the master controller, as illustrated in FIG. 19. The
converter 652 has a mechanical means for moving the master
controller 651 automatically based on electrical signals received
from the optimizer 650.
[0161] Sensors 654 are provided aboard the locomotive to gather
operating condition data, such as but not limited to speed,
emissions, tractive effort, horse power, etc. Locomotive output
information 654 is then provided to the optimizer 650, usually
through the rail vehicle 653, thus completing the closed loop
system.
[0162] FIG. 20 depicts an exemplary flowchart of steps for
operating a rail vehicle in a closed-loop process. The flowchart
660 includes a step for determining an optimized setting for a
locomotive consist, step 662. The optimized setting may include a
setting for any setup variable such as but not limited to at least
one of power level, optimized torque emissions, other locomotive
configurations, etc. Another step provides for converting the
optimized power level and/or the torque setting to a recognizable
input signal for the locomotive consist, step 664. At least one
operational condition of the locomotive consist is determined when
at least one of the optimized power level and the optimized torque
setting is applied, step 667. Another step involves communicating
within a closed control loop to an optimizer the at least one
operational condition so that the at least operational condition is
used to further optimize at least one of power level and torque
setting, step 668.
[0163] As disclosed above, steps illustrated in this flowchart 660
may be performed using a computer software code. Therefore for rail
vehicles that may not initially have the ability to perform the
steps disclosed herein, electronic media containing the computer
software modules may be accessed by a computer on the rail vehicle
so that at least of the software modules may be loaded onto the
rail vehicle for implementation. Electronic media is not to be
limiting since any of the computer software modules may also be
loaded through an electronic media transfer system, including a
wireless and/or wired transfer system, such as but not limited to
using the Internet to accomplish the installation.
[0164] Locomotives produce emission rates based on notch levels. In
reality, a lower notch level does not necessarily result in a lower
emission per unit output, such as for example gm/hp-hr, and the
reverse is true as well. Such emissions may include, but are not
limited to particulates, exhaust, heat, etc. Similarly, noise
levels from a locomotive also may vary based on notch levels, in
particularly noise frequency levels. Therefore, when emissions are
mentioned herein, those skilled in the art will readily recognize
that exemplary embodiments of the invention are also applicable for
reducing noise levels produced by a diesel powered system.
Therefore even though both emissions and noise are disclosed at
various times herein, the term emissions should also be read to
also include noise.
[0165] When an operator calls for a specific horse power level, or
notch level, the operator is expecting the locomotive to operate at
a certain traction power or tractive effort. In an exemplary
embodiment, to minimize emission output, the locomotive is able to
switch between notch/power/engine speed levels while maintaining
the average traction power desired by the operator. For example,
suppose that the operator calls for Notch 4 or 2000 HP. Then the
locomotive may operate at Notch 3 for a given period, such as a
minute, and then move to Notch 5 for a period and then back to
Notch 3 for a period such that the average power produced
corresponds to Notch 4. The locomotive moves to Notch 5 because the
emission output of the locomotive at this notch setting is already
known to be less than when at Notch 4. During the total time that
the locomotive is moving between notch settings, the average is
still Notch 4, thus the tractive power desired by the operator is
still realized.
[0166] The time for each notch is determined by various factors,
such as but not limited to, including the emissions at each notch,
power levels at each notch, and the operator sensitivity. Those
skilled in the art will readily recognize that embodiments of the
invention are operable when the locomotive is being operated
manually, and/or when operation is automatically performed, such as
but not limited to when controlled by an optimizer, and during low
speed regulation.
[0167] In another exemplary embodiment multiple set points are
used. These set points may be determined by considering a plurality
of factors such as, but not limited to, notch setting, engine
speed, power, engine control settings, etc. In another exemplary
embodiment, when multiple locomotives are used but may operate at
different notch/power settings, the notch/power setting are
determined as a function of performance and/or time. When emissions
are being reduced, other factors that may be considered wherein a
tradeoff may be considered in reducing emissions includes, but are
not limited to, fuel efficiency, noise, etc. Likewise, if the
desire is to reduce noise, emissions and fuel efficiency may be
considered. A similar analysis may be applied if fuel efficiency is
what is to be improved.
[0168] FIG. 21 depicts an embodiment of a speed versus time graph
comparing current operations to emissions optimized operation. The
speed change compared to desirable speed can be arbitrarily
minimized. For example if the operator desires to move from one
speed (S1) to another speed (S2) within a desired time, it can be
achieved with minor deviations.
[0169] FIG. 22 depicts a modulation pattern that results in
maintaining a constant desired notch and/or horsepower. The amount
of time at each notch depends on the number of locomotives and the
weight of the train and its characteristics. Essentially the
inertia of the train is used to integrate the tractive power/effort
to obtain a desired speed. For example if the train is heavy the
time between transitions of Notches 3 to 5 and vice versa in the
example can be large. In another example, if the number of
locomotives for a given train is great, the time between
transitions need to be smaller. More specifically, the time
modulation and/or cycling will depend on train and/or locomotive
characteristics.
[0170] As discussed previously, emission output may be based on an
assumed Notch distribution but the operator/rail road is not
required to have that overall distribution. Therefore it is
possible to enforce the Notch distribution over a period of time,
over many locomotives over a period of time, and/or for a fleet
locomotives over a period of time. By being providing emission
data, the trip optimized described herein compares the notch/power
setting desired with emission output based on notch/power settings
and determines the notch/power cycle to meet the speed required
while minimizing emission output. The optimization could be
explicitly used to generate the plan, or the plan could be modified
to enforce, reduce, and/or meet the emissions required.
[0171] FIG. 23 depicts an exemplary flowchart of steps for
determining a configuration of a diesel powered system having at
least one diesel-fueled power generating unit. One step disclosed
in the flowchart 700 provides for determining a minimum power, or
power level, required from the diesel powered system in order to
accomplish a specified mission, step 702. An emission output based
on the minimum power, or power level, required is determined, step
704. Another step provides for using at least one other power level
that results in a lower emission output wherein the overall
resulting power is proximate the power required, step 706.
Therefore in operation, the desired power level with at least
another power level may be used and/or two power levels, not
including the desired power level may be used. In the second
example, as disclosed if the desires power level is Notch 4, the
two power levels used may include Notch 3 and Notch 5.
[0172] As disclosed, emission output data based on notch speed is
provided to the trip optimizer. If a certain notch speed produces a
high amount of emission, the trip optimizer can function by cycling
between notch settings that produce lower amounts of emission
output so that the locomotive will avoid operating at the
particular notch while still meeting the speed of the avoided notch
setting. For example applying the same example provided above, if
Notch 4 is identified as a less than optimum setting to operate at
because of emission output, but other Notch 3 and 5 produce lower
emission outputs, the trip optimizer may cycle between Notch 3 and
5 where that the average speed equates to speed realized at Notch
4. Therefore, while providing speed associated with Notch 4, the
total emission output is less than the emission output expected at
Notch 4.
[0173] Therefore when operating in this configuration though speed
constraints imposed based on defining Notch limitations may not
actually be adhered to, total emission output over a complete
mission may be improved. More specifically, though a region may
impose that rail vehicles are not to exceed Notch 5, the trip
optimizer may determined that cycling between Notch 6 and 4 may be
preferable to reach the Notch 5 speed limit but while also
improving emission output because emission output for the
combination of Notch 6 and 4 are better than when operating at
Notch 5 since either Notch 4 or Notch 6 or both are better than
Notch 5.
[0174] FIG. 24 illustrates a system for minimizing emission output,
noise level, etc., from a diesel powered system having at least one
diesel-fueled power generating unit while maintaining a specific
speed. As disclosed above, the system 722 includes a processor 725
for determining a minimum power required from the diesel-powered
system 18 in order to accomplish a specified mission is provided.
The processor 725 may also determine when to alternate between two
power levels. A determination device 727 is used to determine an
emission output based on the minimum power required. A power level
controller 729 for alternating between power levels to achieve the
minimum power required is also included. The power level controller
729 functions to produce a lower emission output while the overall
average resulting power is proximate the minimum power
required.
[0175] FIG. 25 illustrates a system for minimizing such output as
but not limited to emission output and noise output from a diesel
powered system having at least one diesel-fueled power generating
unit while maintaining a specific speed. The system includes
processor 727 for determining a power level required from the
diesel-powered system in order to accomplish a specified mission is
disclosed. An emission determinator device 727 for determining an
emission output based on the power level required is further
disclosed. An emission comparison device 731 is also disclosed. The
emission comparison device 731 compares emission outputs for other
power levels with the emission output based on the power level
required. The emission output of the diesel-fueled power generating
unit 18 is reduced based on the power level required by alternating
between at least two other power levels which produce less emission
output than the power level required wherein alternating between
the at least two other power levels produces an average power level
proximate the power level required while producing a lower emission
output than the emission output of the power level required. As
disclosed herein, alternating may simply result in using at least
one other power level. Therefore though discussed as alternating,
this term is not used to be limiting. Towards this end, a device
753 is provided for alternating between the at least two power
levels and/or at least use on other power level.
[0176] Though the above examples illustrated cycling between two
notch levels to meet a third notch level, those skilled in the art
will readily recognize that more than two notch levels may be used
when seeking to meet a specific desired notch level. Therefore
three or more notch levels may be included in cycling to achieve a
specific desired not level to improve emissions while still meeting
speed requirements. Additionally, one of the notch levels that are
alternated with may include the desired notch level. Therefore, at
a minimum, the desired notch level and another notch level may be
the two power levels that are alternated between.
[0177] While exemplary embodiment of the invention has been
described with reference to an exemplary embodiment, it will be
understood by those skilled in the art that various changes,
omissions and/or additions may be made and equivalents may be
substituted for elements thereof without departing from the spirit
and scope of the invention. In addition, many modifications may be
made to adapt a particular situation or material to the teachings
of the invention without departing from the scope thereof.
Therefore, it is intended that the invention not be limited to the
particular embodiment disclosed as the best mode contemplated for
carrying out this invention, but that the invention will include
all embodiments falling within the scope of the appended claims.
Moreover, unless specifically stated any use of the terms first,
second, etc. do not denote any order or importance, but rather the
terms first, second, etc. are used to distinguish one element from
another.
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