U.S. patent application number 14/275581 was filed with the patent office on 2014-11-13 for methods for automatically optimizing ship performance and devices thereof.
This patent application is currently assigned to ESRG Technology Group, LLC. The applicant listed for this patent is ESRG Technology Group, LLC. Invention is credited to Rob Bradenham, Ken Krooner.
Application Number | 20140336853 14/275581 |
Document ID | / |
Family ID | 51865376 |
Filed Date | 2014-11-13 |
United States Patent
Application |
20140336853 |
Kind Code |
A1 |
Bradenham; Rob ; et
al. |
November 13, 2014 |
METHODS FOR AUTOMATICALLY OPTIMIZING SHIP PERFORMANCE AND DEVICES
THEREOF
Abstract
A method, non-transitory computer readable medium and
performance optimization computing device for optimizing the
performance of a ship. Data associated with one or more operational
parameters associated with the ship is obtained. One or more
performance values corresponding to the obtained data are
identified. One or more optimal operational parameters are
determined based on a comparison of the identified one or more
performance values and one or more historical performance values.
The historical performance values correspond to historical data
associated with the one or more operational parameters. The
determined one or more optimal operational parameters for the ship
are provided.
Inventors: |
Bradenham; Rob; (Alexandria,
VA) ; Krooner; Ken; (Virginia Beach, VA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
ESRG Technology Group, LLC |
Virginia Beach |
VA |
US |
|
|
Assignee: |
ESRG Technology Group, LLC
Virginia Beach
VA
|
Family ID: |
51865376 |
Appl. No.: |
14/275581 |
Filed: |
May 12, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61821724 |
May 10, 2013 |
|
|
|
Current U.S.
Class: |
701/21 |
Current CPC
Class: |
B63B 79/00 20200101;
B63B 49/00 20130101; Y02T 70/10 20130101 |
Class at
Publication: |
701/21 |
International
Class: |
B63B 9/00 20060101
B63B009/00 |
Claims
1. A method for optimizing performance of a ship, the method
comprising: obtaining, by a performance optimization computing
device, data associated with one or more operational parameters
associated with the ship; identifying, by the performance
optimization computing device, one or more performance values
corresponding to the obtained data; determining, by the performance
optimization computing device, one or more optimal operational
parameters based on a comparison of the identified one or more
performance values and one or more historical performance values,
wherein the historical performance values correspond to historical
data associated with the one or more operational parameters;
providing, by the performance optimization computing device, the
determined one or more optimal operational parameters for the
ship.
2. The method of claim 1 wherein the one or more operational
parameters comprise one of more of an engine performance value, an
electrical load value, or one or more environmental factor
values.
3. The method of claim 1 wherein the one or more performance values
comprises a fuel consumption value.
4. The method of claim 1 wherein the determined optimal operational
parameter comprises a ship speed value.
5. The method of claim 4 further comprising comparing, by the
performance optimization computing device, the determined optimal
ship speed to at least one of a current ship speed or a schedule
maintenance ship speed; and determining, by the performance
optimization computing device, a potential cost savings based on
the comparison.
6. The method of claim 4 wherein the optimal ship speed value
comprises a ship speed value that minimizes fuel consumption for
the ship at the one or more operational parameters.
7. The method of claim 4 wherein the optimal ship speed value
comprises a ship speed value that maximizes profitability of the
ship.
8. The method of claim 1 wherein the one or more performance values
comprises an engine configuration and utilization value.
9. A performance optimization computing device comprises: a memory
coupled to one or more processors which are configured to execute
programmed instructions stored in the memory comprising: obtaining
data associated with one or more operational parameters associated
with the ship; identifying one or more performance values
corresponding to the obtained data; determining one or more optimal
operational parameters based on a comparison of the identified one
or more performance values and one or more historical performance
values, wherein the historical performance values correspond to
historical data associated with the one or more operational
parameters; providing the determined one or more optimal
operational parameters for the ship.
10. The device of claim 9 wherein the one or more operational
parameters comprise one of more of an engine performance value, an
electrical load value, or one or more environmental factor
values.
11. The device of claim 9 wherein the one or more performance
values comprises a fuel consumption value.
12. The device of claim 9 wherein the determined optimal
operational parameter comprises a ship speed value.
13. The device of claim 12 wherein the one or more processors are
further configured to execute programmed instructions stored in the
memory comprising: comparing the determined optimal ship speed to
at least one of a current ship speed or a schedule maintenance ship
speed; and determining a potential cost savings based on the
comparison.
14. The device of claim 12 wherein the optimal ship speed value
comprises a ship speed value that minimizes fuel consumption for
the ship at the one or more operational parameters.
15. The device of claim 12 wherein the optimal ship speed value
comprises a ship speed value that maximizes profitability of the
ship.
16. The device of claim 9 wherein the one or more performance
values comprises an engine configuration and utilization value.
17. A non-transitory computer readable medium having stored thereon
instructions for optimizing ship performance comprising machine
executable code which when executed by at least one processor
causes the processor to perform steps comprising: obtaining data
associated with one or more operational parameters associated with
the ship; identifying one or more performance values corresponding
to the obtained data; determining one or more optimal operational
parameters based on a comparison of the identified one or more
performance values and one or more historical performance values,
wherein the historical performance values correspond to historical
data associated with the one or more operational parameters;
providing the determined one or more optimal operational parameters
for the ship.
18. The medium of claim 17 wherein the one or more operational
parameters comprise one of more of an engine performance value, an
electrical load value, or one or more environmental factor
values.
19. The medium of claim 17 wherein the one or more performance
values comprises a fuel consumption value.
20. The medium of claim 17 wherein the determined optimal
operational parameter comprises a ship speed value.
21. The medium of claim 20 further having stored thereon
instructions comprising machine executable code which when executed
by at least one processor causes the processor to perform steps
comprising: comparing the determined optimal ship speed to at least
one of a current ship speed or a schedule maintenance ship speed;
and determining a potential cost savings based on the
comparison.
22. The medium of claim 20 wherein the optimal ship speed value
comprises a ship speed value that minimizes fuel consumption for
the ship at the one or more operational parameters.
23. The medium of claim 20 wherein the optimal ship speed value
comprises a ship speed value that maximizes profitability of the
ship.
24. The medium of claim 17 wherein the one or more performance
values comprises an engine configuration and utilization value.
Description
[0001] This application claims the benefit of U.S. Provisional
Patent Application Ser. No. 61/821,724 filed May 10, 2013, which is
hereby incorporated by reference in its entirety.
FIELD
[0002] This technology relates to methods for optimizing ship
performance and devices thereof.
BACKGROUND
[0003] Optimizing ship performance results in the reduction of
total vessel fuel consumption and costs and the maximization of
vessel profitability. Fuel consumption is based on the operational
parameters of the ship, such as by way of example only actual
engine and generator performance. Fuel consumption is related to
both the amount of fuel required for propulsion of the ship
throughout its journey, as well as the fuel needed to power
necessary equipment aboard the ship during the ship's voyage. The
optimal ship speed must balance the benefits of slowing down the
ship in order to save propulsion fuel with the associated costs of
the additional electrical load impact (i.e., the power required to
operate necessary equipment) on fuel consumption resulting from the
excess time required to make the voyage at the slower rate of
speed. This optimal speed may also take into account the
opportunity for optimizing vessel profit through greater revenue by
performing more voyages, if there is additional unmet demand.
Further, ship performance may be improved based on the
configuration and utilization of various power sources.
[0004] Currently available technologies for determining optimal
ship speed or power source configuration and utilization typically
are based on a static analysis that is performed either when an
engine is being tested at the factory before being shipped or on a
ship during the initial sea trials. These calculations are often
performed as manual calculations using approximate data.
[0005] After the factory testing and initial sea tests, the optimal
operational profile of the ship will change as the vessel and
onboard equipment wear, age, are maintained, are operated, etc.
Each vessel will look slightly different and the optimal operation
parameters will change over time. The existing technologies do not
account for these various changes in the operational profile of the
ship, which directly relate to the optimal speed and power source
configuration and utilization. These existing technologies are
based on the prior, static analysis and lack any real-time analysis
of the optimal ship performance based on the real-time operational
parameters (i.e., current condition) of the ship.
SUMMARY
[0006] A method for optimizing ship performance includes obtaining,
by a performance optimization computing device, data associated
with one or more operational parameters associated with the ship.
One or more performance values corresponding to the obtained data
are identified. One or more optimal operational parameters are
determined based on a comparison of the identified one or more
performance values and one or more historical performance values.
The historical performance values correspond to historical data
associated with the one or more operational parameters. The
determined one or more optimal operational parameters for the ship
are provided.
[0007] A performance optimization computing device includes a
memory coupled to one or more processors which are configured to
execute programmed instructions stored in the memory including
obtaining data associated with one or more operational parameters
associated with the ship. One or more performance values
corresponding to the obtained data are identified. One or more
optimal operational parameters are determined based on a comparison
of the identified one or more performance values and one or more
historical performance values. The historical performance values
correspond to historical data associated with the one or more
operational parameters. The determined one or more optimal
operational parameters for the ship are provided.
[0008] A non-transitory computer readable medium having stored
thereon instructions for optimizing ship performance comprising
machine executable code which when executed by at least one
processor causes the processor to perform steps including obtaining
data associated with one or more operational parameters associated
with the ship. One or more performance values corresponding to the
obtained data are identified. One or more optimal operational
parameters are determined based on a comparison of the identified
one or more performance values and one or more historical
performance values. The historical performance values correspond to
historical data associated with the one or more operational
parameters. The determined one or more optimal operational
parameters for the ship are provided.
[0009] This technology provides a number of advantages including
providing more effective methods, devices, and non-transitory
computer readable media for optimizing ship performance. This
technology provides a real-time analysis of the optimal ship
performance parameters, such as speed and the configuration and
utilization of various power sources, based on the current
operational parameters of the ship and the current condition of the
ship. Additionally, this technology provides real-time optimization
information that may be utilized by stakeholders, such as the ship
owner, ship manager, ship technical superintendent, original
equipment manufacturer, service providers, port engineers, and
other third parties to make better decisions regarding the ship's
schedule, maintenance of ship equipment, and load planning for the
ship.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] FIG. 1 is an exemplary network environment comprising a
performance optimization computing device;
[0011] FIG. 2 is an exemplary functional block diagram of the
performance optimization computing device;
[0012] FIG. 3 is an exemplary functional block diagram of the
modules within a memory of the performance optimization computing
device; and
[0013] FIG. 4 is a flowchart of an example of a method of
optimizing ship performance.
DETAILED DESCRIPTION
[0014] An exemplary network environment 10 with a performance
optimization computing device 12 for optimizing ship speed is
illustrated in FIG. 1. The exemplary network environment 10
includes the performance optimizing computing device 12, a
plurality of user devices 14(1)-14(n), and one or more ship
operational systems 16(1)-16(n) which are coupled together by the
communication networks 30, although the environment can include
other types and numbers of devices, components, elements and
communication networks in a variety of other topologies and
deployments. While not shown, the exemplary environment 10 may
include additional components, such as routers, switches and other
devices which are well known to those of ordinary skill in the art
and thus will not be described here. The exemplary network
environment 10 may be contained within a ship, solely onshore, or
spread across onboard and onshore locations. This technology
provides a number of advantages including providing a more
effective method, non-transitory computer readable medium, and
device for optimizing ship performance.
[0015] Referring more specifically to FIG. 1, performance
optimization computing device 12 interacts with the plurality of
user devices 14(1)-14(n) and the one or more ship operational
systems 16(1)-16(n) through the communication networks 30, although
the performance optimization computing device 12 can interact with
the plurality of user devices 14(1)-14(n) and the one or more ship
operational systems 16(1)-16(n) using other methods or techniques.
Communication networks 30 include local area networks (LAN), wide
area network (WAN), 3G technologies, GPRS or EDGE technologies,
although the communication networks 30 can include other types and
numbers of networks and other network topologies. The
communications take place over the communication networks according
to standard network protocols, such as the Modbus, OPC, NMEA, HTTP,
UDP, and/or TCP/IP protocols.
[0016] The performance optimization computing device 12 optimizes
ship performance within a network environment 10 as illustrated and
described with the examples herein, although performance
optimization computing device 12 may perform other types and
numbers of functions in other types of networks. As illustrated in
FIG. 2, the performance optimization computing device 12 includes
at least one processor 18, a memory 20, an input device 22, a
display device 23, and input/output (I/O) system 24 which are
coupled together by bus 26, although the performance optimization
computing device 12 may comprise other types and numbers of
elements in other configurations.
[0017] Processor(s) 18 may execute one or more computer-executable
instructions stored in the memory 20 for the methods illustrated
and described with reference to the examples herein, although the
processor(s) can execute other types and numbers of instructions
and perform other types and numbers of operations. The processor(s)
18 may comprise one or more central processing units ("CPUs") or
general purpose processors with one or more processing cores, such
as AMD.RTM. processor(s), although other types of processor(s)
could be used (e.g., Intel.RTM.).
[0018] Memory 20 may comprise one or more tangible storage media,
such as RAM, ROM, flash memory, CD-ROM, floppy disk, hard disk
drive(s), solid state memory, DVD, or any other memory storage
types or devices, including combinations thereof, which are known
to those of ordinary skill in the art. Memory 20 may store one or
more programmed instructions of this technology as illustrated and
described with reference to the examples herein that may be
executed by the one or more processor(s) 18. By way of example
only, the flow chart shown in FIG. 4 is representative of
programmed steps or actions of this technology that may be embodied
or expressed as one or more non-transitory computer or machine
readable having stored instructions stored in memory 20 that may be
executed by the processor(s) 18, although other types and numbers
of programmed instructions and/or other data may be stored. Memory
20 may also store data from the ship operational systems
16(1)-16(n) (as shown in FIG. 1), although the data could be stored
in other locations on other devices.
[0019] Additionally as illustrated in FIG. 3, the memory 20
includes a main engine data manager 300, an auxiliary engine data
manager 302, a trip data module 304, an efficiency manager 306, a
scheduler manager 308, a heuristics manager 310, a command manager
312 and a reporting module 314, although the memory 20 may include
other types and numbers of modules and/or other programmed
instructions or other data.
[0020] The main engine data manager 300 receives input data in real
time from one or more ship operational systems 16(1)-16(n)
associated with the main engines, although main engine data manager
300 may receive input data from other sources, such as user devices
14(1)-14(n). In particular, the input data is associated with the
main engines operating to propel and/or maneuver or steer the ship.
Such input data may include, by way of example only, engine fuel
consumption data (from fuel flow meters), engine temperature,
trim/draft and displacement data, engine power, shaft power/torque,
although other data related to the one or more main engines may be
input. Engine performance data such as lube oil pressures and
temperatures, fuel oil pressures and temperatures, bearings data
and/or other data associated with the efficiency and performance
information of the main engine(s) may also be input.
[0021] The main engine data manager 300 may also receive input data
associated with one or more boiler systems on the ship (if
applicable) from one or more ship operational systems 16(1)-16(n),
although main engine data manager 300 may receive input data from
other sources, such as user devices 14(1)-14(n). The boiler system
may be configured to consume fuel to power one or more turbines,
auxiliary engines or other systems or services, although it is
contemplated that the boiler system may be configured to
efficiently utilize and convert excess energy such as heat to power
turbines, auxiliary engines or other systems or services. For
example, the boiler system may be utilized to produce steam for
ship's services as well as fresh water on the ship.
[0022] The auxiliary engine data manager 302 receives data
associated with the amount of fuel that one or more of the ship's
auxiliary engines consume in order to meet electrical load demands
while the ship is operating from one or more ship operational
systems 16(1)-16(n), although auxiliary engine data manager 302 may
receive input data from other sources, such as user devices
14(1)-14(n). In particular, the auxiliary engine data manager 302
receives input data associated with fuel consumed by the one or
more auxiliary engines. Additionally, the auxiliary engine data
manager 302 receives input data from one or more real time data
sources, such as sensors, which represent the fuel consumed by the
auxiliary engines in providing electrical power to the various
systems and components which demand electrical power. Such systems
and components which require electrical power include, but are not
limited to, air compressors, lighting systems, air
conditioning/heating systems, sewage and water pumps, plumbing
systems, freezers, refrigeration systems, steering systems, anchor
systems, electro hydraulic equipment, oil waste transfer systems,
ballast tank pumps, communication systems, computer systems,
navigation systems, and the like.
[0023] The trip data manager 304 receives data associated with
factors which are not related to propulsion or electrical load
information handled by the main and/or auxiliary engine(s) of the
ship from one or more ship operational systems 16(1)-16(n),
although trip data manager 304 may receive input data from other
sources such as user devices 14(1)-14(n). Such information may be
manually entered, automatically retrieved from onboard computers
(e.g. navigation/GPS systems, ship charting systems) or remote
communication systems. Trip data includes, but is not limited to,
draft/trim and displacement information, ship speed data, fuel cost
data, wind state, air temperature, weather data, sea state (i.e.,
wave height, choppiness), navigation details, port information,
distance information, head/tail wind data, geopolitical information
(embargos, conflict zones), operational cost data (crew and
supplies costs), charter revenue price rates, fuel density and
specific gravity data, seawater and ambient air temperature and
other relevant environmental factors, or trip information
(distance, time of voyage).
[0024] The efficiency manager 306 is configured to analyze the
amount of fuel consumed by differing combinations of (main and/or
auxiliary) engines to meet load demand. For example, a ship may
have a plurality of auxiliary engines, each of which are of
differing ages, models, or load handling capacities, wherein the
efficiency manager would determine that a certain combination of
engines simultaneously operating to meet a certain electrical or
propulsion demand would consume less fuel than another combination
of engines. The efficiency manager 306 continually monitors input
data provided by one or more of the data managers 300, 302, 304 and
analyzes the data to effectively calculate varying fuel
consumptions for those associated load demands for different
combinations of engines and utilization rates for the engines. The
efficiency manager 306 may also analyze and select fuel consumption
scenarios for one or more main engines in addition or alternatively
to auxiliary engines. The efficiency manager 306 is configured to
continuously refresh the optimal main engine and auxiliary engine
combinations. For example, this could be configured to `look for`
the best combination of Auxiliary Engine performance and fuel
consumption over the past 90 (or other number of) days.
[0025] The heuristics manager 310 communicates with the efficiency
manager 306 and stores as well as organizes historical data of the
analyzed results provided by the efficiency manager 306. This
monitored information as well as the analyzed results are time
stamped and provided to the heuristics manager 310. In an example,
the electrical load on a ship containing multiple refrigerated
containers and four auxiliary engines or generators can be between
1,000 kilowatts or 3,500 kilowatts. In the event that the
electrical load demand changes, either one, two, three or all four
of those generators may be used to meet demand. The efficiency
manager 306 may determine that not all of the four generators are
the same as they may be different models, of differing handling
capacities, of different material condition, of different age, of
different current performance, or of different time from last
overhaul, for example, which causes the generators to perform at
different efficiencies from one another for a particular load
demand. The efficiency manager 306 along with the heuristics
manager 310 may determine, for a load demand of 2000 kilowatts,
that the most fuel efficient combination are generators #1 and #3.
In contrast, for an electrical load demand of 2200 kilowatts, the
efficiency manager 306 along with the heuristics manager 310 may
determine that operating generators #2 and #4 yields the highest
fuel efficiency. The efficiency manager 306 may also utilize
historical data handled by the heuristics manager 310 in making
decisions on which combination of engines should be used for a
particular load demand.
[0026] The scheduler manager 308 receives input data from the main
engine data manager 300, the auxiliary engine data manager 302, the
trip data manager 304 as well as the efficiency manager 306 and the
heuristics manager 310 to determine the optimal speed that the ship
should be cruising at while consuming the least amount of fuel to
ensure that all electrical and power load demands are adequately
met. The scheduler manager 308 may also be configured to determine
the optimal speed the ship should be travelling at to optimize ship
profit.
[0027] In particular, the scheduler manager optimizes between
slowing down to save propulsion fuel with the excess time required
to transit and the electrical load impact on fuel consumption
during a longer/shorter voyage. The scheduler manager 308 takes
into account real time data from the main engine data manager 300,
the auxiliary engine data manager 302 and the trip data manager 304
and calculates an optimal speed at which the ship should be
operating at to achieve the most fuel efficient consumption rate
while conforming to the established schedule on which the ship is
to reach its destination. When optimizing for ship profit, the
scheduler manager 308 will also balance the impact of speeding up
and potentially achieving more revenue.
[0028] The command manager 312 allows instructions to be provided
manually by display or electronically to another computer, such as
the user device 14(1). The reporting manager 314 provides
information, data, reports and other information to be displayed by
to the user via a display screen such as on user device 14(1).
[0029] Referring again to FIG. 2, the input device 22 enables a
user, such as an administrator, to interact with the utility
management computing device 14, such as to input and/or view data
and/or to configure, program and/or operate it by way of example
only. By way of example only, input device 22 may include one or
more of a touch screen, keyboard and/or a computer mouse.
[0030] The display device 23 enables a user, such as an
administrator, to interact with the utility management computing
device 14, such as to view and/or input information and/or to
configure, program and/or operate it by way of example only. By way
of example only, the display device 23 may include one or more of a
CRT, LED monitor, LCD monitor, or touch screen display technology
although other types and numbers of display devices could be
used.
[0031] The I/O system 24 in the performance optimization computing
device 12 is used to operatively couple and communicate between the
performance optimization computing device 12, the user computing
devices 14(1)-14(n), and the one or more ship operational systems
16(1)-16(n), which are all coupled together by communication
network 30. The I/O system engages in network communications over
communication network 30 utilizing standard network protocols such
as Modbus, OPC, NMEA, TCP/IP, HTTP, UDP, RADIUS, or DNS, by way of
example only. In this example, the bus 26 is a hyper-transport bus,
although other bus types and links may be used, such as PCI.
[0032] Each of the plurality of user computing devices 14(1)-14(n)
includes a central processing unit (CPU) or processor, a memory, an
input device, a display device, and an input/output (I/O) system,
which are coupled together by a bus or other link, although other
numbers and types of network devices could be used. The plurality
of user devices 14(1)-14(n) communicate with the performance
optimization computing device 12 to allow a user to manually input
information related to operational parameters for the ship, such as
fuel cost, fuel type and density, fixed costs (e.g., crew costs,
depreciation), or revenue rates, to the performance optimization
computing device 12. The plurality of user computing devices
14(1)-14(n) may run interface application(s), such as a Web
browser, that may provide an interface to input data and receive
content and/or communicate with web applications stored on the
performance optimization computing device 12 via the communication
network 30.
[0033] The network environment 10 also includes the one or more
ship operational systems 16(1)-16(n). Each of the plurality of ship
operational systems 16(1)-16(n) includes a central processing unit
(CPU) or processor, a memory, an interface device, and an I/O
system, which are coupled together by a bus or other link, although
other numbers and types of network devices could be used. The ship
operational systems 16(1)-16(n) are various measurement devices on
the ship utilized to measure operational parameters related to the
ship. The plurality of ship operational systems 16(1)-16(n)
communicate with the performance optimization computing device 12
through communication network 30, although the ship operational
systems 16(1)-16(n) can interact with the performance optimization
computing device 12 using other techniques. The ship operational
systems 16(1)-16(n) measure and communicate data associated with
one or more ship operational parameters, such as electrical load
required, draft/displacement, engine power, shaft power/torque,
speed through water, generator performance, engine performance,
engine fuel consumption, boiler fuel consumption, wind, current,
sea state, generator combination and configuration, or
environmental factors by way of example to the performance
optimization computing device 12.
[0034] Although an exemplary network environment 10 with the
plurality of user computing devices 12(1)-12(n), performance
optimization computing device 14 and plurality of ship operational
systems 16(1)-16(n) are described and illustrated herein, other
types and numbers of systems, devices in other topologies can be
used. It is to be understood that the systems of the examples
described herein are for exemplary purposes, as many variations of
the specific hardware and software used to implement the examples
are possible, as will be appreciated by those skilled in the
relevant art(s). By way of example, the systems of the present
technology can be contained within a ship, solely be onshore, or
spread across onboard the vessel and onshore locations.
[0035] Furthermore, each of the systems of the examples may be
conveniently implemented using one or more general purpose computer
systems, microprocessors, digital signal processors, and
micro-controllers, programmed according to the teachings of the
examples, as described and illustrated herein, and as will be
appreciated by those of ordinary skill in the art.
[0036] The examples may also be embodied as a non-transitory
computer readable medium having instructions stored thereon for one
or more aspects of the present technology as described and
illustrated by way of the examples herein, as described herein,
which when executed by a processor, cause the processor to carry
out the steps necessary to implement the methods of the examples,
as described and illustrated herein.
[0037] An example of a method for optimizing ship performance will
now be described with reference to FIGS. 1-4. Referring more
specifically to FIG. 4, an example of the method is described with
respect to optimizing the speed of the ship, although other
operational parameters related to the performance of the ship, such
as by way of example only engine utilization, may be optimized
using the exemplary method.
[0038] In step 400, the performance optimization computing device
12 obtains data associated with one or more operational parameters.
The performance optimization computing device 12 receives one or
more operational parameters in real-time from the ship operational
systems 16(1)-16(2), which may include the electrical load
necessary to operate the onboard equipment, draft/displacement of
the ship, engine power, shaft power/torque, speed through water,
generator performance, engine performance, environmental conditions
such as wind, current, or sea state, or generator
combination/configuration, although other operational parameters
may be received from the one or more ship operational systems
16(1)-16(n). The performance optimization computing device 12 may
also obtain data associated with operational parameters, such as
fuel cost, fuel type, trip information, costs, or revenue, from the
one or more user devices 14(1)-14(2), althought the performance
optimization computing device 12 may obtain other types of data
associated with operational parameters from other sources.
[0039] In step 410, the performance optimization computing device
12 identifies one or more performance values, such as by way of
example fuel consumption, corresponding to the obtained data,
although other performance values may be utilized. Although other
performance values may be utilized, the method will be described in
relation to fuel consumption. The fuel consumption value indicate
the performance of the ship based on the current operational
parameters, that is a lower fuel consumption value indicates more
efficient operation of the ship at the current operational
parameters.
[0040] In step 415, the performance optimization computing device
12 stores the obtained data from the ship operational systems
16(1)-16(n) along with the fuel consumption value in memory 20,
althought the obtained data may be stored in other locations or on
other devices, such as an external storage system (i.e., in a third
party data historian system). In one example, the stored data and
fuel consumption value may be time-stamped. The obtained data may
be stored over a period of time such as a month, a year, a season,
or a particular voyage time. The data is continuously updated over
the period of time in order to provide an accurate assessment of
the current condition of the ship. The operation data may be stored
in a table which correlates the operational parameters, such as
electrical load and displacement, with the fuel consumption
data.
[0041] Next, in step 420 the performance optimization computing
device 12 compares the current obtained data and associated fuel
consumption values with historical data stored in the memory 20.
The obtained data is compared against the data stored for the
relevant time period. The data is compared to identify different
fuel consumption values for the same operational parameters at
different rates of speed for the ship, although other comparisons
of other types and numbers of values may be utilized. By way of
example, the performance optimization computing device 12 may
determine whether the is a more efficient value for fuel
consumption in the stored table based on the obtained data. The
table may be updated if the current operational parameters yield a
more efficient value.
[0042] In step 425, the performance optimization computing device
12 determines, based on the comparison in step 420, an optimal
speed for the ship at the current operational parameters, although
the performance optimization device 12 may determine optimal values
for other parameters such as engine configuration or utilization
among several engines. The performance optimization computing
device 12 determines if the ship is currently travelling at the
optimal speed In one example, the optimal speed for the ship is
determined using a regression analysis, although other methods may
be utilized to determine the optimal speed. By way of example, the
performance optimization computing device 12 correlates speed of
the ship to the operational parameters to determine the speed at
which the ship has the most efficient fuel consumption value.
[0043] Next, in step 430, the performance optimization computing
device 12 provides the optimal speed. By way of example, the
optimal speed may be displayed on one or more of the user devices
14(1)-14(n), although the optimal speed may be displayed on other
devices in other locations. The optimal speed for the ship may be
continuously updated based on changes in operational parameters for
the ship. By way of example, an increase in temperature may require
an increased electrical load to operate refrigeration equipment on
the ship. The increased electrical load will impact the optimal
speed at which the ship should travel to minimize fuel consumption
over the course of the ship's voyage.
[0044] In step 435, the performance optimization computing device
12 compares the optimal speed provided in step 430 with a current
speed or a ship schedule maintenance speed, although the optimal
speed may be compared with other values. By way of example, the
ship schedule maintenance speed is the speed that the ship must
travel at to complete its voyage in the scheduled amount of time
allotted for the voyage. The performance computing device 12 may
indicate the difference between the optimal speed and the required
schedule maintenance speed to provide information to ship operators
that may be utilized to revise scheduling practices.
[0045] In step 440, the performance optimization computing device
12 determines a potential cost savings based on travelling at the
optimal speed based on the comparison in step 435. The performance
optimization computing device 12 determines the potential cost
savings based on the obtained data, which may include trip
information, costs information, and revenue information.
[0046] In step 445, the performance optimization computing device
12 provides the potential cost savings. By way of example, the
potential cost savings may be displayed on one or more of the user
devices 14(1)-14(n), although the potential cost savings may be
displayed on other devices in other locations. The potential cost
savings may be utilized to monitor and modify shipping practices
for the ship.
[0047] This technology provides a number of advantages including
providing more effective methods, devices, and non-transitory
computer readable media for optimizing ship performance. The
present technology provides a real-time analysis of the optimal
ship performance parameters, such as speed and the configuration
and utilization of various power sources, based on the current
operational parameters of the ship and the current condition of the
ship.
[0048] Having thus described the basic concept of the invention, it
will be rather apparent to those skilled in the art that the
foregoing detailed disclosure is intended to be presented by way of
example only, and is not limiting. Various alterations,
improvements, and modifications will occur and are intended to
those skilled in the art, though not expressly stated herein. These
alterations, improvements, and modifications are intended to be
suggested hereby, and are within the spirit and scope of the
invention. Additionally, the recited order of processing elements
or sequences, or the use of numbers, letters, or other designations
therefore, is not intended to limit the claimed processes to any
order except as may be specified in the claims. Accordingly, the
invention is limited only by the following claims and equivalents
thereto.
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