U.S. patent application number 17/717886 was filed with the patent office on 2022-08-04 for vehicle power management systems and methods.
The applicant listed for this patent is Invently Automotive Inc.. Invention is credited to Stephen J. Brown, Nicole G. Goldstein, Jason H. Harper, Martin Koebler.
Application Number | 20220242239 17/717886 |
Document ID | / |
Family ID | 1000006256107 |
Filed Date | 2022-08-04 |
United States Patent
Application |
20220242239 |
Kind Code |
A1 |
Koebler; Martin ; et
al. |
August 4, 2022 |
Vehicle Power Management Systems and Methods
Abstract
A method of vehicle operation includes, using one or more
processors, receiving one or more inputs from one of one or more
sensors of a first vehicle and one or more external sources
communicatively coupled with the one or more processors. The one or
more processors determine a plurality of optional routes existing
between a first location of the first vehicle and a future
destination of the first vehicle. Using the one or more inputs, the
one or more processors predict a vehicle route by predicting which
of the optional routes the first vehicle will take to get from the
first location to the future destination.
Inventors: |
Koebler; Martin;
(Saal/Donau, DE) ; Goldstein; Nicole G.;
(Woodside, CA) ; Brown; Stephen J.; (Malibu,
CA) ; Harper; Jason H.; (Pleasanton, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Invently Automotive Inc. |
Los Altos |
CA |
US |
|
|
Family ID: |
1000006256107 |
Appl. No.: |
17/717886 |
Filed: |
April 11, 2022 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16433261 |
Jun 6, 2019 |
11325468 |
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17717886 |
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15720032 |
Sep 29, 2017 |
10919409 |
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16433261 |
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15626676 |
Jun 19, 2017 |
11065977 |
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15720032 |
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14566848 |
Dec 11, 2014 |
9682624 |
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15626676 |
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14206138 |
Mar 12, 2014 |
8972162 |
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14566848 |
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13066189 |
Apr 8, 2011 |
8712650 |
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14206138 |
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11283137 |
Nov 17, 2005 |
7925426 |
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13066189 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 7/00 20130101; B60L
2240/547 20130101; B60L 2240/423 20130101; B60L 2250/10 20130101;
G01C 21/3617 20130101; B60L 2240/441 20130101; B60K 35/00 20130101;
B60L 2240/445 20130101; Y02T 10/70 20130101; B60L 2240/667
20130101; G07C 5/008 20130101; B60L 2240/421 20130101; B60L 2240/12
20130101; B60L 2240/665 20130101; B60T 7/18 20130101; B60T 2201/04
20130101; Y02T 10/40 20130101; B60L 2250/16 20130101; G08G 1/096775
20130101; B60T 13/586 20130101; B60L 2240/549 20130101; Y02T 10/72
20130101; B60L 2240/545 20130101; Y02T 10/7072 20130101; B60W 10/11
20130101; B60W 30/143 20130101; B60W 2556/50 20200201; B60L 3/12
20130101; B60L 2240/622 20130101; G07C 5/085 20130101; B60L 2240/68
20130101; B60W 2556/10 20200201; B60L 2240/647 20130101; Y02T 10/64
20130101; B60L 2240/645 20130101; B60K 2370/15 20190501; B60L 8/003
20130101; Y02T 90/16 20130101; B60L 58/12 20190201; B60L 2240/443
20130101; B60W 50/0097 20130101; B60L 2240/662 20130101; B60L
15/2045 20130101; B60L 7/12 20130101; B60L 2240/642 20130101; B60W
2552/20 20200201; B60T 1/10 20130101; B60L 50/62 20190201; B60T
2210/36 20130101; G01C 21/3469 20130101; G08G 1/096844 20130101;
B60T 7/22 20130101; B60W 10/06 20130101; B60L 2220/44 20130101;
B60L 2260/28 20130101; B60L 58/16 20190201; B60L 2260/50 20130101;
B60K 2370/174 20190501; Y02T 10/62 20130101 |
International
Class: |
B60K 35/00 20060101
B60K035/00; B60L 8/00 20060101 B60L008/00; G06F 7/00 20060101
G06F007/00; B60L 15/20 20060101 B60L015/20; G07C 5/08 20060101
G07C005/08; B60L 50/62 20060101 B60L050/62; B60W 10/11 20060101
B60W010/11; B60W 30/14 20060101 B60W030/14; G08G 1/0967 20060101
G08G001/0967; B60T 7/22 20060101 B60T007/22; B60W 50/00 20060101
B60W050/00; G08G 1/0968 20060101 G08G001/0968; B60T 7/18 20060101
B60T007/18; G01C 21/36 20060101 G01C021/36; B60T 1/10 20060101
B60T001/10; B60W 10/06 20060101 B60W010/06; B60L 58/12 20060101
B60L058/12; B60L 58/16 20060101 B60L058/16; B60L 7/12 20060101
B60L007/12; B60T 13/58 20060101 B60T013/58; B60L 3/12 20060101
B60L003/12; G01C 21/34 20060101 G01C021/34 |
Claims
1. A method of vehicle operation, comprising: using one or more
processors: receiving one or more inputs from one of one or more
sensors of a first vehicle and one or more sources communicatively
coupled with the one or more processors; determining a plurality of
optional routes existing between a first location of the first
vehicle and a future destination of the first vehicle; and using
the one or more inputs, predicting a vehicle route by predicting
which of the optional routes the first vehicle will take to get
from the first location to the future destination.
2. The method of claim 1, wherein the future destination is a
destination at which the first vehicle will be parked and turned
off.
3. The method of claim 1, wherein a plurality of intermediary
destinations exist between the first location and the future
destination, and wherein the method further comprises predicting
which of the intermediary destinations the first vehicle will
traverse between the first location and the future destination.
4. The method of claim 3, wherein the one or more processors
predict the intermediary destinations without determining the
future destination and without having received the future
destination.
5. The method of claim 1, further comprising, using the one or more
processors, determining information about operational status of the
first vehicle, user command inputs to the first vehicle, and one or
more operational parameters of the first vehicle.
6. The method of claim 5, further comprising updating the one or
more operational parameters of the first vehicle from a remote
source.
7. The method of claim 5, wherein the one or more operational
parameters of the first vehicle are communicated to the first
vehicle from an external source.
8. The method of claim 1, further comprising updating control logic
of the one or more processors from a remote source.
9. The method of claim 1, further comprising preventing flooding of
an engine of the first vehicle by overriding a user command
input.
10. The method of claim 1, further comprising the one or more
processors using a distance between the first vehicle and a second
vehicle as an input to increase an energy efficiency of the first
vehicle.
11. An apparatus comprising: a first vehicle having a power source
and a communication system; and one or more processors configured
to: receive one or more inputs from one of one or more sensors of
the first vehicle and the communication system; determine a
plurality of optional routes existing between a first location of
the first vehicle and a future destination of the first vehicle;
and using the one or more inputs, predict a vehicle route by
predicting which of the optional routes the first vehicle will take
to get from the first location to the future destination.
12. The apparatus of claim 11, wherein the future destination is a
destination at which the first vehicle will be parked and turned
off.
13. The apparatus of claim 11, wherein a plurality of intermediary
destinations exist between the first location and the future
destination, and wherein the one or more processors are further
configured to determine which of the intermediary destinations the
first vehicle will traverse between the first location and the
future destination.
14. The apparatus of claim 13, wherein the one or more processors
are configured to predict the intermediary destinations without
determining the future destination and without having received the
future destination.
15. The apparatus of claim 11, wherein the one or more processors
are configured to prevent flooding of an engine of the first
vehicle by overriding a user command input.
16. The apparatus of claim 11, wherein the one or more processors
are configured to use a distance between the first vehicle and a
second vehicle as an input to increase an energy efficiency of the
first vehicle.
17. An apparatus, comprising: a vehicle having one or more
processors configured to: determine a vehicle route; determine
information about operational status of the vehicle; determine
information about an external environment of the vehicle, including
identifying an uphill portion and a downhill portion along the
vehicle route; determine a location of the vehicle along the
vehicle route; and maximize an energy efficiency of the vehicle
along the vehicle route, within one or more constraints, by
controlling one of: a difference in a speed of the vehicle on the
downhill portion relative to a speed of the vehicle on the uphill
portion; and a ratio of energy from a first power source of the
vehicle and a second power source of the vehicle.
18. The apparatus of claim 17, wherein the first power source
comprises an electric power source and the second power source
comprises an internal combustion engine, and wherein the one or
more processors maximize the energy efficiency at least in part by:
adjusting the ratio of energy from the first power source and the
second power source while traveling on the uphill portion so that
the first power source is exhausted on the uphill portion; and
charging the first power source while traveling on the downhill
portion.
19. The apparatus of claim 17, wherein the one or more processors
maximize the energy efficiency at least in part by increasing a
speed of the vehicle on the downhill portion when the one or more
processors determine that the uphill portion is upcoming.
20. The apparatus of claim 17, wherein the determined information
about operational status of the vehicle includes a weight of the
vehicle and a speed of the vehicle, and wherein the determined
information about the external environment of the vehicle includes
a road grade.
Description
[0001] This application is a continuation application of U.S.
patent application Ser. No. 16/433,261, filed Jun. 6, 2019, which
is a continuation of U.S. patent application Ser. No. 15/720,032,
filed Sep. 29, 2017, now U.S. Pat. No. 10,919,409, which is a
continuation of U.S. patent application Ser. No. 15/626,676, filed
Jun. 19, 2017, now U.S. Pat. No. 11,065,977, which is a
continuation of U.S. patent application Ser. No. 14/566,848, filed
Dec. 11, 2014, now U.S. Pat. No. 9,682,624, which is a continuation
of U.S. patent application Ser. No. 14/206,138, filed Mar. 12,
2014, now U.S. Pat. No. 8,972,162, which is a continuation of U.S.
patent application Ser. No. 13/066,189, filed Apr. 8, 2011, now
U.S. Pat. No. 8,712,650, which is a continuation of U.S. patent
application Ser. No. 11/283,137, filed Nov. 17, 2005, now U.S. Pat.
No. 7,925,426, each of which is incorporated herein by reference in
its entirety.
FIELD OF THE INVENTION
[0002] The invention relates to devices, methods and systems for
controlling power applied to a vehicle engine.
BACKGROUND OF THE INVENTION
[0003] Currently, drivers of automotive vehicles have only very
imprecise methods for managing the fuel consumption of their cars.
For example, drivers can slow down, they can brake lightly, and
they can carry lighter loads. Generally, however, fuel consumption
cannot be precisely controlled by the driver. More accurate and
precise control of fuel consumption is one of the best ways to
improve the energy efficiency of most cars. In particular, accurate
control of fuel consumption may optimize the energy efficiency of a
car.
[0004] It has been shown that you can reduce fuel usage by
efficient driving. According to Amory Lovins of the Rocky Mountain
Institute, a 35% improvement in miles per gallon (mpg) for all 2001
vehicles (whose overall average mpg was 20) would have reduced oil
use in the United States by 2.7 Mbbl/d, approximately the same
amount that the U.S. imported from the Gulf. See, for example,
"Winning the Oil Endgame," Rocky Mountain Institute, 2004. p.50.
Empirical evidence also supports the assertion that efficient
driving can reduce fuel usage. For example, the Honda Insight.TM.,
a car available to the general public that normally gets 60 mpg,
broke records in 2000 by getting 102 miles per gallon in a 7-day
drive around the circumference of Britain. The team responsible did
this purely by driving more efficiently, and not by modifying the
car in any manner.
[0005] In most automotive vehicles, an operator controls the power
applied to the vehicle (e.g., the engine of the vehicle) by
operating the ignition, break and gas petals. Additional control is
typically provided by operational assisting devices, such as a
cruise control, that help to keep the vehicle at a constant speed,
or within a range of speeds. However, such operational assisting
devices typically do not optimize the power consumption of the
vehicle, or control the speed and/or power provided to the vehicle
based on an optimal power consumption level.
[0006] Many parameters may impact the optimal power consumption of
a vehicle, including external factors (e.g., forces and conditions
that act on the vehicle), internal conditions (e.g., the current
status of the vehicle and it's component parts), operator commands
(e.g., control commands from the operator driving or preparing to
drive the vehicle), and operational parameters of the vehicle
(e.g., performance capabilities of the vehicle based on the make
and model and/or the component parts of the vehicle, as well as the
historical performance of the vehicle).
[0007] In recent years the need for energy efficient vehicles has
increased as the cost and availability of traditional fossil fuels
has fluctuated. However, the need for fuel efficiency spans all
types of vehicles, including currently available vehicles (e.g.,
internal combustion, solar, electric, and hybrid vehicles), as well
as vehicles proposed or under development (e.g., hydrogen fuel cell
vehicles and other electrically-fueled vehicles). In all of these
types of vehicles, the overall fuel efficiency (regardless of the
type of fuel), can be improved by optimizing the power supplied to
the engine. As described herein, energy efficiency may be fuel
efficiency or power efficiency. Energy supplied to the vehicle
(e.g., the engine) may come from any appropriate source (e.g., gas,
solar, battery, hydrogen, ethanol, etc.).
[0008] Thus, there is a need for devices and systems for
controlling the power applied to a vehicle engine. The devices,
systems and methods described herein address many problems
identified for controlling the power supplied to automotive engines
raised above.
SUMMARY OF THE INVENTION
[0009] The invention concerns an apparatus comprising an interface,
a memory and a processor. The interface may be configured to
receive sensor data samples during operation of a vehicle. The
memory may be configured to store the sensor data samples over a
number of points in time. The processor may be configured to
analyze the sensor data samples stored in the memory to detect a
pattern. The processor may be configured to manage an application
of brakes of the vehicle in response to the pattern.
[0010] Described herein are devices, systems, and methods for
managing the power consumption of an automotive vehicle, and
thereby for optimizing the power consumption of the vehicle. The
devices and systems for managing the power consumption of the
vehicle typically include power management logic that can calculate
an applied power for the vehicle engine based on information
provided from the external environment of the vehicle, the
operational status of the vehicle, one or more command inputs from
a driver, and one or more operational parameters of the vehicle.
The information provided to the power management logic may come
from data inputs (e.g., sensors, telemetries, etc.), memory, user
commands, or it may be derived. The power management logic may
comprise software, hardware, or any combination of software or
hardware. In some variations, the devices and systems include a
processor (e.g., a microprocessor) that can perform the power
management logic, and provide an applied power. The applied power
that is determined by the power management logic may be used to
control the vehicle engine. For example, the power management logic
may be used by a motor control mechanism to control the application
of power to the vehicle engine as the vehicle travels along a route
(either a predetermined or a non-predetermined route). The applied
power may also be expressed as an optimized speed or speeds to
which the vehicle is controlled. For example, the motor control
mechanism may adjust the speed of the vehicle to an optimized speed
or speeds as the vehicle travels. Or, the device or system may
provide a suggested fuel-efficient speed to the driver, who in turn
will manually adjust his/her speed. Thus, the devices, systems, and
methods described herein may optimize the power consumption of an
automotive vehicle by controlling the final speed of the vehicle,
for example, by controlling the power applied to the vehicle
motor.
[0011] The system may be manually engaged by the operator either
when the vehicle is turned on, or in the midst of a trip (e.g., "on
the fly"). In one variation, the operator sets a preferred speed,
and a range at which to manage that speed (e.g., the preferred
speed may be 60 mph, and the range can be 5 mph) over at least a
portion of the trip. The system may determine an optimal (e.g.,
fuel efficient) speed within the range selected. By calculating and
then averaging the efficient speed over a given route, the system
can optimize energy usage within the driver's stated speed and
range. The power management logic may determine energy efficiency
over the course of a trip, based on current location and
destination. The destination of the driver does not have to be
known (e.g., input into a GPS or other similar system by the
driver). The system (e.g., anticipated destination logic) may infer
the driver's destination based on a subset of the information
inputs to the system, such as the time of day, current location,
previous driving habits, and other inputs. In some variations, the
driver can manually accelerate (e.g., override the system) for
passing, braking and the like. In some variations, the device or
system may provide a suggested speed to the driver to match, in
order for the driver to better optimize power usage.
[0012] In some variations, the system is automatically enabled
whenever the vehicle is turned on. In this case, the operator of
the vehicle does not have to set any a destination, target speed or
range, or the like. By automatically monitoring the operator's
real-time speed, braking and acceleration, and by utilizing
applicable inputs (e.g., from sensors and/or from a database), the
power management system may determine the most efficient speed to
travel a route. In some variations, the device or system may adjust
the vehicle speed automatically. The power management devices or
systems described herein may operate whether or not the driver has
entered a destination into the GPS, because the system may infer
the destination based on previous driving habits if the driver has
not explicitly provided a destination.
[0013] In some variations, the driver (or other user) provides the
system a destination and the vehicle determines the optimal speeds
to drive throughout the route. The system may use speed limits,
traffic conditions, physical calculations, and statistical models
from previous trips to the same destination to select the target
speeds to optimize around. Thus, in some variations, the driver
only needs to steer, although hard acceleration or braking by the
driver may override the system.
[0014] Described herein are devices for managing the power
consumption of an automotive vehicle comprising a power management
logic operable to calculate an applied power for the vehicle engine
from information about the external environment of the vehicle,
information about the operational status of the vehicle, one or
more command inputs, and one or more operational parameters of the
vehicle. The power management device may also include a processor
responsive to the power management logic (e.g., a microprocessor),
and a motor control mechanism, wherein the motor control mechanism
controls the application of power to the vehicle engine.
[0015] The power management logic may determine an applied power
for the vehicle engine based on information about the external
environment of the vehicle that is selected from the group
consisting of: the current location of the vehicle, the elevation
of the vehicle, upcoming elevations of the vehicle, the current
slope/grade of the route, the predicted slope/grade of the next
segments (or upcoming segments) of the route, speed limit
information of the current route segment, speed limit information
of upcoming route segments, the condition of the known or predicted
route (or a portion thereof), traffic information or data, traffic
surrounding the vehicle, the location of stoplights, the timing of
stoplights, a map of the roadway, the present angle of the sun, the
predicted angle of the sun for upcoming route segments, the weather
around the vehicle, present wind direction, the predicted wind
direction for upcoming route segments, present wind velocity, the
predicted wind velocity for upcoming route segments, current
temperature, the predicted temperature for upcoming route segments,
current air pressure, predicted air pressure for upcoming route
segments, time of day, date, day of week, visibility, present road
conditions, predicted road conditions for upcoming route segments,
and the distance to/from other vehicles. Any of this information
may be acquired by measuring (e.g., from sensors), or it may be
detected or input (e.g., from manual inputs, telemetry, detectors,
a memory, etc.), or it may be derived (e.g., based on other
information, including other environmental information).
[0016] The power management logic may determine an applied power
for the vehicle engine based on information about the operational
status of the vehicle. The operational status information input may
be selected from the group consisting of: the vehicle's current
speed, the motor speed, the vehicle's current orientation, the RPM
of the vehicle's motor, wheel rotations per minute, the battery
state, the voltage of the battery, the amp hours from the battery,
the state of the battery, temperature of battery, the age of the
battery, and the number of times the battery has charged and
discharged, the tire pressure, the drag force due to rolling
resistance of the vehicle, the weight of vehicle, the amount of air
going to the engine, the amount of gas going to engine, and the
weight of driver. Any of this information may be acquired by
measuring (e.g., by sensors), or it may be input (e.g., from an
external telemetry, a memory, etc.), or it may be derived (e.g.,
based on other information, including other operational status
information).
[0017] The power management logic may determine an applied power
for the vehicle engine based on command input information. Command
input information may be selected from the group consisting of: the
acceleration applied by a driver, the braking applied by a driver,
the intended destination, preferred speed, maximum and minimum
range over which speed should adjust, and preferred route. Any of
this information may be acquired by input (e.g., from an external
telemetry, keyboard, mouse, voice command, a memory, etc.), sensor
(e.g., optical detectors, etc.), or it may be derived (e.g., based
on other information, including other command information).
[0018] The power management logic may determine an applied power
for the vehicle engine based on information about one or more
operational parameters of the vehicle. Operational parameters may
be selected from the group consisting of: aerodynamic parameters
(CDA), rolling resistance parameters (Crr1 and Crr2), drive train
efficiency parameters, motor efficiency parameters, and battery
model parameters, battery charge and discharge relationships, type
of battery. Any of this information may be input (e.g., from an
external telemetry, a memory, etc.), or it may be derived (e.g.,
based on other information, including historical information or
other operational parameter information).
[0019] The power management device or system may further comprise a
memory containing vehicle information about one or more operational
parameters for the vehicle. The memory may store any of the
information about the external environment, operational status or
command inputs, including derived or historical information.
[0020] The devices and systems described herein may be used with
any appropriate vehicle, including internal combustion vehicles
(which run on gasoline, diesel, or ethanol for example), a hybrid
internal combustion/electric vehicles, electric vehicles powered by
the electric grid (plug-in), electric vehicles powered by the sun
(solar), and hydrogen fuel cell vehicles.
[0021] Also described herein are systems for managing the power
consumption of an automotive vehicle, comprising a first input,
operable to receive information about the external environment of
the vehicle, a second input, operable to receive information about
the operational status of the vehicle, a third input, operable to
receive one or more command inputs from a driver of the vehicle, a
memory containing information about one or more operational
parameters of the vehicle, power management logic operable to
calculate an applied power for the vehicle engine from the first
input, the second input, the third input, and the memory, and a
processor responsive to the power management logic. The system may
also include a motor control mechanism, wherein the motor control
mechanism regulates the application of power to the vehicle
engine.
[0022] Also described herein are methods of managing the power
consumption of a vehicle, including calculating an applied power
for the vehicle using a processor. The processor (e.g., a
microprocessor, etc.) receives a first input comprising information
about the environment of the vehicle, a second input comprising
information about the operational status of the vehicle, a third
input comprising a command input from the driver of the vehicle,
and a fourth input comprising vehicle information about the
operational parameters of the vehicle. The method may also include
the step of applying the applied power to the engine of the
vehicle, and/or to notifying the driver of the optimal speed.
[0023] The step of calculating an applied power may include
determining a route, segmenting the route into one or more segment
(or intermediate) destinations, calculating an energy efficient
speed for the vehicle to travel to the segment destination,
determining an optimized speed for the vehicle to travel to the
segment destination, and calculating the applied power from the
optimized speed for all of the segments. The applied power may be
calculated continuously. For example, the applied power may be
calculated at each point (e.g., every segment, or points within a
segment) as the vehicle is driven. Thus, over an entire route, the
most energy efficient speed at which to drive may be continuously
calculated. This may be done by determining a destination, and then
coming up with a route for that destination. If the destination is
not known (e.g., has not been provided to the power management
device or system), a predicted destination may be estimated, based
on statistical destination logic (e.g., using map coordinates, and
the historical operation of the vehicle). Energy efficient speeds
for current and upcoming route segments can then be calculated
based on the route. In some variations, the route is divided up
into segments. In some variations, the optimized speed for the
vehicle is determined based on historical speeds for similar
destinations. The route can be revised (e.g., continuously revised)
during operation.
BRIEF DESCRIPTION OF THE DRAWINGS
[0024] FIGS. 1A, 1B show an example of a vehicle controlled by a
traditional cruise control device and the same vehicle controlled
by one variation of this power management system described
herein.
[0025] FIG. 2 illustrates steps that may be used to optimize power
applied to a motor, as described herein.
[0026] FIG. 3A shows a schematic route as described herein.
[0027] FIG. 3B shows steps that may be followed to determine a
route destination.
[0028] FIGS. 4A, 4B show steps that may be followed to determine a
calculated optimized velocity for segments of a route.
[0029] FIG. 5 shows steps that may be followed for determining a
probable optimal speed based on historical route information.
[0030] FIG. 6 shows a schematic diagram of one variation of the
power management logic described herein.
[0031] FIG. 7 illustrates one variation of a vehicle including a
power management system, as described herein.
[0032] FIG. 8 illustrates a user interface for a power management
device.
[0033] FIG. 9 shows inputs that may be coordinated by the power
management user interface.
[0034] FIG. 10 shows a schematic diagram of a portion of a power
management system, as described herein.
[0035] FIG. 11 illustrates a power management system remotely
communicating with a server, as described herein.
[0036] FIGS. 12A, 12B show exemplary charge and discharge
characteristics for one type of battery.
[0037] FIGS. 13A, 13B show examples of engine characteristics.
DETAILED DESCRIPTION
[0038] The power supplied and used by a motorized vehicle can be
optimized based on information inputs including: user demands,
environmental conditions, the current or anticipated operational
state of the vehicle, and the operational parameters for the
vehicle. These parameters can be estimated, directly measured, or
derived, and may be used to determine the driving route, and
therefore an estimated power requirement for the route. The
estimated power requirement for a route and a historical power
requirement from the same vehicle traveling over the same route may
be used to determine the optimal power supplied to the vehicle. The
power required of a vehicle and the optimal power supplied to a
vehicle may also be expressed in terms of the speed or velocity of
the vehicle.
[0039] Management of a vehicle's power supply typically involves
optimization of the power supplied to the engine. As described
herein, the "engine" may refer to any portion of the vehicle to
which power is supplied, including the motor, powertrain, etc. As
will be apparent below, optimizing the power supplied to the engine
typically means minimizing the energy loss from the vehicle,
thereby increasing fuel efficiency. The power supplied to the
engine may alternatively be optimized based on other criterion. For
example, the power supplied to the engine may be optimized with
respect to speed or travel time. Furthermore, the devices, methods
and systems described herein may be used with any appropriate
vehicle, and are not limited to internal combustion vehicles. For
example, the devices, methods and systems described herein may be
used with vehicles having a hybrid internal combustion/electric
engine, an electric engine powered by the electric grid (e.g., a
plug-in vehicle), an electric engine powered by the sun (e.g., a
solar vehicle), and an electric engine powered by hydrogen fuel
cell. Thus the term "fuel" does not necessarily refer exclusively
to hydrocarbon fuels, but may refer to any appropriate power source
for the engine.
[0040] FIGS. 1A and 1B compare a traditional "cruise control"
device (in FIG. 1A) to one variation of the power management device
described herein (in FIG. 1B). In FIG. 1A, a typical cruise control
device regulates the speed of a vehicle as it drives from point A
to point B when the vehicle speed is set to 50 mph. As the vehicle
moves across different terrain (e.g., roads having different
elevations), or through different weather conditions, the
traditional cruise control device adjusts the power supplied to the
vehicles (and thus the speed) based only on the set velocity and
the actual velocity of the vehicle. Thus, the cruise control device
receives information on the current speed of the vehicle, and
adjusts the power supplied to the engine to maintain the vehicle at
the set speed. This type of device is a "velocity control" cruise
control device. In contrast, FIG. 1B shows a vehicle with a power
management device for optimizing the power supplied to the vehicle,
as described further herein.
[0041] In FIG. 1B, the power management system receives external
inputs, including information on the location and grade (e.g.,
steepness of any uphill/downhill portions) of the road, the
distances traveled. The power management system also includes or
deduces information about the route (e.g., from point A to point
B), and the acceptable range of speeds that the vehicle may travel
over this route (e.g., between 45 and 55 mph). The power management
system may also receive information about the state of the vehicle,
including the velocity at which it is traveling, and the weight of
the vehicle. Finally, the power management system may include
operational parameters such as the performance of the engine,
aerodynamic performance, and rolling resistance of the vehicle.
Given this information, the power management system may calculate
applied power to the engine, and may derive a speed (or set of
speeds) that optimizes the applied power. As shown in FIGS. 1A and
1B, the total energy used by the power management system in FIG. 1B
is 0.9 kwh compared to 1 kwh for the cruise control system shown in
FIG. 1A for identical vehicles traveling over the same pathway.
[0042] In general, there are many ways to optimize energy
efficiency, as described in more detail below. As will be
described, any of the methods, devices and system described herein
may be used together, individually, or in different
combinations.
[0043] Inputs
[0044] The power management devices and systems described herein
manage the power of the vehicle using inputs from four categories
of information input: information from the external environment of
the vehicle, information about the operational status of the
vehicle, information from one or more command inputs, and
operational parameters of the vehicle. Typically, at least one
input from each of these sources of information is used to
determine an optimal speed (or applied power) for the vehicle. Some
of the information inputs for each of these categories are
described below. In every case, the information may be directly
measured (e.g., by sensors or other inputs), communicated from an
external source, or it may be derived from other information
inputs, or from stored data.
[0045] Information from the external environment of the vehicle may
be used to determine the optimal power to apply to the vehicle.
External environment information generally includes any information
about the environment surrounding or acting on the vehicle.
External information may be used to determine forces acting on the
vehicle (e.g., drag, wind resistance, tire resistance, etc.), the
location of the vehicle relative to the destination (e.g.,
position, direction, etc.), and the environment surrounding the
vehicle (e.g., traffic patterns, surrounding traffic, etc.). In
some variations, the external information may be used to help
describe the power available to the vehicle, particularly in solar
powered vehicles (e.g., amount of light energy, time of day,
position of the sun, etc.).
[0046] Examples of environmental information inputs include, but
are not limited to: the current location of the vehicle,
geographical information about the surrounding area, the elevation
of the vehicle, upcoming elevations of the vehicle, the current
slope/grade of road, the predicted slope/grade of the next segments
of road, traffic surrounding the vehicle, the location of
stoplights, the timing of stoplights, a map of the roadway, the
present angle of the sun, the predicted angle of the sun for
upcoming route segments, the weather around the vehicle, present
wind direction, the predicted wind direction for upcoming route
segments, present wind velocity, the predicted wind velocity for
upcoming route segments, current temperature, the predicted
temperature for upcoming route segments, current air pressure,
predicted air pressure for upcoming route segments, time of day,
date, day of week, visibility, present road conditions, predicted
road conditions for upcoming route segments, and the distance from
other vehicles.
[0047] Some of the information inputs may be redundant, or may be
derived from related information. For example, the vehicle location
may be provided by a GPS device which may be either a separate
device or a portion of the power management device that receives a
GPS signal and locates the vehicle based on the received signal.
Geographical and topographical information about the area
surrounding the vehicle may be determined from the location
information. For example, the location may be used to index an
atlas of the surrounding area. Some variations of the power
management device include a memory or database of information,
including information about maps and road information. In some
variations, the power management device communicates with one or
more such databases to identify the location and surrounding road
features (e.g., suggested speed limits, stop signs, traffic
patterns, etc.).
[0048] The power management device may include or may be connected
to sensors or other inputs to directly determine some of the
information inputs. For example, the power management device may
include a pre-set clock (e.g., for the current time and date), one
or more optical sensors (e.g., to determine the intensity of
sunlight, visibility, distance from nearby vehicles, etc.), and/or
weather sensors (e.g., temperature, wind direction and velocity,
air pressure, etc.). In some variations, the power management
system receives some of this information by telemetry with
off-board information sources such as databases and the like. For
example, the power management system may communicate with a weather
service, a map service, a traffic service, etc.
[0049] These examples of information about the external environment
are only intended to illustrate the kinds of external information
that may be used by the power management devices and systems
described herein and are not intended to be limiting. Any
appropriate information about the external environment may be
provided to the power management device or used by the power
management device.
[0050] Information about the operational status of the vehicle may
be used to determine the optimal power to apply to the vehicle.
Operational status information generally includes any information
about the current operational status of the vehicle itself.
Operational status information may be used to determine the current
condition of the vehicle's engine and component parts (e.g., motor,
powertrain, battery, tires, etc.), the current fuel supply, the
manner in which the vehicle is traveling (e.g., velocity,
acceleration, etc.), and the like.
[0051] Examples of environmental information inputs include, but
are not limited to: the vehicle's current speed, the motor speed,
the vehicle's current orientation, the RPM of the vehicle's motor,
wheel rotations per minute, the battery state, the voltage of the
battery, the amp hours from the battery, the state of the battery,
temperature of battery, the age of the battery, and the number of
times the battery has charged and discharged, the tire pressure,
the drag force due to rolling resistance of the vehicle, the weight
of vehicle, the amount of air going to the engine, the amount of
gas going to engine, and the weight of driver.
[0052] As described above, some of the information inputs may be
redundant, or may be derived from related information. Furthermore,
the power management system may use any of the sensors, gauges and
detectors already present in the vehicle as information inputs. For
example, the velocity of the vehicle may be detected by a
speedometer which may pass information on to the power management
system. The power management device may also include additional
sensors, inputs or detectors to determine or derive any information
about the operational status of the vehicle. For example, the power
management device or system may include one or more weight sensors
(to determine the load in the vehicle, including the driver's
weight).
[0053] The examples of operational status information inputs are
only intended to illustrate the kinds of operational status
information that may be used by the power management devices and
systems described herein. Any appropriate information about the
operational state of the vehicle may be provided to the power
management device or used by the power management device.
[0054] Information from one or more command inputs may be used to
determine the optimal power to apply to the vehicle. Command inputs
generally include any instructions from the driver of the vehicle
about the operation (or intended operation) of the vehicle. Command
inputs may be directly input by the user, or they may be derived by
the actions of the driver or the identity of the driver. Examples
of command inputs include, but are not limited to: the acceleration
applied by a driver, the braking applied by a driver, the vehicle's
known or predicted final destination, the vehicle's known or
predicted interim destination, preferred speed, maximum and minimum
range over which speed should be adjusted, and preferred route.
[0055] As with all of the information inputs, some of the command
inputs may be redundant, or may be derived from related
information. For example, a route destination may be input by the
driver, or it may be inferred from the driving behavior and/or
identity of the driver. The identity of the driver may also be
input by the driver, or it may be inferred. For example, the
identity of the driver may be matched to the weight of the driver.
Command inputs may include any of the drivers actions to control
the vehicle. For example, command inputs may include steering,
breaking, shifting, or application of the accelerator. The power
management device may include sensors, inputs or detectors to
monitor the manipulations of the driver. In some variations, the
driver may directly input commands to the power management system
or to other devices in the vehicle that communicate these command
to the power management system. For example, the driver may use an
on-board navigational system to select a destination, and this
destination may be communicated to the power management system. In
some variations, the user may provide commands directly to the
power management system. In some variations, the command inputs may
be derived from other information, including the environmental
information and the operational status information. For example,
the destination (either a final or an intermediate destination) may
be estimated based on the current location of the vehicle, the
direction that the vehicle is traveling, the time of day and/or the
driver of the vehicle (e.g., if it's 8:00 am, and driver X is
driving the car on interstate 280, then the final destination is
most likely to the address of X's work place).
[0056] Information inputs, including command inputs, may have
default or pre-set values. For example, the power management device
or system may have a preset or default maximum and minimum range of
speeds for traveling part of the route (e.g., if the maximum and
minimum range has not been explicitly input, the maximum and
minimum range may be set to +/-4 mph). In some variations, the
information inputs may include metadata describing one or more
features of an information input. Metadata may include information
about the information input. For example, metadata may indicate the
last time a particular data input was updated, or may indicate that
the data is a default setting, or the like.
[0057] These examples of command inputs are only intended to
illustrate the kinds of command inputs that may be used by the
power management devices and systems described herein. Any
appropriate command input may be provided to the power management
device or used by the power management device.
[0058] Information from one or more operational parameters of the
vehicle may be used to determine the optimal power to apply to the
vehicle. Operational parameters generally include information about
characteristics that are specific to the vehicle (e.g.,
characteristics of component parts of the vehicle, including the
battery, the engine, the powertrain, the tires, etc.). Operational
parameters of the vehicle may be stored and retrieved from a memory
that is part of the power management device or system, or they may
be retrieved from a remote information source.
[0059] Examples of operational parameters include, but are not
limited to: aerodynamic parameters (CDA), rolling resistance
parameters (Crr1 and Crr2), drive train efficiency parameters,
motor efficiency parameters, and battery model parameters, battery
charge and discharge relationships, type of battery.
[0060] The operational parameters may be fixed (e.g., may not vary
with operation of the vehicle), or they may be changed. In some
variations, the operational parameters may comprise a database
(e.g., a lookup table), so that the value of the operational
parameter may depend upon another information input, and may be
retrieved from the database by using one or more information inputs
as a search key. In some variations, the operational parameter may
comprise an equation or relationship that has other information
inputs as variables.
[0061] Examples of operational parameters are provided below. In
general, operational parameters may be determined experimentally
(e.g., by testing) or may be provided by product manufacturers. In
some variations, general (or generic) operation parameters may be
used if more specific parameters are not available. For example,
battery charge and discharge graphs (showing operational
characteristics of the battery) can be obtained from battery
manufacturers. Operational parameters for various types of
batteries (e.g., Lithium polymer batteries, etc.) can include
material characteristics, energy densities, power densities,
thermal characteristics, cycle life, charge and discharge
characteristics (e.g., voltage over time), and current flux over
time. For example, FIGS. 12A and 12B show exemplary charge and
discharge characteristics for one type of Lithium polymer battery
(e.g., the Li--Po 40 Ah from Leclanche SA, Switzerland). Complete
characterization may also be made by taking charge and discharge
measurements from either a specific battery, or a specific model
and make of a battery.
[0062] Motor efficiency data may be obtainable from the
manufacturer. A full model dynamometer testing may also be used to
determine motor characteristics. For example, FIGS. 13A and 13B
show some examples of motor characteristics that may be provided.
Aerodynamic parameters of the vehicle (e.g., the outer chassis) can
also be provided by the auto manufacturer, or could be measured
(e.g., in a wind tunnel). Aerodynamic properties may also be
estimated or calculated for different vehicles (or vehicle shapes,
makes, or models) using literature values. Examples of aerodynamic
parameters may be found, for example in "GM Sunraycer Case
History/M-101" (Published by the Society for Automotive Engineers,
Inc, Dec. 1, 1990), The Leading Edge: Aerodynamic Design of
Ultra-Streamlined Land Vehicles (Engineering and Performance) by
Goro Tamai (Robert Bentley, Inc, 1999), and The Winning Solar Car:
A Design Guide for Solar Race Car Teams by Douglas R. Carroll (SAE
International, 2003), each of which is herein incorporated by
reference in its entirety. Examples of drag coefficients are also
readily available (e.g., online:
http://www.answers.com/topic/drag-coefficient-1, last visited Oct.
12, 2005).
[0063] Rolling resistance parameters may also be provided by the
tire manufacturer, or may be measured. An example of one variation
of a published rolling resistance formula may be found in
"Fahrwerktechnik: Reifen and Raeder" by Jornsen Reimpell and Peter
Sponagel (published by Vogel-Fachbuch Technik, ISBN 3-8023-0737-2,
1988), herein incorporated by reference in its entirety. Similarly,
a drivetrain efficiency model may be provided by the vehicle
manufacturer, or may be measured from the power input vs. the power
output for the entire drivetrain. In some variations, (e.g., some
variations of solar cars, for example) do not have a drivetrain,
since the motor is built directly into the wheel.
[0064] Examples of operational parameters are only intended to
illustrate the kinds of operational parameters of the vehicle that
may be used by the power management devices and systems described
herein. Any appropriate operational parameter may be provided to
the power management device or used by the power management
device.
[0065] The information inputs described herein may be used to
determine the optimally efficient energy to supply to the
engine.
[0066] Optimization of Engine Efficiency
[0067] FIG. 2 illustrates some of the steps that may be followed to
optimize the energy supplied to an engine so that the vehicle
travels at a fuel-efficient speed. To determine an optimally
efficient speed (or the optimal power to be supplied to the
engine), a route is determined 201 from the starting position and
an actual or estimated ending position, the route is segmented 203
into one or more segments, a model optimal speed (or power) is
calculated 205, statistical data from previous trips along the same
segment of the route are retrieved 207, and an overall efficiency
applied power is calculated from at least the model power and the
statistical data 209. Finally, the overall efficient applied power
is provided to the engine. In some variations, the vehicle operator
may be notified of the overall efficient applied power instead of
(or in addition to) automatically applying this optimal power. Each
of these steps is described more fully below. The statistical data
from previous trips may be an optional element. For instance, one
may choose not the use statistical data or one may not have
statistical data.
[0068] 1. Determine Route
[0069] The route is determined based on the current position of the
vehicle and a final destination position. The destination position
may be explicitly provided by the operator of the vehicle (e.g., as
an operator input), or it may be derived. In some variations, the
operator may provide a destination directly to the power management
device, or to a device that communicates with the power management
system (e.g., an on-board navigation system, etc.). The operator
may also select the preferred route to the final destination either
before beginning the trip, or after beginning the trip. For
example, the operator may choose a destination using a navigation
system including navigation systems that are not part of the power
management device (such as any commercially available GPS
navigation systems), which may also generate a route. The GPS
navigation system may communicate the destination and route
information to the power management device. In some variations, the
power management system includes a GPS component or module, and may
at least partly act as a navigation system.
[0070] The destination may be derived from information about the
operator, the current location, the time of day, or the like. The
power management device may include statistical destination logic
that determines one (or more) most likely destinations based on
information provided from environmental inputs, user command
inputs, and vehicle operational status inputs. In some variations,
the destination is derived by generating a series of statistically
weighted (e.g., likely) destinations based on any, all, or some of
these inputs. Examples of some of the inputs that may be used by
the statistical destination logic to determine a likely destination
may include, but are not limited to: the weight of the driver, the
time of the day, the current location of the vehicle, the direction
that the vehicle is facing (or traveling in), the day of the week,
and the speed of the vehicle.
[0071] The statistical destination logic may identify one or more
destinations based on information held in a memory. For example,
the statistical destination logic may use any of the information
inputs to select among a record of destinations to which the
vehicle has previously driven. These destinations may be assigned a
probability weighting based on the information inputs. For example,
the statistical destination logic may continuously infer the
vehicle's destination. The information inputs can be used to assign
a probability to a particular destination. It is important to note
that the word "destination" in this context is not necessarily the
driver's final destination. It may be an intermediate destination
along the route that the statistical destination logic determines
has a greater chance than some threshold likelihood (e.g., X %) of
being the destination. A threshold likelihood may be preset, and
may be varied by the user or by the power management device.
[0072] For instance, if a driver leaves her house to go to work,
and drives toward the highway, the statistical destination logic
may determine that there is a 95% chance that she is going to the
highway but only a 75% chance that she is going to go South on the
highway. So, if the threshold (X) is 90%, the "destination" in this
case would be the highway onramp. Once she gets on the highway
going south, the probability that she is going to work may have
increased to 92%. Now, the "destination" would be her work. Thus,
as the vehicle drives around, the probable destination determined
by the statistical destination logic may constantly change to
revise the destination or intermediate destination.
[0073] In some variations, the statistical destination logic
accesses (and may also write to) a memory comprising past
destinations that are correlated to some or all of the information
inputs (such as location, driver weight, time of day, day of week,
direction, velocity, etc.), and/or information derived from these
inputs (e.g., driver identity, driving habits, etc.). The list of
possible locations may be weighted by the statistical destination
logic based on how closely the information inputs correspond to the
associated information inputs for these destinations, and may be
influenced or refined by the number of times that the driver has
driven to this destination. Some of the information inputs (or some
combination of the information inputs) may be weighted more heavily
than others in determining the likelihood of a destination.
Furthermore, the statistical destination logic may select more than
one likely destination, including selecting a final destination and
one or more intermediate destinations.
[0074] One variation of a procedure for determining the most likely
destination is described below, and illustrated in FIG. 3B. For
example, the schematic route shown in FIG. 3A has 10 junctions (A
to J). The probably that a driver will take any particular route
from the start position may be described as "P". Thus, Pold is the
previous (or old) percentage likelihood of taking a route, whereas
P is the newly calculated percentage likelihood. Pold is initially
set to 1 because there is a 100% likelihood that your route will go
through the place that you are currently at. As used in this
example, an intersection is as a junction having more than one
choice of direction that you may go in. Examples include highway
exits (e.g., you can stay on the highway or take the exit), a
four-way stop, and a fork in the road.
[0075] Referring now to FIG. 3A, assume that you have taken the
following trips: [0076] 1. start.fwdarw.A.fwdarw.C.fwdarw.E [0077]
2. start.fwdarw.A.fwdarw.C.fwdarw.D.fwdarw.F [0078] 3.
start.fwdarw.A.fwdarw.G.fwdarw.I [0079] 4.
start.fwdarw.A.fwdarw.G.fwdarw.I [0080] 5. start.fwdarw.A.fwdarw.C
[0081] 6. start.fwdarw.A.fwdarw.C.fwdarw.E [0082] 7.
start.fwdarw.A.fwdarw.C.fwdarw.E [0083] 8.
start.fwdarw.A.fwdarw.G.fwdarw.J.fwdarw.C.fwdarw.E [0084] 9.
start.fwdarw.A.fwdarw.C.fwdarw.E [0085] 10.
start.fwdarw.A.fwdarw.C.fwdarw.D.fwdarw.F
[0086] Based on this trip history, the probably of your taking
moving from any junction in the route shown in FIG. 3A can be
determined based on this trip history. These probabilities are
tabulated in the table:
TABLE-US-00001 Probably of continuing in Probably of going through
each Position the possible directions location based on past
behavior start 10/10 A A 7/10 C A: 10/10 = 100% 3/10 G 0/10 B B 0/0
B: 0/0 = 0% C 2/8 D C: (10/10)*(7/10) + 5/8 E
(10/10)*(3/10)*(1/3)*(1/1) = 71% 1/8 end D 2/2 F D: (.71)*(2/8) =
17.75% E 5/5 end E: (.71)*(5/8) = 44.375% F 2/2 end F:
(.1775)*(2/2) = 17.75% G 2/3 I G: (10/10)*(3/10) = 30% 1/3 J H 0/0
H: 0/0 = 0% I 2/2 end I: (.30)*(2/3) = 20% J 1/1 C J: (.30)*(1/3) =
10%
[0087] The Table also shows the probably of going through each
location based on my previous driving behavior in the next trip.
For a new trip, at each junction, the probabilities may be
recalculated. For example (on the same trip), once you have reached
point A and decided to turn toward C, the new probabilities are
recalculated as: A: 0%, B: 0%, C: 100%, D: 25%, E: 62.5%, F: 25%,
G: 0%, H: 0%, I: 0%, J: 0%. In real world examples, it could take
hundreds of drives before the statistics become useful at
predicting where the driver is likely to go. FIG. 3B illustrates
one variation of a statistical destination logic that may be
used.
[0088] 2. Segment Route
[0089] The route used by the power management device typically
includes a starting position (e.g., the current position of the
vehicle, which may be indicated by GPS), an ending position, as
described above, and any intermediate positions between the initial
and the final positions. In some variations, the route may be
broken up into segments that may be used by a power management
device to optimize the power needed to travel this segment. A
segment may comprise any distance to be traveled, including the
entire route, or small portions of the route. Different segments in
the same route may be of different lengths.
[0090] The route may be segmented in any appropriate manner. For
example, the route may be broken into segments based on
predetermined or anticipated changes in speed (e.g., switching from
65 to 55 mph), changing traffic patterns (e.g., turns, stops,
yields, etc.), traffic or anticipated traffic, distance (e.g., x
miles), terrain (e.g., the gradient or condition of a road), or the
like. In some variations, the route may be segmented based on a
combination of such factors.
[0091] A route may be entirely segmented, or only partially
segmented. For example, the power management device may segment
only the first part of the route (e.g., the portion containing the
current position of the vehicle), or the first few segments. This
may be particularly useful when the destination is an anticipated
destination determined by the statistical destination logic, for
example. The route may be continuously re-segmented. For example,
as the vehicle moves, the power management device may become aware
of changing road conditions (e.g., traffic, weather, etc.), or the
user may change the route, necessitating re-segmenting. As used
herein, "continuously" may mean repeated multiple times, including
repeating regularly or periodically.
[0092] In some variations, the entire route (or the entire
predicted route) may be divided up into N segments. The number (N)
of segments may be fixed or may depend upon the route. The more
segments that the route is split into, the more accurate the model
may be. However, more segments may also require more computing
power. Thus, the number of segments N may be decided based on the
tradeoff between computing power and accuracy.
[0093] 3. Calculated Energy for the Route
[0094] The power required by the vehicle to travel along a route,
or a segment of the route, may be estimated or calculated, and this
calculation may be used to determine a calculated speed for the
vehicle so that the power usage is optimized or minimized. Such
calculations of power requirements at different speeds typically
use information inputs from the vehicle, the user, and the
environment over the route from the initial position to a
destination (e.g., a final destination or an intermediate
destination). Any appropriate information input may be used.
[0095] Simulation of the power requirement of the vehicle may
estimate power requirements at different speeds. Thus, the speed(s)
that the vehicle travels the route (or a segment of the route) can
be optimized. For example, the simulation could determine the most
energy efficient speed for the vehicle to travel over one or more
segments by minimizing the power requirement for the vehicle while
allowing the speed to vary within the range of acceptable
speeds.
[0096] In some variations, the power management device includes
simulated energy requirement logic that determines the power
requirement given the information inputs (e.g., information from
the external environment of the vehicle, the operational status of
the vehicle, information from one or more command inputs, and
operational parameters of the vehicle). The simulated energy
requirement logic can calculate the required applied power for the
vehicle by calculating different power requirements for all or a
portion of the route (e.g., the first segment) when the speed of
the vehicle is within the range of speeds acceptable for traveling
this section of the route. For example, if the target speed for a
portion of the route is 60 mph with a range of +/-5 mph, the
simulated energy requirement logic may determine the speed at which
the energy requirement is lowest that is closest to the desired
speed (60 mph). Any appropriate method of calculating and/or
optimizing this velocity may be used, including iteratively
simulating different speeds within the target range.
[0097] The optimal speed may be calculated by energy calculation
logic. A simplified example is provided below, using the following
parameters, assuming an electric car with regenerative brakes.
TABLE-US-00002 mass of the vehicle and the driver (m) 4000 kg CdA
of the car .25 The rolling resistance .01 coefficients: .05 Crr1
Crr2 Drivetrain efficiency (eff) 80% air density (rho) 1.3 kg/m3
acceleration due to gravity (g) 9.8 m/s2 number of wheels (n) 4
headwind velocity (vhw) 10 kph or 2.78 m/s
[0098] In this example, the route may be split into five segments
of 5 km each with the following altitudes measured at the end of
each segment: 0 (beginning of segment 1), 200 m (end of 1), 100 m
(end of 2), 400 m (end of 3), 100 m (end of 4), 0 (end of 5). We
may also make the simplifying assumption that the road grade is
constant between measured points, and the road grades are
calculated to be: +0.04 (seg 1), -0.02 (seg 2), +0.06 (seg 3),
-0.06 (seg 4), -0.02 (seg 5). The target average speed is 100
kph.
[0099] For the sake of simplicity in this example, we can then
calculate the amount of energy required to drive at a constant 100
kph speed for the entire route, as well as for 16 other
combinations of the speeds 95 kph (26.39 mps), 100 kph (27.78 mps),
and 105 kph (29.17 mps). In practice, this simulation may be run
for hundreds or even thousands of combinations of speeds which may
be tested to find the optimal speed to drive each segment. It is
assumed that we enter the first segment traveling 100 kph (27.78
mps). It is also assumed that the speed listed for the segment is
the final speed of the segment and the vehicle accelerates linearly
throughout the segment.
[0100] The Table below shows the results of the energy calculation
for all of the combinations tried. The lowest energy usage is
4275.94 Watt-hours. This was obtained by going 95 kph (seg1), 105
kph (seg2), 95 kph (seg3), 105 kph (seg4), 100 kph (seg5). The
average speed over all 5 segments is still 100 kph, but the energy
used is 10.2% less.
TABLE-US-00003 seg seg seg seg seg iterations 1 2 3 4 5 Energy
units 1 27.78 27.78 27.78 27.78 27.78 4763.2484 Whr 2 26.39 29.17
27.78 27.78 27.78 4536.889 Whr 3 26.39 29.17 26.39 29.17 27.78
4275.938 Whr 4 26.39 29.17 26.39 27.78 29.17 4382.5026 Whr 5 26.39
29.17 27.78 26.39 29.17 4950.1438 Whr 6 26.39 29.17 27.78 29.17
26.39 4438.3467 Whr 7 26.39 26.39 29.17 29.17 27.78 4942.6325 Whr 8
26.39 26.39 29.17 27.78 29.17 5055.9124 Whr 9 26.39 26.39 27.78
29.17 29.17 4784.1865 Whr 10 29.17 26.39 27.78 27.78 27.78
5013.2565 Whr 11 29.17 26.39 26.39 29.17 27.78 4745.585 Whr 12
29.17 26.39 26.39 27.78 29.17 4852.1495 Whr 13 29.17 26.39 27.78
26.39 29.17 5137.6625 Whr 14 29.17 26.39 27.78 29.17 26.39
4914.7142 Whr 15 29.17 29.17 26.39 26.39 27.78 4602.8845 Whr 16
29.17 29.17 26.39 27.78 26.39 4493.3028 Whr 17 29.17 29.17 27.78
26.39 26.39 4765.4617 Whr
[0101] In general, any appropriate relationship between the
information inputs, the speed (e.g., the applied power) and the
required energy may be used to determine an optimized speed. In
some variations, the energy requirement may be calculated from
aerodynamic information, rolling resistance, potential energy
change due to road gradient and acceleration. FIGS. 4A, B show one
method of determining the target speeds for a route by an iterative
method. One variation of a method for determining target speeds is
described by the equation:
E = V tarn eff .times. ( CdA .times. .rho. 2 .times. ( V tarn + V
hw ) 2 + ( mgC rr .times. .times. 1 + nV tarn .times. C rr .times.
.times. 2 ) .times. cos .function. ( tan - 1 .function. ( G ) ) +
mg .times. .times. sin .function. ( tan - 1 .function. ( G ) ) + ma
) ##EQU00001##
where E is the total energy used over the segment. The terms of the
equation include:
V tarn eff ##EQU00002##
where V.sub.tarnt=target velocity over time, and eff is the
efficiency of the powertrain.
[0102] The terms inside of the parenthesis calculates the total
drag force on the vehicle. However, we want to calculate the total
amount of energy. In general, Power=Force*Velocity, and
Energy=Power*time=Force*Velocity*Time. The total amount of energy
used is increased based on the power lost due to the inefficient
powertrain.
[0103] The drag force due to the aerodynamics of the car is
expressed as:
CdA .times. .rho. 2 .times. ( V tarn + V hw ) 2 ##EQU00003##
where CdA is the coefficient of drag time area (which can be a
measured value), and rho (.rho.) is the density of air, V.sub.tarn
is the target velocity in the nth iteration, and V.sub.hw is the
headwind velocity. The drag force due to the rolling resistance of
the tires is expressed as:
mgC.sub.rr1+nV.sub.tarnC.sub.rr2)cos(tan.sup.-1(G))
where m is the mass of the car, g is the acceleration due to
gravity, n is the number of wheels, Vtarn is the target velocity in
the nth iteration, C.sub.rr1 and C.sub.rr2 are the coefficients of
rolling resistance, and G is the grade of the road. The
coefficients of rolling resistance may be measured values or they
may be values supplied by tire manufacturer (e.g., tire
manufacturer). The numbers may vary for different road surfaces as
well.
[0104] The force due to the road gradient is:
mg sin(tan.sup.-1(G))
where m is the mass of the car, g is the gravitational constant,
and G is the grade of the road. The force due to the acceleration
of the car is ma (the mass of the car times the acceleration over
the segment, assuming linear acceleration for the segment).
[0105] Putting everything together, the equation can be solved for
E, the total energy used over the segment. Similar equations are
described for calculating the total energy used over a segment in
"The Speed of Light, The 1996 World Solar Challenge" by Roche,
Schinckel, Storey, Humphris, and Guelden (UNSW, 1997), herein
incorporated by reference in its entirety.
[0106] FIGS. 4A, B describe a method of calculating an array of
optimized velocities for an entire route that has been broken up
into segments. In some variations, only one or a subset of
optimized speeds are calculated.
[0107] Variations on the above equations may be made to simplify
the relationships or to include additional factors. For example,
the speed varying part of the rolling resistance equation may be
removed to simplify the equation to: mgC.sub.rr
cos(tan.sup.-1(G)).
[0108] Additional factors could be added as well, for example, by
including the variation of the motortrain efficiency with speed, or
by including the variations of the CdA depending on the
directionality of the wind.
[0109] 4. Historical Route Information
[0110] The power management device may refer to a record of
historical route information. For example, the power management
device may include a memory or a data structure that holds
information on routes or segments or routes that the vehicle has
previously traveled. The memory may comprise a database, a
register, or the like. In some variations, a power management
system communicates with a memory or other data structure that is
located remotely. The record of historical route information may
include the route information (e.g., starting location and any
intermediate locations), as well as information about the actual or
optimized velocities and/or applied power for the vehicle traveling
the route. The record of historical route information may also
include any informational from information inputs (described
below). For example, the record of historical route information may
include information about the time of day, weather conditions, road
conditions, driver, etc. Multiple records for the same route (or
segments of a route) may be included as part of the record of
historical route information.
[0111] The record of historical route information may provide
statistical information on driving habits. The driving habits of an
operator over a particular route or segment of a route may be
determined by analyzing the previous times that the driver has
taken this route, and by looking at the efficiency (e.g., the power
efficiency) for each previous trip, and for the combination of
previous trips. Thus, the historical route information may be
analyzed by statistical route analysis logic that can determine a
probable optimal speed at each point along a route (e.g., at
segments along the route). The more times that a driver has driven
the route, the more data can be used to estimate a probable optimal
speed for all or part of the route.
[0112] Historical data may be particularly useful when there is a
large amount of such data available. Instead of trying to calculate
the predicted power usage based on physics modeling, this method
merely looks at all of the previous data to determine the power
that would be utilized to drive each segment at a particular speed.
For example, in the past, a driver may have driven a particular
segment 1000 times. Out of those thousand times, she may have
driven it at speeds ranging from 80 kph to 120 kph. For each of
those 1000 times that she drove the segment, the car recorded how
fast she drove it, and how much energy was used. Therefore, to
estimate how much energy would be required to drive the segment at
95 kph, the power may be estimated by taking an average of all of
the previous times the driver drove that segment at 95 kph to
arrive at an estimated energy usage, rather than calculating the
power from the physics calculations, as described above. In one
variation, only the previous trips along the segment made under
approximately similar conditions are considered (e.g., similar
cargo weight, headwinds, etc.).
[0113] FIG. 5 describes one method of using historical data to
determine a Probable Optimal Speed. This speed most likely
approximates the optimal speed, based on previous trips. In
general, this method is most accurate when there are many similar
previous trips to be in the database. FIG. 5 shows that, the
location of the vehicle is periodically determined (e.g., via GPS,
manual entry, etc.), and this location can then be used to
determine a historical segment corresponding to the current
location. As described above, every route may be divided into a
finite number of segments, and the more segments that the route is
split into, the more accurate the algorithms may be. However,
additional segments also increase the computing power needed. The
destination is also determined periodically 505 (e.g. as the
vehicle is moving), and is reevaluated based on the current
location. It can then be determined if the vehicle is in the same
segment as previously determined or if it has entered a new segment
507 since reevaluating the vehicle location. If the answer is
"yes," then nothing needs to be done until the next time the
location is measured. If the answer is "no," then the database is
examined to find the historical information about this segment. For
example, the historical information is queried to determine what
speed the vehicle was traveling every time that the vehicle (or the
specific driver of the vehicle) was in the same segment going to
the predicted destination. In particular, the historical
information is queried to determine how fast the vehicle was
traveling during the trip in which the vehicle used the least
amount of energy over the same route. The result of this query
gives a speed that is most likely the best (e.g., most efficient)
speed to travel for the current trip. The process can iteratively
repeat for the next location measurement as the vehicle
continues.
[0114] FIG. 5 describes a method of determining a probable optimal
speed using historical route information. In FIG. 5, the probable
optimal speed is identified from the historical route information
as the most efficient speed (e.g., the speed having the lowest
energy requirement) used by the vehicle when traversing the
segment, when that segment is part of a route having the same
destination as the current destination. The flowchart shown in FIG.
5 illustrates a continuous process, in which the power management
device can determine a probable optimal speed as the current
segment changes (e.g., as the vehicle moves).
[0115] In some variations, probable optimal speeds may be
identified for the entire route. For example, the predicted or
actual route may be segmented, and an array of probable optimal
speeds may be identified from the historical route information for
each segment. In some variations, the probable optimal speed is not
a single most efficient speed for a segment of a route, but is
derived from a combination (e.g., an average, median, weighted
average, etc.) of all or a subset of the historical route
information speeds. In some variation, only a subset of the
historical route information is used. For example the probable
optimal speed may be driver specific, so that only information for
a specific driver is used to calculate a probable optimal speed.
Drivers may be identified by bodyweight, or some other information
input, including self-identification. If there is no historical
route information for the segment or route being examined, then the
probable optimal speed may be set to a predetermined value (e.g.,
zero), or some other indicator may be toggled so that the probable
optimal speed is not relied upon.
[0116] In one variation, a reliability estimate may be assigned to
the probable optimal speed. For example, a reliability estimate may
be related to the number of data points (e.g., the number of times
that the vehicle (or a driver driving the vehicle) has driven that
segment or route. For example, if there are no records of the
vehicle driving the route, the reliability estimate may be set very
low. Generally, the more records for a route in the historical
route information, or the more closely the identifying information
in the record matches the information about the current route
(e.g., the driver, weather conditions, traffic, etc.), the higher
the setting of the reliability estimate.
[0117] 5. Calculation of an Efficient Speed Output
[0118] Finally, an efficient speed for the vehicle to travel the
route (or a part of the route) may be determined from the
calculated optimized speed and the probable optimal speed. The
optimum speed is the most efficient speed (E), as described above.
This efficient speed (or efficient speed output of the power
management system) may also be expressed as the applied power that
is provided to the engine to achieve the speed at which the fuel
efficiency is optimal. Thus, an efficient speed is typically a
function of the driver's current operational demands, the current
operational conditions of the vehicle, the operational parameters
for the vehicle, and any historical behavior of the vehicle taking
the same (or a similar) route.
[0119] In general, an efficient speed output is determined by a
combination of the calculated optimized speed and the probable
optimized speed after they have been appropriately weighted. In
some variations, this weighting takes into account the total energy
predicted by the calculated optimized speed (e.g., by the simulated
energy requirement logic) and the total energy required for the
route predicted by the probable optimized speed (e.g., by the
statistical route analysis logic). The reliability estimate for the
probable optimized speed may also contribute to the weighting. The
power management device may include derived efficient speed logic
that can determine efficient speeds for the vehicle to travel the
route, or a portion of the route. In some variations, the efficient
speeds are expressed as power or energy to be applied to the
vehicle engine (e.g., the applied power).
[0120] As previously mentioned, the methods and logic described
above may be used to calculate a speed or an applied power for
running the vehicle at an optimal fuel efficiency. As will be
apparent to one of skill in the art, the same procedures may be
used to determine a speed (or speeds) over the route that minimize
or maximize other factors, and are not limited to optimizing only
fuel efficiency. For example, the power management device may
control the speed of the vehicle so as to minimize the duration of
the trip instead of (or in addition to) fuel efficiency. Thus, the
simulated energy requirement logic may be expressed as a simulated
time requirement, and may calculate the time required to travel a
segment of the route as a function of the speed or energy, and
additional information input. In this case, calculated optimized
speeds may be determined by minimizing the duration of the trip
over each segment. Furthermore, the probable optimal speed may be
determined from the historical route information based on the
duration of travel, rather than the power applied, for each
segment.
[0121] Control Logic
[0122] The power management device may include control logic for
controlling the operation of the power management device. Control
logic may include logic for acquiring information inputs,
communicating with different components of the power management
system, estimating the destination of the vehicle from information
inputs, segmenting the route into segments, simulating the energy
requirements of the engine from information inputs, and controlling
the entire power management device or system.
[0123] For example, the power management device or system may
include polling logic for acquiring information inputs and may also
coordinate writing of information from the power management device
to a memory. In some variations, the polling logic polls sources of
information data that are provided to the power management device.
For example, the polling logic may poll data from sensors, inputs,
memories, or any other source of information data. The polling
logic may further coordinate storing of this data in a memory, such
as a memory register or a memory device or database that may be
accessed by the power management device or system. In some
variations, the polling logic causes old data (e.g., greater than x
weeks old) to be overwritten. The polling logic may also control
how often the various information data sources are polled. For
example, the polling logic may continuously poll data from external
environmental sensors (e.g., detecting location, direction,
elevation, traffic, weather, etc.) and operational status detectors
(e.g., detecting vehicle speed, well velocity, motor speed, etc.).
The polling logic may also coordinate writing of route information.
For example, the polling logic may coordinate recording the
decisions made at intersections, and information about routes
traveled by the vehicle, and the like. In some variations, the
polling logic also coordinates the writing of information derived
from the information inputs to a memory. For example, the polling
logic may coordinate recording the optimal speed or energy used to
traverse a segment or other portion of a route.
[0124] As described above, the power management device or system
may also include statistical destination logic. Statistical
destination logic may infer one or more likely destinations based
on the information inputs. For example, the power management system
may infer the destination of the route based on the current
location and direction of the vehicle, and the date and time of
day. In some variations, the power management system is unable to
infer a final destination, but it can generate an intermediate
destination or segment for the route, as described above. The
probable destination(s) identified by the statistical destination
logic may then be used to optimize the power needed to travel the
route or a segment of the route, and to determine a historical
probable optimal speed.
[0125] In some variations, the power management device or system
includes simulated energy requirement logic and statistical route
analysis logic. As described above, simulated energy requirement
logic may determine a calculated optimized speed for the vehicle,
and statistical route analysis logic may be used to determine a
probable optimal speed. The power management device or system may
also include derived efficient speed logic that determines the most
efficient speed or power to be applied to the vehicle engine, as
described above.
[0126] Power management logic can coordinate different components
of the power management system, including the logic components,
user interfaces, informational data inputs, memory, processors,
motor control mechanisms, and the like. Thus, the power management
system may include power management logic to control the overall
activity of the power management system. FIG. 6 shows a graphical
representation of one variation of the power management device,
indicating that the power management logic controls and coordinates
the various components of the system. In FIG. 6, the polling logic
607 coordinates the activity of information inputs 601, 603, 605.
The information inputs are also linked to each other and to the
statistical destination logic 609, statistical route analysis logic
611, and simulated energy requirement logic 613. In particular,
these elements are all connected to the memory, and may read and
write to this memory. The derived efficient speed logic also
controls these three logic elements 609, 611, and 613. As described
above, the derived efficient speed logic 615 may produce an
efficient speed output for each part of the route (e.g., the speeds
or applied powers resulting from optimizing the fuel efficiency
over the route or parts of the route). Before this applied power
can be used to control the motor (via a motor control mechanism
619), the power management logic may check for overrides such as
operator overrides (e.g., breaking), or other overrides that may be
indicated by the headway cruise control box 617. For example, the
operator may override the power management device by applying the
brakes, etc. The power management device may also be preempted by
an obstruction (such as another vehicle) in the "headway" that
blocks the vehicle, requiring the vehicle to slow or stop.
[0127] FIG. 6 shows one variation of the power management device
descried herein. As will be apparent to those of skill in the art,
different variations are possible. For example, additional
components (e.g., communications elements, microprocessors,
memories, etc.), and/or additional logic (e.g., route segmentation
logic, operator interface logic, etc.) may also be included. In
some variations, some of the elements may be omitted (e.g., the
separate polling logic), or may be combined with other elements. In
some variations, the organization of the elements may be different.
For example, the statistical destination logic may be controlled by
the polling logic, rather than the derived efficient speed
logic.
[0128] Power Management Devices
[0129] In general, the power management device comprises power
management logic that receives information input about the external
environment of the vehicle, the operational status of the vehicle,
one or more command inputs from the driver, and one or more
operational parameters of the vehicle. The power management device
may also include additional components such as information inputs
(e.g., sensors, detectors, relays, etc.), one or more processors
(e.g., microprocessors), memories (e.g., databases, ROM, RAM,
EPROM, etc.), communications devices (e.g., wireless connections),
user interfaces (e.g., screens, control panels, etc.), and/or motor
control mechanisms. In some variations, the power management device
may be installed into the vehicle by the vehicle manufacturer. In
other variations, the power management device may be retrofitted
into a vehicle. In general, the power management device or system
intervenes between the driver and the engine. In practice, the
power management system may be physically located in any
appropriate location in the vehicle. FIG. 7 shows one example of a
vehicle having a power management system 701 as described herein.
In FIG. 7, the power management system is shown in the front of the
car 700, connecting the motors 705 and batteries 707. Any
appropriate sensors, detectors or data inputs may be used with the
power management devices and systems described herein. For example,
sensors for detecting external environmental information may be
used (e.g., optical, mechanical, electrical, or magnetic sensors).
Sensors may be monitored (e.g., polled) in real-time, as described
above. For example, polling logic may coordinate continuous or
periodic polling of Global Positioning System (GPS) information
(e.g., giving information on the vehicle's current location,
current elevation, upcoming elevations, upcoming terrain, vehicle's
destination, etc.), speedometer information (e.g., vehicle's
current speed, motor speed), date and time information (e.g., the
date and time may be used to determine personal driving habits and
sun angle), gyroscope information (e.g., vehicle's current
orientation, current slope/grade of road), RPM (e.g., motor and
wheel rotations per minute), accelerator and brake pedal position
(e.g., pressure applied and/or current angle of the petals), the
angle of sun (e.g., sensors may detect latitude, longitude, time of
day, date), weather (e.g., wind direction and velocity, rain, sun,
snow, etc.), battery state (e.g., voltage, amp hour meter, etc.),
tire pressure (e.g., may be used to calculate the drag force due to
rolling resistance), headway control information (e.g., the
distance from a car in front of the vehicle), the weight of car
(e.g., weight of cargo, passengers, driver), airflow (e.g., the
amount of air going to the engine), gas flow sensor (e.g., the
amount of gas going to engine of a hybrid or ICE car), weight of
driver (e.g., may be used identify the driver and linked to
personal driving habits). Different detectors or sensors may be
polled at different intervals, including continuously, or only
occasionally. Polling may also depend upon the availability of a
resource. For example, information may be available only when a
telecommunications network (e.g., satellite, cellular, etc.) is
available.
[0130] In some variations, a memory may be used. The memory may be
read/write memory, or read only memory. The memory may include
information, such as information on the operational parameters of
the vehicle related to the make and model of the vehicle. As
described above, operational parameters may include look up tables,
charts, or the like. For example, a memory may include information
about an aerodynamic model (CDA) for the vehicle, a rolling
resistance model (Crr1 and Crr2), a drive train efficiency model, a
motor efficiency model, and/or a battery model (e.g., charge and
discharge graphs for the battery). In some variations, these models
are not part of a memory, but are algorithms or logic.
[0131] Any appropriate memory may be used, including ROM, RAM,
removable memories (e.g., flash memory), erasable memories (e.g.,
EPROM), digital media (e.g., tape media, disk media, optical
media), or the like. In some variations, the memory may comprise a
database for holding any of the route information (including
historical route information), about the segments traveled, the
speeds traveled, energy usage measured or calculated for this route
or segment, who the driver was, external environmental conditions
while driving the route, operational status of the vehicle while
driving the route, and command inputs while driving the route. The
power management system may include more than one memory.
[0132] The power management system may also include one or more
user interfaces. A user interface may allow input of user command
information (e.g., selecting a destination, selecting a route,
selecting a target speed or speeds, selecting a range of acceptable
speeds, etc.). In some variations, a user interface may also
provide output from the power management system that can be viewed
by the user. For example, the user interface may provide visual or
auditory output, or suggest target speeds that the user can match
to optimize power supplied to the vehicle. In some variations the
user interface may provide status information to the user about the
power management system. For example, the user interface may
indicate that the power management system is engaged, what the
destination (or predicted destination) is, what the optimal speed
(or speeds) is, what inputs are missing or estimated, or the like.
In some variations, the user interface may display any of the
information inputs.
[0133] FIG. 8 shows one variation of a user interface for a power
management device or system. In FIG. 8, the user interface 800
includes a screen region 801, that shows a two-dimensional map
indicating at least part of the route 805 and the direction of
travel 803, the temperature of the external environment 807, the
weather 809 (indicated by an icon), the current or derived
efficient speed 811, the set (or cruising) speed 813, and the range
within which the speed should be maintained 815. The screen region
of the user interface shown in FIG. 8 also shows the destination
819.
[0134] In some variations, the user interface of the power
management system may include multiple screens for displaying
information, or for accepting user input. In FIG. 8, the user
interface also includes a plurality of buttons 821, including a
toggle 823 allowing menu-driven interaction. The user interface may
also include messaging features. For example, when the vehicle is
turned on but stopped, a user interface may indicate a message has
been sent/received (e.g., by flashing, etc.). When the user presses
a "Messages" button, the system may display feedback messages. For
example, if the tire pressure sensor notices that the tire pressure
is low, a message to that effect will be displayed to the user.
Diagnostic/test messages can also be sent to this screen for
testing, development, or repair purposes. The messaging features
may be included on the face of the user interface (e.g., as a
"Messages" button 821, etc.).
[0135] FIG. 9 illustrates the flow of information in one variation
of a power management system. Information inputs into the power
management system 901, 903, 905 enter the system and some (or all
of them) may be displayed by the user interface. For example,
external information inputs 901 may be shown. The status of some of
the information inputs (or the status of the detectors that receive
the information inputs) may also be shown. For example, the user
interface can indicate when the system is connected to an external
information input. In some variations, the external information
inputs may be connected to the power management system by a
wireless transmission (e.g., from an external source), and the
connection to the external source may be indicated by the user
interface. As described above, the user interface may accept
command inputs from the driver (or a passenger) 905. In some
variations, user commands may be accepted directly by using buttons
on the user interface, or by voice commands. In other variations,
at least some of the user commands may be entered into the power
management system from another source (e.g., a separate cruise
control or GPS device). Finally, the user interface may indicate
the output of the power management device or system 909, typically
an efficient speed output for the engine.
[0136] In some variations, the power management system may include
a headway cruise control. The headway cruise control can prevent
collisions when the vehicle is in motion by overriding the power
management control system's control of the vehicle speed. In some
variations, the headway cruise control detects the proximity of
other vehicles or obstacles in the road ahead. The headway cruise
control may include sensors on the vehicle, such as laser,
ultrasound or other electronic distance measurement devices.
Increasingly, more vehicles are including some sort of GPS
interface to communicate with other vehicles to determine distance
between the vehicles to avoid collisions.
[0137] The power management devices and systems described herein
may also include a motor control mechanism. The motor/engine
controller changes the motor speed by mechanical operations such as
pulling on a cable to adjust gas/airflow mixture or by electrical
means with either analog or digital inputs by the driver. With
electric driven motors, a variable may be changed to increase or
decrease motor speed. In the cruise control settings, the speed of
the motor may change based algorithm in the processor.
[0138] The power management devices and systems described herein
may be organized in any appropriate manner, as described above. For
example, in some variations, the power management device described
herein may include component parts that are connected as
illustrated in FIG. 10. FIG. 10 shows a schematic of one variation
of a power management device. In FIG. 10, the power management
system includes a central processor 1001 (CPU) that can execute
control logic such as power management control logic, statistical
destination logic, simulated energy requirement logic, statistical
route analysis logic, derived efficient speed logic, polling logic,
etc. This CPU receives inputs from sensors 1005, GPS receiver 1007,
a clock 1011, a telemetry data receiver 1009, a speech recognition
processor 1021 (including a microphone 1019, 1025), user interface
buttons 1039, 1037, and memory components (including RAM 1035, a
long-term memory 1033, firmware ROM 1031, and a removable memory
1029, 1041). The CPU may also coordinate output through the LCD
display 1015, 1017, a speaker 1023, 1027, and the motor control
mechanism (motor controller) 1043. In some variations, the sensors
1045 may also be included as part of the power management devices
or systems.
[0139] As described above, the power management system may also be
used with a telemetry system. Thus, the power management system may
communicate with one or more external components. For example, the
power management system may store information in a remote memory.
The power management system may also contribute to a database of
information about route, road conditions, and the like, such as a
database of historical route information. In some variations, the
motor control system may remotely communicate with a processor, so
that at least some of the control logic is applied remotely.
[0140] FIG. 11 shows a schematic illustrating the use of telemetry
by the motor control system. In FIG. 11, a power management device
1101 communicates by wireless communication with a database 1107
through a transmitter/receiver 1105 (shown as a satellite). Any
reasonable type of wireless communications may be used, including
cellular, wireless internet connections, radio, or the like. In
this example, the database may both receive data from the power
management device and/or transmit data or instructions to the power
management device. Communication between the power management
device and other components that are remotely located (e.g.,
memory, processor, information inputs) may also be used to update
or correct the power management device. For example, the
operational parameters of the vehicle may be revised or updated
from a remote source. In some variations, control logic (e.g.,
power management control logic) may be remotely updated or
revised.
[0141] The concepts described above may be used in various
combinations to optimize the power used by a vehicle. Examples of
power management systems, including methods of using them, are
described below.
EXAMPLES
[0142] 1. Fuel Efficient Hybrid Vehicle
[0143] Using one variation of the power management system described
herein (e.g., a power management system having an integrated with a
GPS), a hybrid car approaching a large hill or grade can adjust the
ratio of electric to ICE such that the batteries would be empty at
the crest of the hill and fully charged at the bottom of the hill,
and therefore would use less gasoline.
[0144] The same methods described above could be used to calculate
the energy usage of the vehicle as in the previous example. The mix
of electric to ICE can be based on the calculated energy usage and
the energy stored in the batteries. The exact mechanism for
instructing the hybrid vehicle to alter its electric/ICE ratio may
vary between manufacturers.
[0145] 2. Fuel Efficient Internal Combustion Engine (ICE)
Vehicle
[0146] Using one variation of the power management system described
herein, an ICE car will speed up on a downhill when it knows that
an uphill is the next terrain, and thereby use momentum to get up
the hill, using less gasoline. FIG. 1B illustrates this Example. As
described previously, the system may determine the optimum energy
using external and internal sensors and information, including the
operational parameters appropriate to the vehicle. Such operational
parameters may vary from manufacturer to manufacturer (or vehicle
to vehicle), and, as described above, could involve sending an
electrical signal to a computer-based motor controller or even
mechanically controlling the gas/air-flow mixture to the
engine.
[0147] 3. Energy Efficient Solar-Powered Vehicle
[0148] Using one variation of the power management system described
herein, a solar-powered car can ensure that it has adequate power
to traverse a predetermined route. The power management system may
ensure that there is enough solar energy power for the route by
slowing and speeding the car as necessary based on current energy
levels and anticipated energy needs.
[0149] This example is similar to the example discussed when
determining the optimum speed above, with a couple of additional
steps. In addition to calculating the energy usage, the system may
also include a solar array model that could model the power
generated by the solar array throughout the route base on the
predicted weather, geographic location, and time of day. A battery
model may also be included to keep track of the energy put into the
batteries by the solar array, and the energy drawn from the
batteries by the motor. When selecting the optimum speeds to drive
the segments of the route, the system logic (e.g., software,
hardware or both), may apply or access the battery model to prevent
the battery from becoming completely drained.
[0150] 4. Preventing Engine Flooding
[0151] One of the keys to efficient driving is not to step on the
accelerator more than the engine can actually burn and use
efficiently. Flooding the engine not only wastes gas but it doesn't
maximize power, despite the drivers' demands. According to one
variation of the power management system described herein, a
traditional ICE engine may be protected from flooding of the engine
using the power management device.
[0152] In this variation of a power management device, power
management device receives information inputs including a command
input (acceleration), at least two environmental inputs (air
resistance), the operational status of the vehicle (velocity and
engine temperature), and at least one operational parameter (e.g.,
maximum fuel volume). For example, the power management device may
receive information about the amount of pressure that the driver is
applying to the accelerator. The power management system may also
detect the current speed, resistance and temperature of the
vehicle. This information input may be used to select the proper
operational parameter of the vehicle. For example, the device may
include a memory having a table of maximum fuel volumes for a given
velocity, resistance and temperature. Thus, the velocity,
resistance and temperature data may be used to look up a maximum
fuel volume. In some variations, the maximum fuel volume may be
calculate or estimated from this data. By comparing the operator
demand (for acceleration) to supply fuel with the maximum amount of
fuel that the engine can handle, the power management control logic
may correct for the drivers inefficiency, and instruct the motor
control mechanism to provide the actual maximum amount of fuel to
the engine, thereby avoiding flooding of the engine.
[0153] This is a last example is a very simplified case of the
overall actions of the power management control system. In general,
the power management device intervenes between the driver and the
engine. Thus, the power management device may interpret the driver
commands so that the driving objective is achieved while maximizing
the efficiency of the vehicle based on information that is not
generally accessible or interpretable by the driver. While the
invention has been described in terms of particular variations and
illustrative figures, those of skill in the art will recognize that
the invention is not limited to the variations or figures
described.
[0154] For example, in one variation the system would be able to
notify the driver the most fuel efficient speed for a route segment
or segment destination. The notification might be via voice,
written word, numbers, symbols, colors and/or the like. The vehicle
operator can then manually adjust the vehicle speed based in
response to the notification. In this example, the calculated power
would not necessarily be directly applied to the vehicle engine as
it would just be used as a driver alert.
[0155] In still another variation, the power consumption
calculation could further include or be based on calculating an
optimal acceleration to (gradually) accelerate to the determined
efficient speed to travel the segment destination or optimal
deceleration to (gradually) decelerate to the determined efficient
speed to travel the segment destination. The calculation could for
example incorporate GPS information, the determined efficient speed
to travel the segment destination, or a combination thereof.
[0156] In still another variation, the information could be based
on past history information of the vehicle, information of one or
more other vehicles traveling one or more of the same route
segments, or a combination thereof. For example, if one drives the
same route to work each day, the energy consumption of those
various trips can be stored along with the speeds driven along
different segments of the route. From enough historical data, an
optimized route could be determined.
[0157] In still another variation, the information could be stored
information of vehicles traveling overlapping route segments. If
many cars drive along overlapping segments, their energy usage for
those segments could be uploaded to e.g. a centralized server where
optimized speeds for those segments could be calculated. Those
optimized speeds could be shared in several ways such as, but not
limiting to, (i) transmitted directly to cars, where they could be
used in fuel economy optimizing cruise control, (ii) transmitted to
cars where they could be used to provide recommendations to
drivers, (iii) shared via a web site where drivers could view
recommendations, (iv) shared via a web site where drivers could
compare their fuel economy to that of other drivers. The data could
be used by state or local governments to adjust speed limits to
improve the overall fuel economy of the cars that drive along their
roads.
[0158] In still another variation, an automatic transmission
vehicle could use the determined efficient speed to intelligently
shift gears, i.e., the optimized speed for (upcoming) route
segments could be used by the automatic transmission to make
intelligent decisions about shifting gears which would improve
overall drive train efficiency.
[0159] In addition, where methods and steps described above
indicate certain events occurring in certain order, those of skill
in the art will recognize that the ordering of certain steps may be
modified and that such modifications are in accordance with the
variations of the invention. Additionally, certain steps may be
performed concurrently in a parallel process when possible, as well
as performed sequentially as described above. Therefore, to the
extent there are variations of the invention, which are within the
spirit of the disclosure or equivalent to the inventions found in
the claims, it is the intent that this patent will cover those
variations as well. Finally, all publications and patent
applications cited in this specification are herein incorporated by
reference in their entirety as if each individual publication or
patent application were specifically and individually put forth
herein.
* * * * *
References