System and Method For Optimizing The Storing of Vehicular Energy

• US 20140200756A1
• Filed: 08/29/2013
• Published: 07/17/2014
• Est. Priority Date: 01/11/2013
• Status: Active Grant

• Current Assignee: CPS Technology Holdings, LLC
• Original Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Inventors: Sisk, Brian C.
• Granted Patent: US 9,061,599 B2
• Time in Patent Office: Days
• US Class Current: 701/22
• CPC Class Codes: B60L 1/08 Methods and devices for control or regulation
• CPC Class Codes: B60L 15/2045 for optimising the use of energy
• CPC Class Codes: B60L 2200/12 Bikes
• CPC Class Codes: B60L 2200/18 Buses
• CPC Class Codes: B60L 2200/32 Waterborne vessels
• CPC Class Codes: B60L 2200/36 Vehicles designed to transport cargo, e.g. trucks
• CPC Class Codes: B60L 2200/40 Working vehicles
• CPC Class Codes: B60L 2240/545 Temperature
• CPC Class Codes: B60L 2240/547 Voltage
• CPC Class Codes: B60L 2240/549 Current
• CPC Class Codes: B60L 2240/622 by satellite navigation
• CPC Class Codes: B60L 2240/66 Ambient conditions
• CPC Class Codes: B60L 2240/80 Time limits
• CPC Class Codes: B60L 2250/16 by display
• CPC Class Codes: B60L 2260/54 Energy consumption estimation
• CPC Class Codes: B60L 3/12 Recording operating variables ; Monitoring of operating variables
• CPC Class Codes: B60L 50/16 with provision for separate direct mechanical propulsion
• CPC Class Codes: B60L 50/66 Arrangements of batteries
• CPC Class Codes: B60L 58/13 Maintaining the SoC within a determined range
• CPC Class Codes: B60L 58/21 having the same nominal voltage
• CPC Class Codes: B60L 7/14 : for vehicles propelled by ac motors
• CPC Class Codes: B60L 7/18 : Controlling the braking effect B60L7/12, B60L7/14, B60L7/16 take precedence
• CPC Class Codes: B60W 20/14 : in conjunction with braking regeneration
• CPC Class Codes: H02J 2310/48 : for electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: H02J 7/1423 : with multiple batteries
• CPC Class Codes: H02J 7/1446 : in response to parameters of a vehicle
• CPC Class Codes: Y02T 10/64 : Electric machine technologies in electromobility
• CPC Class Codes: Y02T 10/70 : Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 : Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 : Electric energy management in electromobility
• CPC Class Codes: Y02T 10/92 : Energy efficient charging or discharging systems for batteries, ultracapacitors, supercapacitors or double-layer capacitors specially adapted for vehicles
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y10S 903/903 : having energy storing means, e.g. battery, capacitor

Abstract

A system for storing electrically a regenerative energy of a vehicle is provided. The system includes a first energy storage device, a second energy storage device, an energy regulating device coupled to the first and second energy storage devices, a source of regenerative power configured to capture a regenerative energy during a regenerative power event of the vehicle, and a control unit coupled to the energy regulating device. The control unit is configured to transfer electrical energy from the first energy storage device to the second energy storage device based on a prediction of the regenerative power event using the energy regulating device. The transfer of the electrical energy serves to reduce the electrical energy stored in the first energy storage device thereby enabling the first energy storage device to receive from the regenerative power device when the predicted regenerative power event occurs an amount of the electrical regenerative energy.

Claims

1. A system for storing electrically a regenerative energy of a vehicle, comprising:

a first energy storage device;

a second energy storage device;

an energy regulating device coupled to the first and second energy storage devices;

a source of regenerative power for capturing regenerative energy during a regenerative power event of the vehicle; and

a control unit coupled to the energy regulating device, wherein the control unit is configured to transfer electrical energy from the first energy storage device to the second energy storage device based on a prediction of the regenerative power event using the energy regulating device, wherein the transfer of the electrical energy serves to reduce the electrical energy stored in the first energy storage device thereby enabling the first energy storage device to receive from the regenerative power device when the predicted regenerative power event occurs an amount of the electrical regenerative energy.

2. The system of claim 1, wherein the control unit is programmed to make a prediction of a time window when the next regenerative power event will likely occur.

3. The system of claim 2, wherein the prediction is based on at least one of a statistical driving model, a detected type of driving style including speed and acceleration, stored driving data from prior trips of the vehicle, stored energy data, and routing information.

4. The system of claim 2, wherein the control unit determines to pass on the electrical energy transfer based at least in part on an estimate of how quickly accessory load current can lower the SOC of the first energy storage device.

5. The system of claim 4, wherein the estimate is based at least in part on at least one of:

a prior history of accessory usage over multiple time scales;

a stored history of accessory usage during trips prior to the current trip;

a history of accessory usage during a time interval of a current trip of the vehicle;

a current state of the vehicle during the current trip including at least one of vehicular speed and acceleration; and

route information of the current trip.

6. The system of claim 5, wherein the estimate is further based at least in part on at least one of:

data collected from vehicle regarding prior, present, and/or predicted accessory data; and

data collected from accessories regarding prior, present, and/or predicted accessory data.

7. The system of claim 1, wherein the control unit is configured to compare a cost of losing regenerative energy because of a failure to timely transfer electrical energy, and a cost of lost transfer energy due to inefficiencies in passing energy from the first energy storage device to the second energy storage device.

8. The system of claim 1, wherein the control unit is configured to use the information to make predictions related to:

a time window when the next regenerative power event will likely occur,

how quickly a normal vehicle operation may drain the first energy storage device,

how likely the regenerating energy may be lost due to the first storage device having more than an optimum amount of electrical energy at the time of the next regenerative power event, and

how much energy may be lost due to inefficiencies in transferring energy from the first energy storage device to the second energy storage energy device; and

wherein the control unit makes a decision based on at least one of these predictions as to whether electrical energy should be transferred from the first energy device to the second energy storage device.

9. The system of claim 1, wherein the first energy storage device is a relatively high power storage device and the second energy storage device compared to the first energy storage device is a relatively high energy storage device.

10. The system of claim 1, further comprising:

a device for transferring energy from the first energy storage device back to wheels of the vehicle to provide propulsion power to the vehicle.

11. The system of claim 1, wherein the source of regenerative power is one of a generator, an alternator, a motor, or any combination thereof.

12. A computer-implemented method of reducing loss of regenerative energy in a vehicle by controlling energy storage devices that power the vehicle, comprising:

predicting when a next regenerative power event during a current trip will occur;

estimating when a first energy storage device connected for receipt of regenerative energy will be in an optimum condition to receive regenerative energy; and

transferring electrical energy from the first energy storage device to a second energy storage device to reduce the loss of regenerative power due to the first energy storage device having a greater than an amount of stored electrical energy suitable to accept regenerative energy during the predicted regenerative power event.

13. The computer-implemented method of claim 12, wherein automatically estimating is based upon at least one of:

a prior history of accessory usage over multiple time scales;

a stored history of accessory usage during trips prior to the current trip;

a history of accessory usage during a time interval of a current trip of the vehicle;

a current state of the vehicle during the current trip including at least one of vehicular speed and acceleration; and

route information of the current trip.

14. The computer-implemented method of claim 13, wherein automatically estimating is further based upon at least one of:

data collected from vehicle regarding prior, present, and/or predicted accessory data; and

data collected from accessories regarding prior, present, and/or predicted accessory data.

15. The computer-implemented method of claim 12, further comprising:

terminating the transferring of electrical energy from the first energy storage system to the second energy storage device when the first energy storage device has no greater amount than the suitable amount of stored electrical energy.

16. The computer-implemented method of claim 12, further comprising:

estimating a time needed to lower an SOC of at least one of the first and second energy storage devices to a suitable level for receipt of regenerative energy; and

comparing a risk of losing regenerative energy based on the estimated time to the next predicted regenerative power event and on the estimated time needed to lower the SOC of the at least one of the first and second energy storage devices.

17. The computer-implemented method of claim 12, wherein energy transferring is performed only if a risk of losing regenerative energy is greater than a preselected level of disruption of a normal operation of the vehicle.

18. The computer-implemented method of claim 12, wherein energy transferring is performed only if a loss of regenerative energy because of a failure to transfer energy is greater than efficiency lost from transferring energy from the first energy storage device to the second energy storage device.

19. The computer-implemented method of claim 12, wherein the first energy storage device is a high power storage device, and the second energy storage device is a high energy storage device.

20. A computing system, comprising:

at least one processing unit and at least one memory unit storing instructions that are operable, when executed by the at least one processing unit, to cause the at least one processing unit to perform a method for reducing loss of power from a regenerative source of power that is provided during regenerative power events, the method comprising;

predicting when a next regenerative power event during a current trip will occur;

estimating when a first energy storage device connected for receipt of regenerative energy will be in an optimum condition to receive regenerative energy; and

transferring electrical energy from the first energy storage device to a second energy storage device to reduce the loss of regenerative power due to the first energy storage device having a greater than an amount of stored electrical energy suitable to accept regenerative energy during the predicted regenerative power event.

21. The computing system of claim 20, wherein automatically estimating is based upon at least one of:

a prior history of accessory usage over multiple time scales;

a stored history of accessory usage during trips prior to the current trip;

a history of accessory usage during a time interval of a current trip of the vehicle;

a current state of the vehicle during the current trip including at least one of vehicular speed and acceleration; and

route information of the current trip.

22. The computing system of claim 20, wherein automatically estimating is further based upon at least one of:

data collected from vehicle regarding prior, present, and/or predicted accessory data; and

data collected from accessories regarding prior, present, and/or predicted accessory data.

23. The computing system of claim 20, further comprising:

terminating the transferring of electrical energy from the first energy storage system to the second energy storage device when the first energy storage device has no greater amount than the suitable amount of stored electrical energy.

24. The computing system of claim 20, further comprising:

estimating a time needed to lower an SOC of at least one of the first and second energy storage devices to a suitable level for receipt of regenerative energy; and

comparing a risk of losing regenerative energy based on the estimated time to the next predicted regenerative power event and on the estimated time needed to lower the SOC of the at least one of the first and second energy storage devices.

25. The computing system of claim 20, wherein energy transferring is performed only if a risk of losing regenerative energy is greater than a preselected level of disruption of a normal operation of the vehicle.

26. The computing system of claim 20, wherein energy transferring is performed only if a loss of regenerative energy because of a failure to transfer energy is greater than efficiency lost from transferring energy from the first energy storage device to the second energy storage device.

27. The computing system of claim 20, wherein the first energy storage device is a high power storage device, and the second energy storage device is a high energy storage device.