Vehicle accessory load controller and method

• US 9,043,085 B2
• Filed: 08/29/2013
• Issued: 05/26/2015
• 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.
• Primary Examiner(s): Tarcza, Thomas
• Assistant Examiner(s): ALHARBI, ADAM MOHAMED
• Application Number:
  US14/014,211
• Publication Number:
  US 20140200763A1
• Time in Patent Office: 635 Days
• Field of Search: None
• US Class Current: 701/36
• CPC Class Codes: B60L 58/13 Maintaining the SoC within a determined range
• CPC Class Codes: B60L 7/10 Dynamic electric regenerative braking B60L7/22 takes precedence
• CPC Class Codes: B60W 10/24 including control of energy storage means
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries

Abstract

A system includes a source of regenerative power that generates power during a regenerative event, an electrical energy storage system connected with the source of regenerative power to receive and store regenerative power during the regenerative event, an accessory load that reduces an amount of energy stored in the energy storage system when being powered, a source of information, and an accessory load controller. The accessory load controller is responsive to the source of information to estimate when a next occurrence of a regeneration event will occur, predict whether the energy storage device will be in a state of charge condition to receive regenerative power at the time of the predicted regeneration event, and control an application of electrical power to the accessory load based on the prediction in order to reduce the amount of energy stored in the energy storage device and minimize any loss of regenerative power during a next regenerative event.

Claims

1. A system, comprising:

a source of regenerative power that generates power during a regenerative event;

an electrical energy storage system connected with the source of regenerative power to receive and store regenerative power during the regenerative event;

an accessory load that reduces an amount of energy stored in the energy storage system when being powered;

a source of information; and

an accessory load controller responsive to the source of information to;

estimate when a next occurrence of a regeneration event will occur,

predict whether the energy storage device will be in a state of charge condition to receive regenerative power at the time of the predicted regeneration event,

estimate a time needed to drain power from the energy storage device,

compare a risk of losing regenerative power based on when the next occurrence of the predicted regenerative event will occur and the time needed to drain the energy storage device to enable optimum benefit from the predicted regenerative event, and

control an application of electrical power to the accessory load based on the prediction in order to reduce the amount of energy stored in the energy storage device and minimize any loss of regenerative power during the predicted regenerative event.

2. The system of claim 1, wherein the accessory load is from a vehicle and the predicted regenerative event is based in part upon at least one of:

a prior history of accessory load usage,

prior history of accessory load usage over multiple time scales,

a history of accessory load usage over a time period of between prior seconds and a prior hour during a current trip of the vehicle,

a stored history of accessory load usage during trips prior to a current trip,

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.

3. The system of claim 1, wherein the accessory load is from a vehicle and the predicted regenerative event is based at least in part on at least one of:

a statistical model,

detected type of driving style including speed and acceleration,

stored driving data from prior trips of the vehicle,

stored energy storage device data,

explicit route information from a vehicle navigation system, and

route information from a GPS unit.

4. The system of claim 1, wherein the accessory load controller is responsive to a state of charge decreasing below a preselected minimum to delay application of power to the accessory load until the amount of energy stored has been increased at least above the preselected minimum.

5. The system of claim 1, wherein the accessory load is from a vehicle and can be at least one of:

an optional accessory that is nonessential for operation of the vehicle,

an accessory that normally draws power intermittently,

an accessory that draws power based on a time schedule,

an air conditioner, and

an electrical heating unit.

6. The system of claim 1, wherein the accessory load controller accelerates power drain of the electrical energy storage system if a risk of losing regenerative power is greater than a level of disruption to normal operation of the accessory load.

7. The system of claim 1, wherein the source of regenerative power is connected with a drive train of a vehicle and the information is vehicle information.

8. A computer-implemented method of reducing loss of regenerative power provided by a regenerative power source by controlling power usage of an accessory load, comprising:

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

predicting when an electrical energy storage device connected with the regenerative power source will be in a condition to receive regenerative power;

estimating a time needed to reduce energy from the electrical energy storage device to a preselected level for receipt of regenerative power;

comparing a risk of losing regenerative power based on when the next regenerative event will occur and the estimated time needed to reduce the electrical energy storage device to benefit from the next regenerative event; and

controlling an application of electrical power to the accessory load to reduce loss of regenerative power due to the electrical energy storage device having a greater amount of energy to accept regenerative power during the next regenerative event.

9. The computer-implemented method of claim 8, wherein the regenerative power is in a vehicle and predicting the condition is based upon at least one of:

prior history of accessory usage,

prior history of accessory usage over multiple time scales,

a history of accessory usage over a time period of between prior seconds and a prior hour during a current trip of the vehicle,

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

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.

10. The computer-implemented method of claim 8, wherein the regenerative power is in a vehicle and prediction of the next regenerative event is based at least in part on at least one of:

a statistical model,

type of driving style including speed and acceleration,

stored driving data from prior trips of the vehicle,

stored energy storage device data,

explicit route information from a vehicle navigation system, and

route information from a GPS unit.

11. The computer-implemented method of claim 8, wherein controlling the application of electrical power comprises:

terminating the application of electrical power to the accessory load when an amount of energy stored in the electrical energy device decreases beneath a preselected minimum level.

12. The computer implemented method of claim 11, wherein the preselected minimum level is a first preselected minimum level, and wherein controlling the application of electrical power comprises resuming the application of electrical power to the accessory load when the amount of energy stored in the electrical energy storage device increases above a second preselected level after power has been automatically reduced.

13. The computer implemented method of claim 8, wherein controlling the application of electrical power comprises:

determining an amount of energy stored of the electrical energy storage device, and

responding to the amount of energy stored in the electrical energy storage device when above a preselected level by applying power to the accessory earlier than it would be applied during normal operation to reduce the amount of energy stored in the energy storage device, thereby enhancing acceptance of charge by the energy storage device during the next regenerative event.

14. The computer-implemented method of claim 8, wherein controlling the application of electrical power comprises:

determining a relative likelihood of the amount of energy stored in the electrical energy storage device being above a preselected level to receive regenerative power when the next occurrence of a regenerative event is predicted such that there will be a risk of losing regenerative power; and

applying power to the accessory load to reduce the amount of energy stored beneath the preselected level before the next predicted occurrence of the regenerative event.

15. The computer-implemented method of claim 8, wherein controlling the application of electrical power comprises:

accelerating power drain of the electrical energy storage device only if the risk of losing regenerative power is greater than a preselected level of disruption to normal operation of the accessory.

16. The computer-implemented method of claim 15, wherein the accessory load controller sets the accessory load to normal operation if the risk of losing regenerative power is less than a preselected maximum level of disruption to normal operation of the accessory.

17. The computer-implemented method of claim 8, wherein the regenerative power is in a vehicle and controlling the application of electrical power comprises comparing a risk of lost regenerative power with inefficiency that may result from early application of power to the accessory load, based on at least one of:

estimated reduction in regenerative capacity,

cost associated with a reduction in fuel economy, and

estimated cost of loss of useful energy.

18. A computing system, comprising:

a processing unit and a memory unit storing instructions that are operable, when executed by the processing unit, to cause the processing unit to perform a method for reducing loss of power from a regenerative source of power that is provided only intermittently during regenerative events to an energy storage device connected with both the source of regenerative power source and an accessory load due to the energy storage device having more than an optimal level of charge, the method comprising;

predicting when a next regenerative event will occur;

determining whether the energy storage device will be at a sufficiently low charge level to be able to accept and store a desirable amount of the regenerative power during the next regenerative event;

estimating a time needed to reduce energy from the electrical energy storage device to a preselected level for receipt of regenerative power;

comparing a risk of losing regenerative power based on when the next regenerative event will occur and the estimated time needed to reduce the electrical energy storage device to benefit from the next regenerative event; and

applying power to the accessory load to reduce a charge level of the energy storage device, if it is determined that the energy storage device will not be at the sufficiently low charge level at the time of the next regenerative event unless power is prematurely applied to the accessory.

19. The computing system of claim 18, wherein the computing system refrains from applying power to the accessory load if it is determined that the energy storage device will be at the sufficiently low charge level at the time of the next regenerative event.

20. The computing system of claim 18, wherein the computing system terminates the application of power to the accessory load after the occurrence of the next regenerative event or after the charge of the energy storage device has been reduced to the sufficiently low charge level.

21. The computing system of claim 18, wherein the computing system compares a cost of lost regenerative power against a cost of disruption to the system to determine if power should be prematurely applied to the accessory.

22. The computing system of claim 18, wherein determining whether the energy storage device will be at a sufficiently low charge level is based on at least one of:

a prior history of accessory usage,

prior history of accessory usage over multiple time scales,

a history of accessory usage over a time period of between prior seconds and a prior hour during a current trip of the vehicle,

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

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.

23. The computing system of claim 18, wherein predicting when the next regenerative event will occur is based at least in part on at least one of:

a statistical model;

type of driving style including speed and acceleration of a driver of a vehicle;

stored driving data from prior trips of the vehicle;

stored data;

explicit route information from a vehicle navigation system; and

route information from a GPS unit.

24. The computer system of claim 18, further comprising:

comparing a risk of lost regenerative power with inefficiency that may result from early application of power to the accessory load, wherein the comparison is based on at least one of estimated reduction in regenerative capacity, cost associated with a reduction in fuel economy, and estimated cost of loss of useful energy.