Optimized fuzzy logic controller for energy management in micro and mild hybrid electric vehicles

• US 9,669,724 B2
• Filed: 08/29/2013
• Issued: 06/06/2017
• Est. Priority Date: 08/31/2012
• 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): Khatib, Rami
• Assistant Examiner(s): BOOMER, JEFFREY C
• Application Number:
  US14/014,117
• Publication Number:
  US 20140067183A1
• Time in Patent Office: 1,377 Days
• Field of Search: None
• CPC Class Codes: B60L 1/003 to auxiliary motors, e.g. for pumps, compressors
• CPC Class Codes: B60L 1/02 to electric heating circuits
• 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 2200/44 Industrial trucks or floor conveyors
• CPC Class Codes: B60L 2210/12 Buck converters
• CPC Class Codes: B60L 2210/14 Boost converters
• CPC Class Codes: B60L 2240/12 Speed
• CPC Class Codes: B60L 2240/34 Cabin temperature
• 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 50/16 with provision for separate direct mechanical propulsion
• CPC Class Codes: B60L 50/40 using propulsion power supplied by capacitors
• CPC Class Codes: B60L 50/61 by batteries charged by engine-driven generators, e.g. series hybrid electric vehicles
• CPC Class Codes: B60L 50/66 Arrangements of batteries
• CPC Class Codes: B60L 58/12 responding to state of charge [SoC]
• CPC Class Codes: B60L 58/20 having different nominal voltages
• CPC Class Codes: B60L 58/26 : by cooling
• CPC Class Codes: B60L 7/18 : Controlling the braking effect B60L7/12, B60L7/14, B60L7/16 take precedence
• CPC Class Codes: B60W 10/08 : including control of electric propulsion units, e.g. motors or generators
• CPC Class Codes: B60W 10/26 : for electrical energy, e.g. batteries or capacitors
• CPC Class Codes: B60W 20/00 : Control systems specially adapted for hybrid vehicles hybrid vehicle design, B60K6/00; electric vehicles B60L
• CPC Class Codes: B60W 20/10 : Controlling the power contribution of each of the prime movers to meet required power demand
• CPC Class Codes: B60W 2510/244 : Charge state
• CPC Class Codes: Y02P 90/60 : Electric or hybrid propulsion means for production processes
• CPC Class Codes: Y02T 10/62 : Hybrid vehicles
• 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

Abstract

An energy storage system of a vehicle includes an energy storage device, a regulation device coupled to the energy storage device, one or more sensing devices for sensing current levels, voltage levels, temperature levels, and/or pressure levels of the energy storage device and/or on components thereof, and a control unit configured to determine dynamically a power flow in/out of the energy storage device using a fuzzy logic approach. The regulation device is configured to regulate at least one of a voltage level, a current level, and any additional state parameter of the energy storage device.

Claims

1. A computer-implemented method for controlling an operation of an energy storage system of a micro-hybrid vehicle, the method comprising:

determining, using a processor, a driving mode of the micro-hybrid vehicle, and determining a speed of the micro-hybrid vehicle when in the driving mode, wherein the driving mode comprises one of an engine-off mode, an acceleration mode, or a slow-down mode;

determining, using the processor, a target state of charge (SOC) of each of a first energy storage device and a second energy storage device based on the speed;

determining, using the processor, a current SOC of each of the first energy storage device and the second energy storage device;

determining, using the processor, an amount of power available from a regenerative event for;

regeneration of the first energy storage device;

regeneration of the second energy storage device;

electrical accessories associated with the micro-hybrid vehicle; and

a motor associated with the micro-hybrid vehicle, wherein the amount of power available from the regenerative event is determined based on a difference between the target SOC and the current SOC of each of the first energy storage device and the second energy storage device; and

directing, using the processor, a power flow from the regenerative event to the first energy storage device, the second energy storage device, the electrical accessories associated with the micro-hybrid vehicle, and the motor associated with the micro-hybrid vehicle using a fuzzy logic and the amount of power available from the regenerative event, wherein the fuzzy logic is configured to cause the processor to;

activate at least one of the electrical accessories when the current SOC of the second energy storage device is suitable for the at least one of the electrical accessories and when the driving mode of the micro-hybrid vehicle corresponds to the engine-off mode;

activate power boosting for the motor when the driving mode of the micro-hybrid vehicle corresponds to the acceleration mode; and

direct braking energy to the second energy storage device when the driving mode of the micro-hybrid vehicle corresponds to the slow-down mode.

2. The computer-implemented method of claim 1, wherein the processor is configured to control a second power flow between the first and second energy storages devices based on the difference between the target SOC and the current SOC.

3. The computer-implemented method of claim 1, wherein the processor is configured to control the power flow using a modulation technique.

4. The computer-implemented method of claim 1, wherein the fuzzy logic is configured to cause the processor to direct the braking energy to the first energy storage device when the driving mode of the micro-hybrid vehicle corresponds to the slow-down mode.

5. The computer-implemented method of claim 4, wherein the fuzzy logic is configured to cause the processor to activate at least one of the electrical accessories when the current SOC of the second energy storage device is suitable for the at least one electrical accessories and when the driving mode of the micro-hybrid vehicle corresponds to a stopped mode.

6. The computer-implemented method of claim 5, wherein the fuzzy logic is configured to cause the processor to provide a starting electric current using energy from the first energy storage device when the driving mode of the micro-hybrid vehicle corresponds to an engine cranking mode.

7. The computer-implemented method of claim 6, wherein the fuzzy logic is configured to cause the processor to provide the starting electric current when the first energy storage device has sufficient energy to provide the starting electric current.

8. The computer-implemented method of claim 7, wherein the fuzzy logic is configured to cause the processor to provide the starting electric current using energy from the second energy storage device when the first energy storage device does not have sufficient energy to provide the starting electric current.

9. A computer-implemented method for controlling an operation of an energy storage system of a micro-hybrid vehicle, the method comprising:

determining, using a processor, a driving mode of the micro-hybrid vehicle, and determining a speed of the micro-hybrid vehicle when in the driving mode, wherein the driving mode comprises one of a stopped mode, an engine cranking mode, or a slow-down mode;

determining, using the processor, a target state of charge (SOC) of each of a first energy storage device and a second energy storage device based on the speed;

determining, using the processor, a current SOC of each of the first energy storage device and the second energy storage device;

determining, using the processor, an amount of power available from a regenerative event for;

regeneration of the first energy storage device;

regeneration of the second energy storage device;

electrical accessories associated with the micro-hybrid vehicle; and

a motor associated with the micro-hybrid vehicle, wherein the amount of power available from the regenerative event is determined based on a difference between the target SOC and the current SOC of each of the first energy storage device and the second energy storage device; and

directing, using the processor, a power flow from the regenerative event to the first energy storage device, the second energy storage device, the electrical accessories associated with the micro-hybrid vehicle, and the motor associated with the micro-hybrid vehicle using a fuzzy logic and the amount of power available from the regenerative event, wherein the fuzzy logic is configured to cause the processor to;

activate at least one of the electrical accessories associated with the micro-hybrid vehicle when the driving mode corresponds to the stopped mode;

provide a starting electric current using energy from the first energy storage device when the driving mode of the vehicle corresponds to the engine cranking mode; and

direct braking energy to the second energy storage device when the driving mode of the micro-hybrid vehicle corresponds to the slow-down mode.

10. The computer-implemented method of claim 9, wherein the fuzzy logic is configured to cause the processor to provide the starting electric current using energy from the second energy storage device when the first energy storage device does not have sufficient energy to provide the starting electric current.

11. The energy storage system of claim 10, wherein the fuzzy logic is configured to cause the processor to direct the braking energy to the first energy storage device when the driving mode of the vehicle corresponds to the slow-down mode.

12. The energy storage system of claim 11, wherein the driving mode comprises an engine-off mode, and wherein the fuzzy logic is configured to cause the processor to activate the at least one of the electrical accessories when a first current SOC of the second energy storage device is suitable for the at least one of the electrical accessories and when driving mode corresponds to the engine-off mode.

13. The energy storage system of claim 12, wherein the driving mode comprises an acceleration mode, and wherein the fuzzy logic is configured to cause a regulation device to activate power boosting for the motor when the driving mode corresponds to the acceleration mode.

14. The energy storage system of claim 13, wherein the fuzzy logic is configured to cause the processor to provide the starting electric current using energy from the second energy storage device when the driving mode of the vehicle corresponds to the engine cranking mode.

15. A computer-implemented method for controlling an operation of an energy storage system of a micro-hybrid vehicle, the method comprising:

determining, using a processor, a driving mode of the micro-hybrid vehicle, and determining a speed of the micro-hybrid vehicle when in the driving mode, wherein the driving mode comprises one of an engine-off mode, an engine cranking mode, or a slow-down mode;

determining, using the processor, a target state of charge (SOC) of each of a first energy storage device and a second energy storage device based on the speed;

determining, using the processor, a current SOC of each of the first energy storage device and the second energy storage device;

determining, using the processor, an amount of power available from a regenerative event for;

regeneration of the first energy storage device;

regeneration of the second energy storage device;

electrical accessories associated with the micro-hybrid vehicle; and

a motor associated with the micro-hybrid vehicle, wherein the amount of power available from the regenerative event is determined based on a difference between the target SOC and the current SOC of each of the first energy storage device and the second energy storage device; and

directing, using the processor, a power flow from the regenerative event to the first energy storage device, the second energy storage device, the electrical accessories associated with the micro-hybrid vehicle, and the motor associated with the micro-hybrid vehicle using a fuzzy logic and the amount of power available from the regenerative event, wherein the fuzzy logic is configured to cause the processor to;

activate at least one of the electrical accessories when a first current SOC of the second energy storage device is suitable for the at least one of the electrical accessories and when the driving mode of the micro-hybrid vehicle corresponds to the engine-off mode;

provide a starting electric current using energy from the first energy storage device when the driving mode of the vehicle corresponds to the engine cranking mode; and

direct braking energy to the second energy storage device when the driving mode of the micro-hybrid vehicle corresponds to the slow-down mode.

16. The method of claim 15, wherein the fuzzy logic is configured to cause the processor to direct the braking energy to the first energy storage device when the driving mode of the micro-hybrid vehicle corresponds to the slow-down mode.

17. The method of claim 15, wherein the fuzzy logic is configured to cause the processor to provide the starting electric current using energy from the second energy storage device when the fuzzy logic determines that the first energy storage device does not have sufficient energy to provide the starting electric current.

18. The method of claim 15, wherein the fuzzy logic is configured to cause the processor to activate at least one of the electrical accessories when the current SOC of the second energy storage device is suitable for the at least one electrical accessories and when the driving mode of the micro-hybrid vehicle corresponds to a stopped mode.

19. The method of claim 15, wherein the target SOC of the first energy storage device and the second energy device is determined using a supervised learning approach.

20. The method of claim 15, wherein the fuzzy logic is configured to cause the processor to activate power boosting for the motor when the driving mode of the micro-hybrid vehicle corresponds to an acceleration mode.