Method for determining state-of-charge using an intelligent system

• US 6,011,379 A
• Filed: 03/12/1998
• Issued: 01/04/2000
• Est. Priority Date: 03/12/1997
• Status: Expired due to Fees

• Current Assignee: Pritpal Singh, Villanova University
• Original Assignee: US Nanocorp, Inc. (The Nano Group, Inc.)
• Inventors: Singh, Pritpal, Fennie, Craig Jr.
• Primary Examiner(s): Tso, Edward H.
• Application Number:
  US09/041,562
• Time in Patent Office: 663 Days
• Field of Search: 320/128, 320/132, 320/134, 320/136, 320/148, 320/149, 320/150, 320/151, 320/152, 320/156, 320/157, 320/158, 320/159, 320/161, 320/162, 320/164, 320/FOR 130 , 320/FOR 134, 320/FOR 138, 320/FOR 142, 320/DIG. 21
• US Class Current: 320/132
• CPC Class Codes: B60L 2260/56 Temperature prediction, e.g. for pre-cooling
• CPC Class Codes: B60L 58/30 for monitoring or controlling fuel cells
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G01R 31/389 Measuring internal impedance, internal conductance or related variables
• CPC Class Codes: H01M 10/42 Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells H01M10/60 takes precedence
• CPC Class Codes: H01M 10/4257 Smart batteries, e.g. electronic circuits inside the housing of the cells or batteries
• CPC Class Codes: H01M 10/48 Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte constructional details of current conducting connections for detecting conditions inside cells or batteries, e.g. details of voltage sensing terminals, H01M50/569
• CPC Class Codes: H01M 10/486 for measuring temperature
• CPC Class Codes: H01M 8/04992 characterised by the implementation of mathematical or computational algorithms, e.g. feedback control loops, fuzzy logic, neural networks or artificial intelligence
• CPC Class Codes: Y02E 60/10 Energy storage using batteries
• CPC Class Codes: Y02E 60/50 Fuel cells
• CPC Class Codes: Y02T 90/40 Application of hydrogen technology to transportation, e.g. using fuel cells
• CPC Class Codes: Y10S 320/21 State of charge of battery

Abstract

A method for determining state of charge (SOC) of an electrochemical device using fuzzy logic (i.e., an intelligent system) is presented. State of charge of an electrochemical device is determined by an internal characteristic or parameter (or external operating and environmental conditions) with an intelligent system. The electrochemical device comprises such devices as primary ("throwaway") batteries, rechargeable batteries, fuel cells, a hybrid battery containing a fuel cell electrode and electrochemical supercapacitors. The intelligent system is trained in the relationship between the characteristic of the electrochemical device and the SOC of the electrochemical device.

Claims

1. A method of determining a state of charge of an electrochemical device, comprising:

detecting at least one internal characteristic of said electrochemical device; and

determining said state of charge of said electrochemical device from an intelligent system trained in a relationship between said at least one internal characteristic and said state of charge.

2. The method of determining said state of charge of claim 1 further comprising:

detecting at least one external characteristic of said electrochemical device; and

wherein said determining said state of charge of said electrochemical device from said intelligent system further includes, said intelligent system trained in a relationship between said at least one external characteristic and said state of charge.

3. The method of determining said state of charge of claim 1 wherein said at least one internal electrical characteristic comprises at least one internal impedance of said electrochemical device.

4. The method of determining said state of charge of claim 3 wherein said at least one internal impedance comprises a first internal impedance at a first frequency.

5. The method of determining said state of charge of claim 4 wherein said at least one internal impedance further comprises a second internal impedance at a second frequency.

6. The method of determining said state of charge of claim 1 wherein said intelligent system comprises a fuzzy system.

7. The method of determining said state of charge of claim 6 wherein said fuzzy system comprises an additive fuzzy system.

8. The method of determining said state of charge of claim 7 wherein said additive fuzzy system mathematically comprises:

##EQU4## where, w_j is a weight of rule j,

a_jⁱ represents if-part set function, membership function of input i of rule j on input i,

a_j represents joint if-part set function, result of "a_j¹ `and` a_j² . . . `and` a_jⁱ, that states a degree to which an input x belongs to the if-part fuzzy set a_j,

B_j represents then-part set function, membership function j on an output,

V_j is a finite positive volume or area of the then-part set B_j,

c_j is a centroid of the then-part set B_j,

B_j is a scaled then-part set, scaled output membership function j, result of a_j (x)B_j, and

B is an output set prior to defuzzification.

9. The method of determining said state of charge of claim 3 wherein said at least one internal impedance includes a resistive part and a reactive part.

10. The method of determining said state of charge of claim 1 wherein said electrochemical device comprises a primary battery, a rechargeable battery, a fuel cell, a hybrid battery containing a fuel cell electrode or an electrochemical supercapacitor.

11. The method of determining said state of charge of claim 2 wherein said at least one external characteristic comprises an external operating condition and an environmental condition.

12. The method of determining said state of charge of claim 11 wherein said relationship between said at least on external characteristic and said state of charge includes:

a relationship between said external operating condition and said environmental condition and a discharge efficiency of said electrochemical device.

13. The method of determining said state of charge of claim 12 wherein said external operating condition comprises current flow from said electrochemical device and said environmental condition comprises temperature of said electrochemical device.

14. The method of determining said state of charge of claim 12 wherein said relationship between said at least on external characteristic and said state of charge further includes:

a relationship between said discharge efficiency and said state of charge.

15. The method of determining said state of charge of claim 7 wherein said additive fuzzy system includes a subtractive clustering algorithm for developing input membership functions and rules.

16. A system for determining a state of charge of an electrochemical device, comprising:

a sensor for detecting at least one internal characteristic of said electrochemical device and providing an internal sensed signal indicative thereof; and

a signal processor responsive to said internal sensed signal for providing a state of charge signal, said signal processor including an intelligent system trained in a relationship between said at least one internal characteristic and said state of charge for determining said state of charge of said electrochemical device.

17. The system for determining said state of charge of claim 16 further comprising:

a sensor for detecting at least one external characteristic of said electrochemical device and providing an external sensed signal indicative thereof; and

wherein said signal processor is also responsive to said external sensed signal for determining said state of charge of said electrochemical device, said signal processor including said intelligent system which is further trained in a relationship between said at least one external characteristic and said state of charge.

18. The system for determining said state of charge of claim 16 wherein said at least one internal electrical characteristic comprises at least one internal impedance of said electrochemical device.

19. The system for determining said state of charge of claim 18 wherein said at least one internal impedance comprises a first internal impedance at a first frequency.

20. The system for determining said state of charge of claim 19 wherein said at least one internal impedance further comprises a second internal impedance at a second frequency.

21. The system for determining said state of charge of claim 16 wherein said intelligent system comprises a fuzzy system.

22. The system for determining said state of charge of claim 21 wherein said fuzzy system comprises an additive fuzzy system.

23. The system for determining said state of charge of claim 22 wherein said additive fuzzy system mathematically comprises:

##EQU5## where, w_j is a weight of rule j,

a_jⁱ represents if-part set function, membership function of input i of rule j on input i,

a_j represents joint if-part set function, result of "a_j¹ `and` a_j² . . . `and` a_jⁱ, that states a degree to which an input x belongs to the if-part fuzzy set a_j,

B_j represents then-part set function, membership function j on an output,

V_j is a finite positive volume or area of the then-part set B_j,

c_j is a centroid of the then-part set B_j,

B_j is a scaled then-part set, scaled output membership function j, result of a_j (x)B_j, and

B is an output set prior to defuzzification.

24. The system for determining said state of charge of claim 18 wherein said at least one internal impedance includes a resistive part and a reactive part.

25. The system for determining said state of charge of claim 16 wherein said electrochemical device comprises a primary battery, a rechargeable battery, a fuel cell, a hybrid battery containing a fuel cell electrode or an electrochemical supercapacitor.

26. The system for determining said state of charge of claim 17 wherein said at least one external characteristic comprises an external operating condition and an environmental condition.

27. The system for determining said state of charge of claim 26 wherein said relationship between said at least on external characteristic and said state of charge includes:

a relationship between said external operating condition and said environmental condition and a discharge efficiency of said electrochemical device.

28. The system for determining said state of charge of claim 27 wherein said external operating condition comprises current flow from said electrochemical device and said environmental condition comprises temperature of said electrochemical device.

29. The system for determining said state of charge of claim 27 wherein said relationship between said at least on external characteristic and said state of charge further includes:

a relationship between said discharge efficiency and said state of charge.

30. The system for determining said state of charge of claim 22 wherein said additive fuzzy system includes a subtractive clustering algorithm for developing input membership functions and rules.

31. The system for determining said state of charge of claim 16 further comprising:

a display responsive to said state of charge signal for displaying said state of charge.

32. A method of determining a state of charge of an electrochemical device, comprising:

detecting at least one characteristic of said electrochemical device; and

determining said state of charge of said electrochemical device from a fuzzy system trained in a relationship between said at least one characteristic and said state of charge.

33. The method of determining said state of charge of claim 32 wherein said at least one characteristic comprises at least one external characteristic.

34. A system for determining a state of charge of an electrochemical device, comprising:

a sensor detecting at least one characteristic of said electrochemical device and providing a sensed signal indicative thereof; and

a signal processor responsive to said sensed signal for determining said state of charge of said electrochemical device and providing a state of charge signal, said signal processor including a fuzzy system trained in a relationship between said at least one characteristic and said state of charge.

35. The system for determining said state of charge of claim 34 wherein said at least one characteristic comprises at least one external characteristic.

36. A method of determining a state of charge of an electrochemical device, comprising:

detecting at least one internal characteristic of said electrochemical device; and

determining said state of charge of said electrochemical device from an intelligent system trained in a relationship between said at least one internal characteristic and said state of charge, said intelligent system comprising an additive fuzzy system, and said additive fuzzy system mathematically comprising;

##EQU6## where, w_j is a weight of rule j,

a_jⁱ represents if-part set function, membership function of input i of rule j on input i,

a_j represents joint if-part set function, result of "a_j¹ `and` a_j² . . . `and` a_jⁱ, that states a degree to which an input x belongs to the if-part fuzzy set a_j,

B_j represents then-part set function, membership function j on an output,

V_j is a finite positive volume or area of the then-part set B_j,

c_j is a centroid of the then-part set B_j,

B_j is a scaled then-part set, scaled output membership function j, result of a_j (x)B_j, and

B is an output set prior to defuzzification.

37. A method of determining a state of charge of an electrochemical device, comprising:

detecting at least one internal characteristic of said electrochemical device; and

determining said state of charge of said electrochemical device from an intelligent system trained in a relationship between said at least one internal characteristic and said state of charge, said intelligent system comprising an additive fuzzy system, and said additive fuzzy system including a subtractive clustering algorithm for developing input membership functions and rules.

38. A system for determining a state of charge of an electrochemical device, comprising:

a sensor for detecting at least one internal characteristic of said electrochemical device and providing an internal sensed signal indicative thereof; and

a signal processor responsive to said internal sensed signal for determining said state of charge of said electrochemical device and providing a state of charge signal, said signal processor including an intelligent system trained in a relationship between said at least one internal characteristic and said state of charge, said intelligent system comprising an additive fuzzy system, said additive fuzzy system mathematically comprising;

##EQU7## where, w_j is a weight of rule j,

a_jⁱ represents if-part set function, membership function of input i of rule j on input i,

a_j represents joint if-part set function, result of "a_j¹ `and` a_j² . . . `and` a_jⁱ, that states a degree to which an input x belongs to the if-part fuzzy set a_j,

B_j represents then-part set function, membership function j on an output,

V_j is a finite positive volume or area of the then-part set B_j,

c_j is a centroid of the then-part set B_j,

B_j is a scaled then-part set, scaled output membership function j, result of a_j (x)B_j, and

B is an output set prior to defuzzification.

39. A system for determining a state of charge of an electrochemical device, comprising:

a sensor for detecting at least one internal characteristic of said electrochemical device and providing an internal sensed signal indicative thereof; and

a signal processor responsive to said internal sensed signal for determining said state of charge of said electrochemical device and providing a state of charge signal, said signal processor including an intelligent system trained in a relationship between said at least one internal characteristic and said state of charge, said intelligent system comprising an additive fuzzy system, said additive fuzzy system including a subtractive clustering algorithm for developing input membership functions and rules.