BATTERY STATE-OF-HEALTH MONITORING SYSTEM AND METHOD

• US 20090265125A1
• Filed: 04/22/2008
• Published: 10/22/2009
• Est. Priority Date: 04/22/2008
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations Incorporated (Motors Liquidation Co. GUC Trust)
• Inventors: ZHANG, Xiaodong
• Granted Patent: US 7,983,862 B2
• Time in Patent Office: Days
• US Class Current: 702/63
• CPC Class Codes: G01R 31/392 Determining battery ageing or deterioration, e.g. state of health
• CPC Class Codes: H01M 10/4207 for several batteries or cells simultaneously or sequentially
• CPC Class Codes: H01M 10/482 for several batteries or cells simultaneously or sequentially
• CPC Class Codes: Y02E 60/10 Energy storage using batteries

Abstract

A battery state-of-health monitoring and prognosis method includes off-line training of parity-relation parameters utilized in providing a measure of battery state-of-health.

Claims

1. A battery state-of-health monitoring and prognosis method comprising:

training off-line parity-relation parameters between extracted battery voltage and current signals during off-line battery discharge events using at least one good off-line battery;

extracting portions of terminal voltage and current signals of an on-board battery corresponding to an on-board engine cranking process;

estimating battery voltage of the on-board battery based on the parity-relation parameters and the extracted portions of the on-board battery current signals;

generating a diagnostic residual defining a deviation between the battery voltage estimation of the on-board battery and extracted portions of the on-board battery terminal voltage signals; and

providing a measure of battery state-of-health based on said diagnostic residual.

2. The battery state-of-health monitoring and prognosis method of claim 1, wherein training off-line parity-relation parameters is effected using extracted off-line battery voltage and current signals extracted in a range sufficient to start a vehicle.

3. The method of claim 2, wherein training a parity-relation parameters comprises using a linear regression model to define engine cranking dynamics of said at least one good off-line battery.

4. The method of claim 1 wherein said training further comprises extracting a portion of the off-line battery terminal voltage and current signals during an off-line battery discharge event from the at least one good off-line battery within an interval subsequent to a predetermined initial off-line voltage signal drop and ending when said off-line current signal attains a predefined value.

5. The method of claim 4, wherein the predefined value comprises substantially −

100 Amps.

6. The method of claim 1 wherein said extracting portions of on-board battery terminal voltage and current signals corresponding to an on-board engine cranking process is effected during an on-board engine cranking event within an interval subsequent to an initial on-board voltage signal drop due to starter engagement and ending when said on-board current signal attains a predefined value.

7. The method of claim 6, wherein extracted portions of on-board battery current signals comprise current signals in a range of about −

300 Amps to about −

100 Amps.

8. The method of claim 1, wherein generating a diagnostic residual comprises low pass filtering.

9. The method of claim 1, wherein providing a measure of battery state-of-health based on said diagnostic residual comprises:

providing a diagnostic residual threshold;

comparing the diagnostic residual to said diagnostic residual threshold; and

when said diagnostic residual crosses said diagnostic residual threshold, indicating said on-board battery is beyond a remaining useful life.

10. The method of claim 1, wherein providing a measure of battery state-of-health based on said diagnostic residual comprises:

indicating a remaining useful life of said on-board battery based on said diagnostic residual, a predetermined diagnostic residual threshold, and a predetermined nominal residual of a fresh battery.

11. The method of claim 9, wherein providing a diagnostic residual threshold comprises:

obtaining an on-board battery temperature;

obtaining an on-board battery start-up state-of-charge; and

determining the diagnostic residual threshold based on said on-board battery temperature and start-up state-of-charge.

12. The method of claim 10, wherein indicating a remaining useful life of said on-board battery comprises:

generating a battery state-of-health index (SOH_INDEX) in accordance with the relationship

13. The method of claim 9, wherein providing a measure of battery state-of-health based on said diagnostic residual further comprises:

prior to said diagnostic residual crossing said diagnostic residual threshold, indicating the remaining useful life of said on-board battery based on said diagnostic residual, a predetermined diagnostic residual threshold, and a predetermined nominal residual of a fresh battery.

14. The method of claim 13, wherein indicating the remaining useful life of said on-board battery comprises:

generating a battery state-of-health index (SOH_INDEX) in accordance with the relationship

15. The method of claim 13, wherein providing said diagnostic residual threshold comprises:

obtaining an on-board battery temperature;

obtaining an on-board battery start-up state-of-charge; and

determining said diagnostic residual threshold based on said on-board battery temperature and start-up state-of-charge.

16. An on-board battery state-of-health monitoring and prognosis apparatus, comprising:

a signal preprocessing module for extracting portions of on-board battery terminal voltage and current signals corresponding to an on-board engine cranking process;

a memory storage device for recalling parity-relation parameters between battery voltage and current signals derived during off-line battery discharge events corresponding to at least one good off-line battery;

a voltage estimation module for estimating battery voltage of said an on-board battery based on recalled parity-relation parameters and the extracted portions of the on-board battery current signals;

a diagnostic residual generation module for generating a diagnostic residual defining a deviation between the estimated battery voltage of the on-board battery and the extracted portion of the on-board battery terminal voltage signals; and

a residual evaluation module for providing a measure of battery state-of-health based on said diagnostic residual.

17. The apparatus of claim 16, wherein the diagnostic residual generation module comprises a low pass filter.

18. An on-board vehicular battery state-of-health monitoring and prognosis method comprising:

determining off-line parameters of a parity-relation between extracted battery signals using at least one good off-line battery;

storing the off-line determined parity-relation parameters in a memory device associated with a voltage estimation module within a battery state-of-health monitoring system on-board a vehicle having an engine;

inputting on-board battery terminal voltage and current signals from an on-board battery into a signal preprocessor module within said battery state-of-health monitoring system when said engine is cranked;

extracting a portion of the on-board battery terminal voltage and current signals using the signal preprocessor module;

estimating the battery voltage of the on-board battery using the stored off-line determined parity-relation parameters and the extracted portion of the on-board battery current signals;

generating a diagnostic residual with a residual generation module, wherein the diagnostic residual represents a deviation between the estimated battery voltage and the corresponding on-board battery terminal voltage signals; and

evaluating the diagnostic residual in a residual evaluation module to determine a state-of-health metric of the on-board battery.