SYSTEMS AND METHODS FOR PREDICTING BATTERY POWER-DELIVERY PERFORMANCE

• US 20120274285A1
• Filed: 04/27/2011
• Published: 11/01/2012
• Est. Priority Date: 04/27/2011
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Chawla, Monika, Doganaksoy, Necip, Wiegman, Herman
• Granted Patent: US 8,872,481 B2
• Time in Patent Office: Days
• US Class Current: 320/127
• CPC Class Codes: G01R 31/389 Measuring internal impedance, internal conductance or related variables
• CPC Class Codes: G01R 31/392 Determining battery ageing or deterioration, e.g. state of health
• CPC Class Codes: H01M 10/44 Methods for charging or discharging circuits for charging H02J7/00
• CPC Class Codes: H01M 10/448 End of discharge regulating measures
• CPC Class Codes: Y02E 60/10 Energy storage using batteries

Abstract

Battery management systems and methods related to predicting power-delivery performance are provided. In one embodiment, a method for predicting power-delivery performance for a battery includes retrieving a plurality of battery operating parameters for a selected discharge cycle, calculating an offset indicative of a difference between a modeled internal resistance of the battery and an observed internal resistance generated from a calibration discharge cycle of the battery prior to the selected discharge cycle, and outputting a battery power-delivery performance prediction based on an offset-corrected internal resistance indicative of a difference between a modeled internal resistance based on the plurality of battery operating parameters for the selected discharge cycle and the offset.

Claims

1. A method for predicting power-delivery performance for a battery, comprising:

retrieving a plurality of battery operating parameters for a selected discharge cycle;

calculating an offset indicative of a difference between a modeled internal resistance of the battery and an observed internal resistance generated from a calibration discharge cycle of the battery prior to the selected discharge cycle; and

outputting a battery power-delivery performance prediction based on an offset-corrected internal resistance indicative of a difference between a modeled internal resistance based on the plurality of battery operating parameters and the offset.

2. The method of claim 1, further comprising:

receiving a user-defined power level; and

outputting a battery power-delivery performance prediction based on the offset-corrected internal resistance and the user-defined power level.

3. The method of claim 1, further comprising:

receiving a user-adjusted power level that is different from the user-defined power level; and

outputting an updated battery power-delivery performance prediction based on the offset-corrected internal resistance and the user-adjusted power level.

4. The method of claim 1, wherein the battery power-delivery performance prediction includes a time remaining till the battery reaches an end-of-discharge internal resistance.

5. The method of claim 1, wherein the battery power-delivery performance prediction includes a vehicle travel distance till the battery reaches an end-of-discharge internal resistance.

6. The method of claim 1, wherein the battery power-delivery performance prediction includes a battery state-of-health indicating whether the battery can deliver power for at least a target time.

7. The method of claim 6, further comprising:

receiving a user-defined target time; and

adjusting the battery state-of-health based on the user-defined target time.

8. The method of claim 1, wherein the plurality of battery operating parameters includes an operating current, an operating temperature, an observed internal resistance, and a charge state.

9. The method of claim 1, wherein retrieving the plurality of battery operating parameters for the selected discharge cycle includes receiving a plurality of sensor signals indicative of the plurality of battery operating parameters in real time, and the battery power-delivery performance prediction is updated in real time during a current discharge cycle.

10. The method of claim 1, wherein retrieving the plurality of battery operating parameters for the selected discharge cycle includes retrieving the plurality of battery operating parameters stored from a previous discharge cycle prior to a next discharge cycle, and the battery power-delivery performance prediction applies to the next discharge cycle.

11. A method for predicting power-delivery performance for a battery, comprising:

receiving a user-defined power level;

retrieving a plurality of battery operating parameters for a current discharge cycle in real time;

calculating an offset indicative of a difference between a modeled internal resistance of the battery and an observed internal resistance generated from a calibration discharge cycle of the battery prior to the current discharge cycle; and

outputting, during the current discharge cycle, a battery power-delivery performance prediction based on an offset corrected internal resistance indicative of a difference between a modeled internal resistance based on the plurality of battery operating parameters and the offset, and the user-defined power level.

12. The method of claim 11, further comprising:

receiving a user-adjusted power level that is different from the user-defined power level; and

outputting an updated battery power-delivery performance prediction based on the offset-corrected internal resistance and the user-adjusted power level.

13. The method of claim 11, wherein the battery power-delivery performance prediction includes a time remaining till the battery reaches an end-of-discharge internal resistance.

14. The method of claim 11, wherein the battery power-delivery performance prediction includes a distance till the battery reaches an end-of-discharge internal resistance.

15. The method of claim 11, wherein the battery power-delivery performance prediction includes a battery state-of-health indicating whether the battery can deliver power for at least a target time.

16. The method of claim 11, wherein the calibration cycle is a full discharge cycle when a cycle count of discharge cycles without an occurrence of a full discharge cycle is less than a discharge cycle threshold and the calibration cycle is a partial discharge cycle when the cycle count of discharge cycles without an occurrence of a full discharge cycle is greater than the discharge cycle threshold.

17. A battery management system comprising:

a battery;

a plurality of battery sensors operable to send a plurality of sensor signals indicative of a plurality of battery operating parameters to a prediction circuit;

the prediction circuit being operable in an offline mode to retrieve a plurality of stored battery operating parameters from a previous discharge cycle, calculate an offset indicative of a difference between a modeled internal resistance of the battery and an observed internal resistance generated from a calibration discharge cycle of the battery prior to the previous discharge cycle, and output a battery power-delivery performance prediction based on an offset-corrected internal resistance indicative of a difference between a modeled internal resistance based on the plurality of stored battery operating parameters and the offset, the battery power-delivery performance prediction being applicable to a next discharge cycle, and the prediction circuit being operable in an online mode to receive the plurality of battery sensor signals indicative of the plurality of battery operating parameters during a current discharge cycle, calculate an offset indicative of a difference between a modeled internal resistance of the battery and an observed internal resistance generated from a calibration discharge cycle of the battery prior to the current discharge cycle, and output a battery power-delivery performance prediction based on an offset-corrected internal resistance indicative of a difference between a modeled internal resistance based on the plurality of battery operating parameters for the current discharge cycle and the offset, the battery power-delivery performance prediction being applicable to the current discharge cycle, the battery power-delivery performance prediction being applicable to the current discharge cycle; and

a display device operable to receive the power-delivery performance prediction from the prediction circuit and display the battery power-delivery performance prediction.

18. The battery management system of claim 17, wherein the prediction circuit is operable to receive a user-defined power level, and output a battery power-delivery performance prediction based on the offset-corrected internal resistance and the user-defined power level.

19. The battery management system of claim 17, wherein the battery power-delivery performance prediction includes a battery state-of-health indicating whether the battery can deliver power for at least a target time, and the prediction circuit is operable to receive a user-defined target time, and adjusting the battery state-of-health based on the user-defined target time.

20. The battery management system of claim 17, wherein the battery power-delivery performance prediction includes a time remaining till the battery reaches an end-of-discharge internal resistance, a distance till the battery reaches an end-of-discharge internal resistance, and a battery state-of-health indicating whether the battery can deliver power for at least a target time.