Predicted sensor information for a battery

• US 9,318,781 B2
• Filed: 08/29/2013
• Issued: 04/19/2016
• 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): RYAN, PATRICK J
• Assistant Examiner(s): Rios, Jose Colucci
• Application Number:
  US14/014,243
• Publication Number:
  US 20140199569A1
• Time in Patent Office: 964 Days
• Field of Search: None
• US Class Current: 1/1
• 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 2260/44 by parameter estimation
• CPC Class Codes: B60L 2260/50 by future state prediction
• CPC Class Codes: B60L 3/0046 relating to electric energy storage systems, e.g. batteries or capacitors
• CPC Class Codes: B60L 50/64 Constructional details of batteries specially adapted for electric vehicles
• CPC Class Codes: B60L 50/66 Arrangements of batteries
• CPC Class Codes: B60L 58/14 Preventing excessive discharging
• CPC Class Codes: B60L 58/15 Preventing overcharging
• CPC Class Codes: B60L 58/16 responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH]
• CPC Class Codes: B60L 58/20 having different nominal voltages
• CPC Class Codes: B60L 58/22 Balancing the charge of battery modules
• CPC Class Codes: B60L 58/26 by cooling
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G01R 31/382 Arrangements for monitoring battery or accumulator variables, e.g. SoC
• CPC Class Codes: G01R 31/396 Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
• CPC Class Codes: H01M 10/4207 for several batteries or cells simultaneously or sequentially
• 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 10/482 for several batteries or cells simultaneously or sequentially
• CPC Class Codes: H01M 2220/20 : Batteries in motive systems, e.g. vehicle, ship, plane
• CPC Class Codes: H02J 7/00 : Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
• CPC Class Codes: Y02E 60/10 : Energy storage using batteries
• CPC Class Codes: Y02T 10/70 : Energy storage systems for electromobility, e.g. batteries

Abstract

A computer-implemented method for predicting a value of a cell parameter is provided, wherein the cell is one of a plurality of cells of a battery pack. The method includes determining which other different conditions of the cell and which similar and/or different conditions of any other cell of the plurality of cells correlate with the cell condition, determining values of one or more parameters from the same cell or any other cell of the plurality of cells that correspond to the determined conditions that correlate with the cell condition, and predicting the value of the cell parameter based on the determined values.

Claims

1. A method for predicting a value of an unmeasured parameter of a first cell of a battery pack using a battery management system (BMS) of the battery pack, the first cell being one of a plurality of cells of the battery pack, the method comprising:

identifying, using a processor of the BMS, a measured parameter of a second cell of the plurality of cells that is correlated with the unmeasured parameter of the first cell in a memory of the BCM;

determining, using a sensor of the battery pack that is operably coupled to the second cell and to the processor of the BMS, a value for the measured parameter of the second cell; and

predicting, using the processor of the BMS, the value of the unmeasured parameter of the first cell based at least in part on the determined value of the measure parameter of the second cell, wherein the unmeasured parameter of the first cell comprises an internal temperature, an external temperature, an internal pressure, a voltage, a current, or a lithium intercalation pressure of the first cell.

2. The method of claim 1, further comprising:

determining, using the processor of the BMS, a value of a parameter of the battery pack that is correlated with the the unmeasured parameter of the first cell in the memory of the BMS, wherein the processor of the BMS predicts the value of the unmeasured parameter of the first cell based at least in part on the determined value of the parameter of the battery pack.

3. The method of claim 1, wherein the first cell and the second cell of the plurality of cells are neighboring cells in the battery pack.

4. The method of claim 1, wherein the first cell and the second cell are separate and distinct cells of the plurality of cells of the battery pack.

5. The method of claim 1, comprising estimating, via the processor of the BMS, a state of charge of the first cell using the predicted value of the unmeasured parameter of the first cell.

16. The method of claim 1, wherein the unmeasured parameter of the first cell is the internal pressure or the lithium intercalation pressure.

17. The method of claim 5, comprising cell balancing, via the processor of the BMS, of the plurality of cells based at least in part on the estimated state of charge of the first cell.

18. The method of claim 5, comprising estimating, via the processor of the BMS, a state of charge of the battery pack based at least in part on the estimated state of charge of the first cell.

19. The method of claim 18, comprising outputting, via the processor of the BMS, the estimated state of charge of the battery pack to a vehicle control module (VCM) of an xEV, wherein the VCM determines when to charge and discharge the battery pack based at least in part on the estimated state of charge of the battery pack.

6. A battery management system (BMS) of a battery pack, comprising:

a processing unit and a memory unit for storing instructions that are operable, when executed by the processing unit, to perform a method for predicting a value of an unmeasured parameter of a first cell of a plurality of cells of the battery pack, the method comprising;

identifying, using the processing unit, a measured parameter of a second cell of the plurality of cells that is correlated with the unmeasured parameter of the first cell in the memory unit of the BMS;

determining, using a sensor of the battery pack that is operably coupled to the second cell and to the processing unit of the BMS, a value for the measured parameter of the second cell; and

predicting, using the processing unit of the BMS, the value of the unmeasured parameter of the first cell based at least in part on the determined value of the measure parameter of the second cell, wherein the unmeasured parameter of the first cell comprises an internal temperature, an external temperature, an internal pressure, a voltage, a current, or a lithium intercalation pressure of the first cell.

7. The BMS of claim 6, further comprising:

determining a value of a parameter of the battery pack that is correlated with the unmeasured parameter of the first cell in the memory unit of the BMS, wherein the processor of the BCM predicts the value of the unmeasured parameter of the first cell based at least in part on the determined value of the parameter of the battery pack.

8. The BMS of claim 6, wherein the first cell and the second cell of the plurality of cells are neighboring cells in the battery pack.

9. The BMS of claim 6, wherein the first cell and the second cell are separate and distinct cells of the plurality of cells of the battery pack.

10. The BMS of claim 6, wherein the method further comprises using the predicted value of the unmeasured parameter of the first cell to estimate the state of charge of the first cell.

11. A battery pack, comprising:

a first cell coupled with a corresponding sensing unit configured to measure a value of a parameter of the first cell;

a second cell that is not coupled with a sensing unit; and

a battery management system (BMS) coupled to each corresponding sensing unit coupled with the first cell, wherein the BMS includes a processor and a memory storing a prediction model that defines correlations between the parameters of the first cell and unmeasured parameters of the second cell, and wherein the processor is configured to use the prediction model to predict values for the unmeasured parameters of the second cell based at least in part on the measured values of the parameters of the first cell.

12. The battery pack of claim 11, wherein the prediction model defines correlations between measured parameters of the battery pack and the unmeasured parameters of the second cell, and wherein the processor is configured to use the prediction model to predict values for the unmeasured parameters of the second plurality of cells based at least in part on the measured parameters of the battery pack.

13. The battery pack of claim 11, wherein the BMS is configured to use the predicted values of the unmeasured parameters of the second cell to estimate a state of charge of the second cell.

14. The battery pack of claim 11, wherein the unmeasured parameters of the second cell comprise an internal temperature, an external temperature, an internal pressure, a voltage, a current, or a lithium intercalation pressure of the second cell.

15. The battery pack of claim 11, wherein the second cell is not coupled with the sensing units to minimize a cost of the battery pack.