Battery internal state estimating apparatus and battery internal state estimating method

• US 9,678,164 B2
• Filed: 11/12/2010
• Issued: 06/13/2017
• Est. Priority Date: 03/23/2010
• Status: Active Grant

• Current Assignee: Furukawa Automotive Systems Incorporated (Furukawa Electric Company Limited), Furukawa Electric Company Limited
• Original Assignee: Furukawa Automotive Systems Incorporated (Furukawa Electric Company Limited), Furukawa Electric Company Limited
• Inventors: Sato, Etsuzo, Mitsuyama, Taiji, Kovats, Antal, Sugimura, Takezo
• Primary Examiner(s): Breene, John
• Assistant Examiner(s): Bermudez, Yaritza H Perez
• Application Number:
  US13/636,653
• Publication Number:
  US 20130110429A1
• Time in Patent Office: 2,405 Days
• Field of Search: 702 63
• 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 31/392 Determining battery ageing or deterioration, e.g. state of health
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: H01M 10/06 Lead-acid accumulators semi-lead accumulators H01M10/20
• 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: Y02E 60/10 Energy storage using batteries

Abstract

To learn a parameter of a simulation model of a battery efficiently. A battery internal state estimating apparatus, estimating an internal state of a battery based on a simulation model of the battery, includes a storing section (RAM10c) that stores a plurality of parameters of the simulation model, a detecting section (I/F10d) that detects a discharge current flowing from the battery to a load, a selecting section (CPU 10a) that selects a parameter to be subjected to adaptive learning based on a value of the discharge current detected by the detecting section, and an adaptive learning section (CPU 10a) that performs adapting learning on a parameter selected by the selecting section.

Claims

1. A battery internal state estimating apparatus that detects a discharge current flowing from a battery to a load including at least an electric motor for starting up an engine and estimates an internal state of the battery based on an equivalent circuit model of the battery as applied on the discharge current, comprising:

a memory that stores computer executable instructions corresponding to implementation of the equivalent circuit model comprising a resistance element corresponding to an internal resistance of the battery, the resistance element having a resistance value variable on specification of an inputted parameter;

a storing section that stores a plurality of parameters of the equivalent circuit model;

a physical detecting section that detects the discharge current flowing from the battery to the load, wherein the load includes at least an electric motor for starting up an engine;

a selecting section that selects a parameter indicating a resistance value of the resistance element to be subjected to adaptive learning based on a value of the discharge current detected by the detecting section, wherein the selecting section selects the parameter indicating the resistance value of the resistance element when a peak current which flows at a start-up of the electric motor is detected by the detection section;

an adaptive learning section that performs adaptive learning on the parameter indicating the resistance value of the resistance element selected by the selecting section;

updating the resistance value of the resistance element of the circuit model, wherein the resistance value of the resistance element is updated in accordance with the adaptive learning and wherein the internal state of the battery is estimated based at least partly on the updated resistance value of the resistance element; and

initiating transmission of a signal indicative of the updated resistance value, wherein the signal is used to update the resistance value of the battery.

2. The battery internal state estimating apparatus according to claim 1, wherein the equivalent circuit model has at least a constant phase element (CPE) which is an equivalent circuit of a cathode and an anode of the battery, the constant phase element being represented by an equivalent circuit in which a plurality of RC parallel units are connected in series,

wherein each RC parallel unit includes a resistance and a capacitor connected in parallel, an element value of each of the resistance and the capacitor constituting each RC parallel unit being taken as a parameter of the plurality of parameters,

wherein the selecting section selects a predetermined RC parallel unit that has been determined in advance in accordance with the value of the discharge current;

and

the adaptive learning selection performs adaptive learning of the element value of each of the resistance and the capacitor which is selected by the selecting section.

3. The battery internal state estimating apparatus according to claim 1, wherein the parameter selected by the selecting section constitutes a state vector of an extended Kalman filter;

and

wherein the adaptive learning selection performs the adaptive learning on the state vector.

4. The battery internal state estimating apparatus according to claim 1, wherein the storing section comprises random access memory (RAM).

5. The battery internal state estimating apparatus according to claim 1, wherein the physical detecting section comprises a current detecting sensor.

6. The battery internal state estimating apparatus according to claim 1, wherein the selecting section and the adaptive learning section comprises computer executable instructions executed on a computer processing unit (CPU).

7. A battery internal state estimating apparatus that detects a discharge current flowing from a battery to a load including at least an electric motor for starting up an engine and estimates an internal state of the battery based on an equivalent circuit model of the battery as applied on the discharge current, comprising:

a memory that stores computer executable instructions corresponding to implementation of the equivalent circuit model comprising a voltage source having a corresponding voltage, wherein the voltage of the voltage source is dynamically adjusted based on a concentration value of an electrolyte;

a storing section that stores a plurality of parameters of the equivalent circuit model;

a physical detecting section that detects the discharge current flowing from the battery to the load, wherein the load includes at least an electric motor for starting up an engine and wherein the detecting section detects the discharge current at a start-up of the engine by the electric motor;

a selecting section that selects a parameter indicating the concentration value of the electrolyte to be subjected to adaptive learning based on the discharge current detected by the detecting section, wherein the discharge current detected is substantially zero;

an adaptive learning section that performs adaptive learning on the parameter indicating the concentration value of the electrolyte selected by the selecting section, and

updating the resistance value of the resistance element of the circuit model, wherein the voltage of the voltage source is updated in accordance with the adaptive learning and wherein the internal state of the battery is estimated based at least partly on the updated voltage of the voltage source, and

initiating transmission of a signal indicative of the updated resistance value, wherein the signal is used to update the resistance value of the battery.

8. The battery internal state estimating apparatus according to claim 7, wherein the equivalent circuit model has at least a constant phase element (CPE) which is an equivalent circuit of a cathode and an anode of the battery, the constant phase element being represented by an equivalent circuit in which a plurality of RC parallel units are connected in series,

wherein each RC parallel unit includes a resistance and a capacitor connected in parallel, an element value of each of the resistance and the capacitor constituting each RC parallel unit being taken as a parameter of the plurality of parameters,

wherein the selecting section selects a predetermined RC parallel unit that has been determined in advance in accordance with the value of the discharge current;

and

the adaptive learning selection performs adaptive learning of the element value of each of the resistance and the capacitor which is selected by the selecting section.

9. The battery internal state estimating apparatus according to claim 7, wherein the parameter selected by the adaptive learning section constitutes a state vector of an extended Kalman filter;

and

wherein the adaptive learning selection performs the adaptive learning on the state vector.

10. The battery internal state estimating apparatus according to claim 7, wherein the storing section comprises random access memory (RAM).

11. The battery internal state estimating apparatus according to claim 7, wherein the physical detecting section comprises a current detecting sensor.

12. The battery internal state estimating apparatus according to claim 7, wherein the selecting section and the adaptive learning section comprises computer executable instructions executed on a computer processing unit (CPU).

13. A battery internal state estimating apparatus for measuring a terminal voltage, a discharge current, and an internal resistance of a battery and estimating an internal state of the battery based on an equivalent circuit model of the battery applied on the terminal voltage, the discharge current, and the internal resistance, comprising:

a memory that stores computer executable instructions corresponding to implementation of the equivalent circuit model comprising an internal resistance of an electric circuit, the internal resistance having a variable resistance value dynamically adjusted based on an inputted parameter;

a storing section that stores a plurality of parameters of the equivalent circuit model;

a physical measuring section that measures the terminal voltage and the discharge current of the battery at a predetermined cycle;

an adaptive learning section that performs adaptive learning on the parameters in accordance with the equivalent circuit model based at least partly on a measurement result of the measuring section;

an actual measurement section that performs actual measurement of the internal resistance of the battery;

an estimating section that estimates an SOH (State of Health) indicating a degradation state of the battery based on an actual measured value R_meas of the internal resistance of the battery obtained by the actual measurement section and a value of the at least one parameter obtained by the adaptive learning selection or a corrected value of the parameter, wherein the estimating section estimates the degradation state based on the corrected value of the parameter, the corrected value of the parameter being a value obtained by multiplying a parameter R0 indicating the internal resistance of the electric circuit by a parameter η

indicating an aging of the internal resistance of the electric circuit, and correcting the value obtained by the multiplication based on an average current I_avrg flowing through the load and a stable open circuit voltage; and

initiating transmission of a signal indicative of the corrected value of the parameter, wherein the signal is used to update the resistance value of the battery.

14. The battery internal state estimating apparatus according to claim 13, wherein the storing section comprises random access memory (RAM).

15. The battery internal state estimating apparatus according to claim 13, wherein the physical detecting section comprises a current detecting sensor.

16. The battery internal state estimating apparatus according to claim 13, wherein the selecting section and the adaptive learning section comprises computer executable instructions executed on a computer processing unit (CPU).

17. A battery internal state estimating apparatus for measuring a terminal voltage, a discharge current, and an internal resistance of a battery and estimating an internal state of the battery based on an equivalent circuit model of the battery applied on the terminal voltage, the discharge current, and the internal resistance, comprising:

a memory that stores computer executable instructions corresponding to implementation of the equivalent circuit model comprising an internal resistance of an electric circuit, the internal resistance having a variable resistance value dynamically adjusted based on an inputted parameter;

a storing section that stores a plurality of parameters of the equivalent circuit model;

a physical measuring section that measures the terminal voltage and the discharge current of the battery at a predetermined cycle;

an adaptive learning section that performs adaptive learning on the parameters in accordance with the equivalent circuit model based at least partly on a measurement result of the measuring section;

an actual measurement section that performs actual measurement of the internal resistance of the battery;

an estimating section that estimates an SOH (State of Health) indicating a degradation state of the battery based on an actual measured value R_meas of the internal resistance of the battery obtained by the actual measurement section and a value of at least one parameter obtained by the adaptive learning selection or a corrected value of the parameter, wherein the estimating section estimates the degradation state based on the correction value of the parameter, the correction value of the parameter being a value obtained by multiplying parameter R0 indicating the internal resistance of the electric circuit by a parameter η

indicating an aging of the internal resistance of the electric circuit, correcting the value obtained by the multiplication based on an average current I_avrg flowing through the load and a stable open circuit voltage, and further correcting the corrected value based on an SOC (State of Charge) indicating a state of charge of the battery, an average voltage V_avrg of the battery while the current is flowing through the load, and a voltage V_start of the battery at a state before the current flows through the load; and

initiating transmission of a signal indicative of the corrected value of the parameter, wherein the signal is used to update the resistance value of the battery.

18. The battery internal state estimating apparatus according to claim 17, wherein the storing section comprises random access memory (RAM).

19. The battery internal state estimating apparatus according to claim 17, wherein the physical detecting section comprises a current detecting sensor.

20. The battery internal state estimating apparatus according to claim 17, wherein the selecting section and the adaptive learning section comprises computer executable instructions executed on a computer processing unit (CPU).