Method and apparatus with battery state estimation

Patent metadata

Field	Value
Publication number	US-11828807-B2
Application number	US-202117328246-A
Country	US
Kind code	B2
Filing date	May 24, 2021
Priority date	Sep 1, 2020
Publication date	Nov 28, 2023
Grant date	Nov 28, 2023

Abstract

A processor-implemented method with battery state estimation includes estimating a current state of charge (SOC) of a target battery by correcting a first electrochemical model corresponding to the target battery using a first voltage difference between a measured voltage of the target battery and an estimated voltage of the target battery that is estimated by the first electrochemical model, estimating an end SOC of the target battery by correcting a second electrochemical model using a second voltage difference between an estimated voltage of a virtual battery that is estimated by the second electrochemical model and a preset voltage, and estimating a relative SOC (RSOC) of the target battery based on the current SOC and the end SOC of the target battery, wherein the second electrochemical model is based on the virtual battery corresponding to the target battery being discharged to reach the preset voltage.

First claim

What is claimed is:

1. A processor-implemented method for battery state estimation, comprising:
correcting a first electrochemical model corresponding to a target battery using a first voltage difference between a measured voltage of the target battery and an estimated voltage of the target battery that is estimated by the first electrochemical model;
estimating, using the corrected first electrochemical model, a current state of charge (SOC) of the target battery;
correcting a second electrochemical model using a second voltage difference between an estimated voltage of a virtual battery that is estimated by the second electrochemical model and a preset voltage;
estimating, using the corrected second electrochemical model, an end SOC of the target battery; and
estimating a relative SOC (RSOC) of the target battery based on the current SOC and the end SOC of the target battery,
wherein the second electrochemical model is based on the virtual battery corresponding to the target battery being discharged to reach the preset voltage.

2. The method of claim 1 , wherein the estimating of the end SOC comprises:
estimating a current SOC of the virtual battery using the second electrochemical model updated, in response to the estimated voltage of the virtual battery corresponding to the preset voltage; and
determining the current SOC of the virtual battery to be the end SOC of the target battery.

3. The method of claim 1 , wherein the first electrochemical model and the second electrochemical model have a same physical property parameter and different internal state information.

4. The method of claim 1 , wherein the end SOC is an SOC obtained as the target battery is discharged by a current output from the target battery and reaches the preset voltage.

5. The method of claim 1 , wherein the estimating of the end SOC comprises:
determining a state variation of the virtual battery using the second voltage difference;
updating an internal state of the second electrochemical model based on the determined state variation of the virtual battery; and
estimating state information of the virtual battery based on the updated internal state of the second electrochemical model.

6. The method of claim 5 , wherein the state variation of the virtual battery is based on the second voltage difference, previous state information estimated by the second electrochemical model, and an open-circuit voltage (OCV) table.

7. The method of claim 6 , wherein the state variation of the virtual battery is determined by obtaining an OCV corresponding to the previous state information based on the OCV table, and applying the second voltage difference to the obtained OCV.

8. The method of claim 5 , wherein the internal state of the second electrochemical model is updated by correcting an ion concentration distribution in an active material particle or an ion concentration distribution in an electrode based on the state variation of the virtual battery.

9. The method of claim 5 , wherein the internal state of the second electrochemical model comprises at least one of a positive electrode lithium ion concentration distribution, a negative electrode lithium ion concentration distribution, or an electrolyte lithium ion concentration distribution of the virtual battery.

10. The method of claim 1 , wherein the estimating of the RSOC comprises:
estimating the RSOC based on one of the current SOC and the end SOC that is estimated in a current period, and the other one of the current SOC and an end SOC estimated in a previous period.

11. The method of claim 1 , wherein the estimating of the end SOC is performed after the estimating of the current SOC is performed for a number of times.

12. The method of claim 1 , wherein:
the target battery comprises a plurality of batteries;
the estimating of the current SOC is performed on each of the plurality of batteries, and the estimating of the end SOC is performed on a representative battery from among the plurality of batteries,
wherein the estimating of the RSOC comprises:
estimating an RSOC of each of the plurality of batteries based on a current SOC estimated from each of the plurality of batteries and an end SOC estimated from the representative battery.

13. The method of claim 1 , wherein the estimating of the end SOC comprises:
estimating a plurality of end SOCs using a plurality of virtual batteries indicating a virtual situation that the target battery is discharged by different currents to reach the preset voltage,
wherein the estimating of the RSOC comprises:
estimating a plurality of RSOCs of the target battery based on the current SOC of the target battery and the estimated end SOCs.

14. The method of claim 1 , wherein the preset voltage is an end-of-discharge voltage (EDV) of the target battery.

15. The method of claim 1 , wherein the target battery is a battery cell, a battery module, or a battery pack.

16. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform the method of claim 1 .

17. An apparatus with battery state estimation, comprising:
a memory configured to store a first electrochemical model corresponding to a target battery and a second electrochemical model based on a virtual battery corresponding to the target battery being discharged to reach a preset voltage; and
a processor configured to:
correct the first electrochemical model using a voltage difference between a measured voltage of a target battery and an estimated voltage of the target battery that is estimated by the first electrochemical model;
estimate, using the corrected first electrochemical model, a current state of charge (SOC) of the target battery;
correct the second electrochemical model using a voltage difference between an estimated voltage of the virtual battery that is estimated by the second electrochemical model and the preset voltage;
estimate, using the corrected second electrochemical model, an end SOC of the target battery by correcting and
estimate the RSOC of the target battery based on the current SOC and the end SOC of the target battery.

18. A processor-implemented method for battery state estimation, comprising:
determining a state variation of a virtual battery corresponding to a target battery that is discharged to reach a preset voltage, using a voltage difference between an estimated voltage that is estimated by an electrochemical model corresponding to the virtual battery and a preset voltage;
updating an internal state of the electrochemical model based on the determined state variation of the virtual battery; and
estimating, using the updated internal state of the electrochemical model, an end state of charge (SOC) of the target battery by estimating state information of the virtual battery.

19. The method of claim 18 , wherein the determining of the state variation of the virtual battery comprises:
determining the state variation of the virtual battery based on the voltage difference, previous state information estimated by the electrochemical model, and an open-circuit voltage (OCV) table.

20. The method of claim 18 , wherein the updating of the internal state of the electrochemical model comprises:
updating the internal state of the electrochemical model by correcting an ion concentration distribution in an active material particle or an ion concentration distribution in an electrode based on the state variation of the virtual battery.

Assignees

• Samsung Electronics Co Ltd

Inventors

• Kim Jinho
• Song Tae Won
• Sung Young Hun

Classifications

• H02J7/82

  Control of state of charge [SOC] · CPC title

• G01R31/3835

  involving only voltage measurements · CPC title

• G01R31/367 Primary

  Software therefor, e.g. for battery testing using modelling or look-up tables · CPC title

• H02J7/0048

  Electricity · mapped topic

• G01R31/388

  involving voltage measurements · CPC title