Method and apparatus for identifying abnormal battery cell, electronic device, and storage medium

Patent metadata

Field	Value
Publication number	US-12540983-B2
Application number	US-202418595117-A
Country	US
Kind code	B2
Filing date	Mar 4, 2024
Priority date	Apr 19, 2022
Publication date	Feb 3, 2026
Grant date	Feb 3, 2026

Abstract

A method for identifying abnormal battery cell includes determining, based on target feature data of a battery cell, whether the battery cell is an abnormal battery cell. The target feature data includes feature data used for differentiation between an abnormal battery cell and a normal battery cell generated during a formation process.

First claim

What is claimed is:

1 . A method for identifying abnormal battery cell, comprising:
determining, based on target feature data of a battery cell, whether the battery cell is an abnormal battery cell; and in response to the determining that the battery cell is abnormal, marking the battery cell as abnormal for removal from subsequent production, wherein:
the target feature data comprises feature data used for differentiation between an abnormal battery cell and a normal battery cell generated during a formation process, the target feature data comprises a first target parameter value corresponding to a first arrival of a variation of a target parameter at a first process variation and a second target parameter value corresponding to a first arrival of the variation of the target parameter at a second process variation, the first process variation and the second process variation are different, the target parameter is selected from film-forming peak (dQ/dV), dynamic internal resistance (V/I), or dV/dQ, the first arrival of the variation of the target parameter at the first or second process variation corresponds to an earliest occurrence during a first stage of the formation process at which a difference between two consecutive sampling points of the target parameter equals the first or second process variation, respectively, the first or second target parameter value is obtained from the sampling points associated with the first arrival of the variation of the target parameter at the first or second process variation, respectively; and
determining, based on the target feature data of the battery cell, whether the battery cell is an abnormal battery cell comprises:
inputting the first and second target parameter values into a two-dimensional Gaussian distribution model constructed from sample battery cells to obtain an identification result of whether the battery cell is an abnormal battery cell, the obtaining the identification result comprising calculating a probability density of the battery cell; and
in response at least to the probability density being less than a preset probability density threshold, determining that the battery cell is an abnormal battery cell.

2 . The method for identifying abnormal battery cell according to claim 1 , wherein the target feature data comprises feature data influenced by electrolyte in the battery cell generated during the formation process.

3 . The method for identifying abnormal battery cell according to claim 1 , wherein the target feature data comprises feature data influenced by water content in the battery cell generated during the formation process.

4 . The method for identifying abnormal battery cell according to claim 1 , wherein determining, based on the target feature data of the battery cell, whether the battery cell is an abnormal battery cell comprises:
determining, during the formation process of the battery cell based on the target feature data of the battery cell, whether the battery cell is an abnormal battery cell.

5 . An electronic device, comprising a processor and a memory; wherein
the processor is configured to execute one or more instructions stored in the memory to implement the method for identifying abnormal battery cell according to claim 1 .

6 . A non-transitory computer-readable storage medium storing one or more instructions, the instructions being executable by a processor to implement the method for identifying abnormal battery cell according to claim 1 .

7 . An apparatus for identifying battery cell with electrolyte abnormalities, comprising:
a processor; and a memory coupled to the processor, the memory storing instructions which, when executed the processor, cause the processor to: determine, based on target feature data of a battery cell, whether the battery cell is an abnormal battery cell; and in response to the determining that the battery cell is abnormal, mark the battery cell as abnormal for removal from subsequent production, wherein:
the target feature data comprises feature data used for differentiation between an abnormal battery cell and a normal battery cell generated during a formation process, the target feature data comprises a first target parameter value corresponding to a first arrival of a variation of a target parameter at a first process variation and a second target parameter value corresponding to a first arrival of the variation of the target parameter at a second process variation, the first process variation and the second process variation are different, the target parameter is selected from film-forming peak (dQ/dV), dynamic internal resistance (V/I), or dV/dQ, the first arrival of the variation of the target parameter at the first or second process variation corresponds to an earliest occurrence during a first stage of the formation process at which a difference between two consecutive sampling points of the target parameter equals the first or second process variation, respectively, the first or second target parameter value is obtained from the sampling points associated with the first arrival of the variation of the target parameter at the first or second process variation, respectively; and
determining, based on the target feature data of the battery cell, whether the battery cell is an abnormal battery cell comprises:
inputting the first and second target parameter values into a two-dimensional Gaussian distribution model constructed from sample battery cells to obtain an identification result of whether the battery cell is an abnormal battery cell, the obtaining the identification result comprising calculating a probability density of the battery cell; and
in response to the probability density being less than a preset probability density threshold and the target feature data being within a preset feature range, determining that the battery cell is an abnormal battery cell.

Assignees

• Contemporary Amperex Technology Hong Kong Ltd

Inventors

• Fan Xiaoyun
• Sun Jianan
• Lin Deming
• Wu Jingliang

Classifications

• G01R31/367

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

• G01R31/3865 Primary

  related to manufacture, e.g. testing after manufacture · CPC title

• G01R31/385

  Arrangements for measuring battery or accumulator variables (for monitoring G01R31/382) · CPC title

• G01R27/02

  Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant (by measuring phase angle only G01R25/00) · CPC title

• H01M10/04

  Construction or manufacture in general (H01M10/058, H01M10/12, H01M10/28, H01M10/38 take precedence) · CPC title