A battery cell internal short circuit detection method, device, storage medium and equipment

CN117031337BActive Publication Date: 2026-07-21GAC AION NEW ENERGY AUTOMOBILE CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
GAC AION NEW ENERGY AUTOMOBILE CO LTD
Filing Date
2023-08-10
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing methods for detecting short circuits within batteries are prone to diagnostic delays, and the accuracy of the results cannot meet requirements.

Method used

A dual-model interactive verification method is adopted. The first model identifies suspected internally short-circuited cells based on the peak area of ​​the cell's capacity increment curve and charging time. The second model further confirms the internally short-circuited cells by comparing the peak area of ​​the capacity increment curves of the actual cell and the reference cell, and generates internal short-circuit warning information.

Benefits of technology

This improves the accuracy of internal short circuit detection results, reduces the risk of diagnostic delays, enables precise internal short circuit warnings, and ensures vehicle safety.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN117031337B_ABST
    Figure CN117031337B_ABST
Patent Text Reader

Abstract

The application provides a kind of electric core internal short circuit detection method, device, storage medium and equipment, in the method, by the first model, according to the highest peak area of the capacity increment curve of each electric core, and the charging time of each electric core charging to the highest peak, judge the electric core that appears internal short circuit and is classified into the first candidate internal short circuit electric core, by the second model, compare the highest peak area of the capacity increment curve of each electric core with the highest peak area of the capacity increment curve of reference electric core, judge the electric core that appears internal short circuit and is classified into the second candidate internal short circuit electric core, then, according to the first candidate internal short circuit electric core group and the second candidate internal short circuit electric core group, determine internal short circuit electric core, and generate internal short circuit early warning information. In this way, the result precision of electric core internal short circuit detection is effectively improved by using the mode of double model interaction verification, the risk of diagnosis delay is reduced, and accurate internal short circuit early warning is realized.
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