Short Circuit and Connection Fault Diagnosis for Lithium-ion Battery Pack Based on Differential Voltage Changes and Independent Component Analysis

In order to avoid thermal runaway as well as ensure safe and stable operation of battery system, it is vital to perform rapid and accurate diagnosis for early faults with similar characteristics. In this paper, a short circuit and connection fault diagnosis method that is applicable to traditional one-to-one voltage sensor topology is proposed based on differential voltage changes (DVCs) and independent component analysis. Voltage measurements is pretreated to obtain DVCs for extracting fault signature and reducing the detrimental effects of inconsistency, interference, etc. to a certain extent. Independent component analysis is combined with the DVC vector to establish diagnostic model and diagnose faults online. Fault detection and isolation is achieved using squared prediction error, and considering that traditional contributions cannot accurately determine fault location, an improved contribution calculation is introduced to localize the faulty cell. Experimental verifications show that the proposed method can timely detect and localize faults, meanwhile it can distinguish short circuit with connection fault.

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Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/epee63731.2024.10875399
Primary Topic
Advanced Algorithms and Applications
Type
article
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article

Short Circuit and Connection Fault Diagnosis for Lithium-ion Battery Pack Based on Differential Voltage Changes and Independent Component Analysis

Hanxiao Liu, Li Yang, Luan Zhang, Liwei Li
Advanced Algorithms and Applications
article

Short Circuit and Connection Fault Diagnosis for Lithium-ion Battery Pack Based on Differential Voltage Changes and Independent Component Analysis

Hanxiao Liu, Li Yang, Luan Zhang, Liwei Li
article en

Abstract

In order to avoid thermal runaway as well as ensure safe and stable operation of battery system, it is vital to perform rapid and accurate diagnosis for early faults with similar characteristics. In this paper, a short circuit and connection fault diagnosis method that is applicable to traditional one-to-one voltage sensor topology is proposed based on differential voltage changes (DVCs) and independent component analysis. Voltage measurements is pretreated to obtain DVCs for extracting fault signature and reducing the detrimental effects of inconsistency, interference, etc. to a certain extent. Independent component analysis is combined with the DVC vector to establish diagnostic model and diagnose faults online. Fault detection and isolation is achieved using squared prediction error, and considering that traditional contributions cannot accurately determine fault location, an improved contribution calculation is introduced to localize the faulty cell. Experimental verifications show that the proposed method can timely detect and localize faults, meanwhile it can distinguish short circuit with connection fault.

Shandong University (CN), Shanghai Electric (China) (CN), Shandong University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 66%
Advanced Algorithms and Applications
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