Research on a Fault Diagnosis Method of Power Battery for New Energy Vehicles

As the energy source of electric vehicles, the power battery system is the core component of electric vehicles. In recent years, the safety of the electric vehicle accidents caused by the power battery system have occurred frequently, and the power battery is affected by driving conditions, environmental conditions and other factors, and its failure is often difficult to diagnose quickly. Based on the real-vehicle operation data of new energy vehicles, the article establishes a predictive analysis model of power battery failure in electric vehicles, which can detect five kinds of failures (insulation failure, self-discharge abnormality, connection abnormality, sampling abnormality, and sudden-type internal short-circuit), in order to realize the diagnosis of battery failure.

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Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1109/ictc62082.2024.10827260
Primary Topic
Smart Grid and Power Systems
Type
article
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article

Research on a Fault Diagnosis Method of Power Battery for New Energy Vehicles

Yizhe Hu, Changhao Piao
Smart Grid and Power Systems
article

Research on a Fault Diagnosis Method of Power Battery for New Energy Vehicles

Yizhe Hu, Changhao Piao
article en

Abstract

As the energy source of electric vehicles, the power battery system is the core component of electric vehicles. In recent years, the safety of the electric vehicle accidents caused by the power battery system have occurred frequently, and the power battery is affected by driving conditions, environmental conditions and other factors, and its failure is often difficult to diagnose quickly. Based on the real-vehicle operation data of new energy vehicles, the article establishes a predictive analysis model of power battery failure in electric vehicles, which can detect five kinds of failures (insulation failure, self-discharge abnormality, connection abnormality, sampling abnormality, and sudden-type internal short-circuit), in order to realize the diagnosis of battery failure.

Chongqing University of Posts and Telecommunications (CN)
Affordable and clean energy
Openalex Percentile: Top 76%
Smart Grid and Power Systems
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