A study of data-driven fault diagnosis and early warning systems for power batteries in new energy vehicles

This study addresses the prevalent issues with new energy vehicle batteries, including failure and other complications. It focuses on lithium-ion batteries in pure electric vehicles and proposes a diagnostic approach based on SDO and NARX. The study also examines the methodology employed in fault judgement and early warning. The findings offer novel insights into the diagnosis of faults in new energy vehicles and provide technical guidance for ensuring the safe operation of these vehicles.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1145/3711129.3711342
Primary Topic
Advanced Battery Technologies Research
Type
article
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article

A study of data-driven fault diagnosis and early warning systems for power batteries in new energy vehicles

Xinqiang Ma, Meng Ling Yan, Qiang Li
Advanced Battery Technologies Research
article

A study of data-driven fault diagnosis and early warning systems for power batteries in new energy vehicles

Xinqiang Ma, Meng Ling Yan, Qiang Li
article en

Abstract

This study addresses the prevalent issues with new energy vehicle batteries, including failure and other complications. It focuses on lithium-ion batteries in pure electric vehicles and proposes a diagnostic approach based on SDO and NARX. The study also examines the methodology employed in fault judgement and early warning. The findings offer novel insights into the diagnosis of faults in new energy vehicles and provide technical guidance for ensuring the safe operation of these vehicles.

Chongqing University (CN), Chongqing University of Arts and Sciences (CN)
Affordable and clean energy
Openalex Percentile: Top 70%
Advanced Battery Technologies Research
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