Current Research Progress and Future Perspectives of Early Fire Prediction Modeling for Electric Vehicles

<div>With the wide application of electric vehicles (EVs) around the world, the increase in battery pack energy density and the growing complexity of electrical systems have gradually heightened the risk of vehicle fires. Therefore, achieving efficient and timely fire risk prediction is essential to minimize the probability of fires in EVs. However, the development of EV prediction models requires multidisciplinary integration to address complex safety challenges. This article provides a detailed discussion on the mechanisms and combustion characteristics of EV fires, followed by an investigation into the high-risk factors that trigger such fires. Based on the above content, this article conducts an in-depth analysis of the characteristics of different models for high-risk factors such as batteries, electrical systems, and collision damage, offering insights to bridge the gap between different disciplines. Finally, it explores the future development direction of predictive models for EVs. This review provides the reader a clear, systematic overview of EV combustion characteristics and early warning systems that can offer insights into the development of predictive models for EVs.</div>

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Publication Details

Journal
SAE International Journal of Electrified Vehicles
Published
2025-11-21
DOI
https://doi.org/10.4271/14-15-01-0001
Primary Topic
Fire dynamics and safety research
Type
article
Field-Weighted Citation Impact
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article

Current Research Progress and Future Perspectives of Early Fire Prediction Modeling for Electric Vehicles

Beihua Cong, Yuyang Shao, Liu Jianghong
SAE International Journal of Electrified Vehicles
Fire dynamics and safety research
article

Current Research Progress and Future Perspectives of Early Fire Prediction Modeling for Electric Vehicles

Beihua Cong, Yuyang Shao, Liu Jianghong
article en

Abstract

<div>With the wide application of electric vehicles (EVs) around the world, the increase in battery pack energy density and the growing complexity of electrical systems have gradually heightened the risk of vehicle fires. Therefore, achieving efficient and timely fire risk prediction is essential to minimize the probability of fires in EVs. However, the development of EV prediction models requires multidisciplinary integration to address complex safety challenges. This article provides a detailed discussion on the mechanisms and combustion characteristics of EV fires, followed by an investigation into the high-risk factors that trigger such fires. Based on the above content, this article conducts an in-depth analysis of the characteristics of different models for high-risk factors such as batteries, electrical systems, and collision damage, offering insights to bridge the gap between different disciplines. Finally, it explores the future development direction of predictive models for EVs. This review provides the reader a clear, systematic overview of EV combustion characteristics and early warning systems that can offer insights into the development of predictive models for EVs.</div>

SAE International Journal of Electrified VehiclesVol. 15(1)
Tongji University (CN), Shanghai Maritime University (CN)
Openalex Percentile: Top 56%
Fire dynamics and safety research
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