跳到主要导航 跳到搜索 跳到主要内容

Thermal runaway feature extraction and risk prediction in electric vehicle battery packs under high-temperature

  • Haixu Yang
  • , Peng Liu*
  • , Saihan Chen
  • , Qing Wang
  • , Yipeng He
  • , Zhaosheng Zhang
  • *此作品的通讯作者
  • Beijing Institute of Technology
  • State Administration for Market Regulation

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

Thermal runaway is a critical issue constraining the development of batteries and electric vehicles. Hot weather, high-power operation, and fast charging can easily cause battery temperatures to rise, intensifying internal reactions and reducing stability. Investigating battery thermal runaway solely at room temperature fails to meet safety requirements. This study focuses on the thermal runaway behavior of battery packs under high-temperature conditions. By triggering a short circuit within the battery pack via needle penetration, temperature and voltage characteristic data during thermal runaway are obtained. Based on this data, a three-level thermal runaway warning strategy is established. Based on the evolution of characteristic data, the propagation path within the pack is identified to guide structural design. Using dynamic time warping, similarity calculations are performed between electric vehicle battery operational data and thermal runaway characteristic voltage data. Highly similar real-world vehicle data is deemed to pose safety risks. Comparisons between computational results for accident vehicles and normal vehicles demonstrate the feasibility of this approach. Under the combined effects of high temperature, pressure, and ejected particles, arc breakdown is a common phenomenon during thermal runaway in battery packs. Electrical simulation studies are conducted on three-dimensional models of the pack, quantifying the electric field strength under various conditions and assessing the hazards associated with arc breakdown. This study proposes a thermal runaway containment method from a structural and data-driven perspective, which can provide guidance for battery pack safety design. The achievement can reduce the public's concern about the safety of electric vehicles, increase the utilization rate of electric vehicles, and contribute to zero-carbon transportation.

源语言英语
期刊论文编号108782
期刊Process Safety and Environmental Protection
卷211
DOI
出版状态已出版 - 1 5月 2026
已对外发布是

学术指纹

探究 'Thermal runaway feature extraction and risk prediction in electric vehicle battery packs under high-temperature' 的科研主题。它们共同构成独一无二的学术指纹。

引用此

Baidu
map