热失控
电池(电)
锂(药物)
锂离子电池
预警系统
计算机科学
核工程
工程类
电信
功率(物理)
量子力学
医学
物理
内分泌学
作者
Xi Zhang,Shun Chen,Jingzhe Zhu,Yizhao Gao
标识
DOI:10.34133/energymatadv.0008
摘要
Lithium-ion batteries are widely used in electric vehicles because of their high energy density and long cycle life. However, the spontaneous combustion accident of electric vehicles caused by thermal runaway of lithium-ion batteries seriously threatens passengers' personal and property safety. This paper expounds on the internal mechanism of lithium-ion battery thermal runaway through many previous studies and summarizes the proposed lithium-ion battery thermal runaway prediction and early warning methods. These methods can be classified into battery electrochemistry-based, battery big data analysis, and artificial intelligence methods. In this paper, various lithium-ion thermal runaway prediction and early warning methods are analyzed in detail, including the advantages and disadvantages of each method, and the challenges and future development directions of the intelligent lithium-ion battery thermal runaway prediction and early warning methods are discussed.
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