Thermal Runaway Early Warning and Risk Estimation Based on Gas Production Characteristics of Different Types of Lithium-Ion Batteries

被引:21
作者
Cui, Yi [1 ]
Shi, Dong [1 ]
Wang, Zheng [2 ]
Mou, Lisha [3 ]
Ou, Mei [3 ]
Fan, Tianchi [3 ]
Bi, Shansong [1 ]
Zhang, Xiaohua [1 ]
Yu, Zhanglong [1 ]
Fang, Yanyan [1 ]
机构
[1] China Automot Battery Res Inst Co Ltd, 11 Xingke East St, Beijing 101407, Peoples R China
[2] Minist Ind & Informat Technol, Equipment Ind Dev Ctr, Beijing 100846, Peoples R China
[3] Chongqing Changan New Energy Vehicles Technol Co L, Chongqing 401135, Peoples R China
来源
BATTERIES-BASEL | 2023年 / 9卷 / 09期
关键词
lithium-ion battery safety; early warning sign; vent gas; thermal runaway degree; CATHODE MATERIALS; HIGH-POWER; FIRE; PROPAGATION; EXPLOSION; BEHAVIORS; EVOLUTION; FEATURES; FAILURE; CELLS;
D O I
10.3390/batteries9090438
中图分类号
O646 [电化学、电解、磁化学];
学科分类号
081704 ;
摘要
Gas production analysis during the thermal runaway (TR) process plays a crucial role in early fire accident detection in electric vehicles. To assess the TR behavior of lithium-ion batteries and perform early warning and risk estimation, gas production and analysis were conducted on LiNi(x)CoyMn(1-x-y)O(2)/graphite and LiFePO4/graphite cells under various trigger conditions. The findings indicate that the unique gas signals can provide TR warnings earlier than temperature, voltage, and pressure signals, with an advanced warning time ranging from 16 to 26 min. A new parameter called the thermal runaway degree (TRD) is introduced, which is the product of the molar quantity of gas production and the square root of the maximum temperature during the TR process. TRD is proposed to evaluate the severity of TR. The research reveals that TRD is influenced by the energy density of cells and the trigger conditions of TR. This parameter allows for a quantitative assessment of the safety risk associated with different battery types and the level of harm caused by various abuse conditions. Despite the uncertainties in the TR process, TRD demonstrates good repeatability (maximum relative deviation < 5%) and can be utilized as a characteristic parameter for risk estimation in lithium-ion batteries.
引用
收藏
页数:14
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