A Review of Lithium-Ion Battery Thermal Runaway Modeling and Diagnosis Approaches

被引:134
作者
Tran, Manh-Kien [1 ]
Mevawalla, Anosh [1 ]
Aziz, Attar [1 ]
Panchal, Satyam [2 ]
Xie, Yi [3 ]
Fowler, Michael [1 ]
机构
[1] Univ Waterloo, Dept Chem Engn, 200 Ave West, University, ON N2L 3G1, Canada
[2] Univ Waterloo, Dept Mech & Mechatron Engn, 200 Ave West, University, ON N2L 3G1, Canada
[3] Chongqing Univ, Coll Mech & Vehicle Engn, Chongqing 400044, Peoples R China
关键词
lithium-ion battery; thermal runaway; battery modeling; fault diagnosis; internal short-circuit; INTERNAL SHORT-CIRCUIT; ELECTRIC VEHICLES; FAULT-DIAGNOSIS; TEMPERATURE; PROPAGATION; CELL; PREDICTION; BEHAVIOR; FAILURE; PACK;
D O I
10.3390/pr10061192
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Lithium-ion (Li-ion) batteries have been utilized increasingly in recent years in various applications, such as electric vehicles (EVs), electronics, and large energy storage systems due to their long lifespan, high energy density, and high-power density, among other qualities. However, there can be faults that occur internally or externally that affect battery performance which can potentially lead to serious safety concerns, such as thermal runaway. Thermal runaway is a major challenge in the Li-ion battery field due to its uncontrollable and irreversible nature, which can lead to fires and explosions, threatening the safety of the public. Therefore, thermal runaway prognosis and diagnosis are significant topics of research. To efficiently study and develop thermal runaway prognosis and diagnosis algorithms, thermal runaway modeling is also important. Li-ion battery thermal runaway modeling, prediction, and detection can help in the development of prevention and mitigation approaches to ensure the safety of the battery system. This paper provides a comprehensive review of Li-ion battery thermal runaway modeling. Various prognostic and diagnostic approaches for thermal runaway are also discussed.
引用
收藏
页数:18
相关论文
共 75 条
[21]   Fault Prognosis and Isolation of Lithium-Ion Batteries in Electric Vehicles Considering Real-Scenario Thermal Runaway Risks [J].
Hong, Jichao ;
Wang, Zhenpo ;
Qu, Changhui ;
Ma, Fei ;
Xu, Xiaoming ;
Yang, Jue ;
Zhang, Jinghan ;
Zhou, Yangjie ;
Shan, Tongxin ;
Hou, Yankai .
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS, 2023, 11 (01) :88-99
[22]   Thermal Runaway Prognosis of Battery Systems Using the Modified Multiscale Entropy in Real-World Electric Vehicles [J].
Hong, Jichao ;
Wang, Zhenpo ;
Ma, Fei ;
Yang, Jue ;
Xu, Xiaoming ;
Qu, Changhui ;
Zhang, Jinghan ;
Shan, Tongxin ;
Hou, Yankai ;
Zhou, Yangjie .
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2021, 7 (04) :2269-2278
[23]   Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks [J].
Hong, Jichao ;
Wang, Zhenpo ;
Yao, Yongtao .
APPLIED ENERGY, 2019, 251
[24]   A review of the internal short circuit mechanism in lithium-ion batteries: Inducement, detection and prevention [J].
Huang, Lili ;
Liu, Lishuo ;
Lu, Languang ;
Feng, Xuning ;
Han, Xuebing ;
Li, Weihan ;
Zhang, Mingxuan ;
Li, Desheng ;
Liu, Xiaobin ;
Sauer, Dirk Uwe ;
Ouyang, Minggao .
INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2021, 45 (11) :15797-15831
[25]   Experimental and modeling analysis of thermal runaway propagation over the large format energy storage battery module with Li4Ti5O12 anode [J].
Huang, Peifeng ;
Ping, Ping ;
Li, Ke ;
Chen, Haodong ;
Wang, Qingsong ;
Wen, Jennifer ;
Sun, Jinhua .
APPLIED ENERGY, 2016, 183 :659-673
[26]  
IEA, 2021, GLOBAL EV OUTLOOK 20, P101, DOI DOI 10.1787/D394399--EN
[27]   A Hybrid Signal-Based Fault Diagnosis Method for Lithium-Ion Batteries in Electric Vehicles [J].
Jiang, Jiuchun ;
Cong, Xinwei ;
Li, Shuowei ;
Zhang, Caiping ;
Zhang, Weige ;
Jiang, Yan .
IEEE ACCESS, 2021, 9 :19175-19186
[28]   Data-driven fault diagnosis and thermal runaway warning for battery packs using real-world vehicle data [J].
Jiang, Lulu ;
Deng, Zhongwei ;
Tang, Xiaolin ;
Hu, Lin ;
Lin, Xianke ;
Hu, Xiaosong .
ENERGY, 2021, 234
[29]   Rapid prediction method for thermal runaway propagation in battery pack based on lumped thermal resistance network and electric circuit analogy [J].
Jiang, Z. Y. ;
Qu, Z. G. ;
Zhang, J. F. ;
Rao, Z. H. .
APPLIED ENERGY, 2020, 268 (268)
[30]   Comparison of Model-Based and Sensor-Based Detection of Thermal Runaway in Li-Ion Battery Modules for Automotive Application [J].
Klink, Jacob ;
Hebenbrock, Andre ;
Grabow, Jens ;
Orazov, Nury ;
Nylen, Ulf ;
Benger, Ralf ;
Beck, Hans-Peter .
BATTERIES-BASEL, 2022, 8 (04)