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Thermal runaway modeling of large format high-nickel/silicon-graphite lithium-ion batteries based on reaction sequence and kinetics

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  • Wang, Yu
  • Ren, Dongsheng
  • Feng, Xuning
  • Wang, Li
  • Ouyang, Minggao

Abstract

Commercial large format high-nickel/silicon-graphite (NCM811/SiC) lithium-ion batteries have been applied in long range electric vehicles for their exceptional high energy density. However, fire and explosions caused by these high-energy batteries arouse safety concerns. Mathematical model is a powerful method to study and predict the hazardous thermal behaviors but have not been well established due to lack of the detailed side reaction sequence and kinetics of the NCM811/SiC chemistry. This paper reveals that the thermal interactions between the high energy materials dominate the heat generation process and determines the detailed side reaction sequence and thermal kinetics based on experiments. A cell thermal runaway model considering the reaction sequence is then established based on the kinetics and achieves accurate prediction of the cell thermal behaviors. The validated model is further employed to investigate the thermal deterioration originated from high-energy NCM811/SiC chemistry. According to the simulations, the thermal interactions between SiC-electrolyte, NCM811-electrolyte and NCM811-SiC can lead to maximum temperature increase by 318 °C, 222 °C and 174 °C, respectively, with total heat rising by 29%, 20% and 17%, when compared with the conventional Li[Ni1/3Co1/3Mn1/3]O2/graphite chemistry.

Suggested Citation

  • Wang, Yu & Ren, Dongsheng & Feng, Xuning & Wang, Li & Ouyang, Minggao, 2022. "Thermal runaway modeling of large format high-nickel/silicon-graphite lithium-ion batteries based on reaction sequence and kinetics," Applied Energy, Elsevier, vol. 306(PA).
    • Handle: RePEc:eee:appene:v:306:y:2022:i:pa:s0306261921012538
    DOI: 10.1016/j.apenergy.2021.117943
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    1. Feng, Xuning & Zheng, Siqi & Ren, Dongsheng & He, Xiangming & Wang, Li & Cui, Hao & Liu, Xiang & Jin, Changyong & Zhang, Fangshu & Xu, Chengshan & Hsu, Hungjen & Gao, Shang & Chen, Tianyu & Li, Yalun , 2019. "Investigating the thermal runaway mechanisms of lithium-ion batteries based on thermal analysis database," Applied Energy, Elsevier, vol. 246(C), pages 53-64.
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    2. Li, Da & Zhang, Zhaosheng & Zhou, Litao & Liu, Peng & Wang, Zhenpo & Deng, Junjun, 2022. "Multi-time-step and multi-parameter prediction for real-world proton exchange membrane fuel cell vehicles (PEMFCVs) toward fault prognosis and energy consumption prediction," Applied Energy, Elsevier, vol. 325(C).
    3. Xu, Chengshan & Wang, Huaibin & Jiang, Fachao & Feng, Xuning & Lu, Languang & Jin, Changyong & Zhang, Fangshu & Huang, Wensheng & Zhang, Mengqi & Ouyang, Minggao, 2023. "Modelling of thermal runaway propagation in lithium-ion battery pack using reduced-order model," Energy, Elsevier, vol. 268(C).
    4. Zhang, Yue & Song, Laifeng & Tian, Jiamin & Mei, Wenxin & Jiang, Lihua & Sun, Jinhua & Wang, Qingsong, 2024. "Modeling the propagation of internal thermal runaway in lithium-ion battery," Applied Energy, Elsevier, vol. 362(C).
    5. Gao, Yizhao & Sun, Ziqiang & Zhang, Dong & Shi, Dapai & Zhang, Xi, 2023. "Determination of half-cell open-circuit potential curve of silicon-graphite in a physics-based model for lithium-ion batteries," Applied Energy, Elsevier, vol. 349(C).
    6. Wei, Gang & Huang, Ranjun & Zhang, Guangxu & Jiang, Bo & Zhu, Jiangong & Guo, Yangyang & Han, Guangshuai & Wei, Xuezhe & Dai, Haifeng, 2023. "A comprehensive insight into the thermal runaway issues in the view of lithium-ion battery intrinsic safety performance and venting gas explosion hazards," Applied Energy, Elsevier, vol. 349(C).
    7. Gao, Xinlei & Li, Yalun & Wang, Huizhi & Liu, Xinhua & Wu, Yu & Yang, Shichun & Zhao, Zhengming & Ouyang, Minggao, 2023. "Probing inhomogeneity of electrical-thermal distribution on electrode during fast charging for lithium-ion batteries," Applied Energy, Elsevier, vol. 336(C).
    8. Zhang, Yue & Cheng, Siyuan & Mei, Wenxin & Jiang, Lihua & Jia, Zhuangzhuang & Cheng, Zhixiang & Sun, Jinhua & Wang, Qingsong, 2023. "Understanding of thermal runaway mechanism of LiFePO4 battery in-depth by three-level analysis," Applied Energy, Elsevier, vol. 336(C).
    9. García, Antonio & Pastor, José V. & Monsalve-Serrano, Javier & Golke, Diego, 2024. "Cell-to-cell dispersion impact on zero-dimensional models for predicting thermal runaway parameters of NCA and NMC811," Applied Energy, Elsevier, vol. 369(C).
    10. Wei, Peng & Li, Han-Xiong, 2022. "Multiscale dynamic construction for abnormality detection and localization of Li-ion batteries," Applied Energy, Elsevier, vol. 325(C).

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