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A comprehensive insight into the thermal runaway issues in the view of lithium-ion battery intrinsic safety performance and venting gas explosion hazards

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  • Wei, Gang
  • Huang, Ranjun
  • Zhang, Guangxu
  • Jiang, Bo
  • Zhu, Jiangong
  • Guo, Yangyang
  • Han, Guangshuai
  • Wei, Xuezhe
  • Dai, Haifeng

Abstract

A comprehensive understanding of thermal runaway (TR) features and battery venting gas (BVG) explosion characteristics is the critical issue of thermal hazard prevention. In this study, commercial-size lithium-ion batteries with LiFePO4 (LFP) and Li(NixCoyMnz)O2 (NCM, x from 0.5 to 0.8) cathode materials, as well as the micro-overcharged cells, are triggered to TR under adiabatic conditions using an accelerating rate calorimeter. In addition, the obtained BVG is transferred into the gas chromatograph for further component identification. Subsequently, the specific values of the intrinsic battery safety performance (TR tolerance and TR hazards) and BVG explosion risks (lower explosion limits, LEL) are calculated. The results show that, from the perspective of battery TR evolution features, LFP batteries have greater TR tolerance than NCM batteries. Moreover, the TR hazards of NCM batteries are more severe than LFP batteries and worsen with increasing nickel content, which is proved by ambient temperature and post-disaster analysis. The primary types of BVG consist of hydrogen, carbon monoxide, carbon dioxide and hydrocarbon gases for both LFP and NCM batteries. However, due to the significant amount of hydrogen and hydrocarbon gases with low LEL values, the LEL values of BVG for LFP batteries are lower than NCM batteries, demonstrating the higher deflagration risks for the former. Besides, the LEL values of NCM batteries' BVG increase with higher energy density. A single micro-overcharge leads to lower TR tolerance and TR hazards but has little effect on LEL values for NCM cells. It is obvious that the safety issues associated with LFP batteries should also be given sufficient attention to avoid system-level explosions. The quantitative evaluation results of this paper provide new ideas for battery intrinsic safety performance assessment and a clear direction for mitigation strategy of battery TR-related secondary disasters.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:349:y:2023:i:c:s0306261923010152
    DOI: 10.1016/j.apenergy.2023.121651
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    1. 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).
    2. 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.
    3. Jiang, Bo & Zhu, Yuli & Zhu, Jiangong & Wei, Xuezhe & Dai, Haifeng, 2023. "An adaptive capacity estimation approach for lithium-ion battery using 10-min relaxation voltage within high state of charge range," Energy, Elsevier, vol. 263(PC).
    4. Donal P. Finegan & Mario Scheel & James B. Robinson & Bernhard Tjaden & Ian Hunt & Thomas J. Mason & Jason Millichamp & Marco Di Michiel & Gregory J. Offer & Gareth Hinds & Dan J.L. Brett & Paul R. Sh, 2015. "In-operando high-speed tomography of lithium-ion batteries during thermal runaway," Nature Communications, Nature, vol. 6(1), pages 1-10, November.
    5. Jiangong Zhu & Yixiu Wang & Yuan Huang & R. Bhushan Gopaluni & Yankai Cao & Michael Heere & Martin J. Mühlbauer & Liuda Mereacre & Haifeng Dai & Xinhua Liu & Anatoliy Senyshyn & Xuezhe Wei & Michael K, 2022. "Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    6. Qiao, Dongdong & Wang, Xueyuan & Lai, Xin & Zheng, Yuejiu & Wei, Xuezhe & Dai, Haifeng, 2022. "Online quantitative diagnosis of internal short circuit for lithium-ion batteries using incremental capacity method," Energy, Elsevier, vol. 243(C).
    7. Ding, Tao & Sun, Yuge & Huang, Can & Mu, Chenlu & Fan, Yuqi & Lin, Jiang & Qin, Yining, 2022. "Pathways of clean energy heating electrification programs for reducing carbon emissions in Northwest China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    8. Jia, Zhuangzhuang & Song, Laifeng & Mei, Wenxin & Yu, Yin & Meng, Xiangdong & Jin, Kaiqiang & Sun, Jinhua & Wang, Qingsong, 2022. "The preload force effect on the thermal runaway and venting behaviors of large-format prismatic LiFePO4 batteries," Applied Energy, Elsevier, vol. 327(C).
    9. Qin, Peng & Jia, Zhuangzhuang & Wu, Jingyun & Jin, Kaiqiang & Duan, Qiangling & Jiang, Lihua & Sun, Jinhua & Ding, Jinghu & Shi, Cheng & Wang, Qingsong, 2022. "The thermal runaway analysis on LiFePO4 electrical energy storage packs with different venting areas and void volumes," Applied Energy, Elsevier, vol. 313(C).
    10. Xiang Liu & Liang Yin & Dongsheng Ren & Li Wang & Yang Ren & Wenqian Xu & Saul Lapidus & Hewu Wang & Xiangming He & Zonghai Chen & Gui-Liang Xu & Minggao Ouyang & Khalil Amine, 2021. "In situ observation of thermal-driven degradation and safety concerns of lithiated graphite anode," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    11. 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).
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