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Modeling venting behavior of lithium-ion batteries during thermal runaway propagation by coupling CFD and thermal resistance network

Author

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  • Wang, Gongquan
  • Kong, Depeng
  • Ping, Ping
  • He, Xiaoqin
  • Lv, Hongpeng
  • Zhao, Hengle
  • Hong, Wanru

Abstract

Thermal runaway (TR) seriously hinders the wide application of lithium-ion batteries. One of the most significant hazards of TR lies in the emission of flammable gases, which might cause explosion in the battery pack. A TR model incorporating venting provides insights into reducing explosion risk and aids to determine the safety-optimal configuration of battery pack. In this study, a modeling framework is proposed to address gas venting and explosion hazard by coupling CFD and thermal resistance network. The TR propagation is predicted by a lumped network integrating heat generation and jet dynamics while the transport of gases is simulated by the CFD models. The developed model was confirmed by cell temperatures and gas concentrations measured by experiments and then adopted to examine the influence of various configurations of battery pack. Results demonstrate increasing ventilation rate can decrease the gas concentration and shorten the duration of battery pack under explosion whereas a limited effect of void volume is evident for that. Despite of reducing TR propagation speeds, the increase of cell distance can inhibit the rapid dispersion of venting gases, causing battery pack exposed to a prolonged explosion risk. The present model represents the further optimization of battery pack from the aspect of safety.

Suggested Citation

  • Wang, Gongquan & Kong, Depeng & Ping, Ping & He, Xiaoqin & Lv, Hongpeng & Zhao, Hengle & Hong, Wanru, 2023. "Modeling venting behavior of lithium-ion batteries during thermal runaway propagation by coupling CFD and thermal resistance network," Applied Energy, Elsevier, vol. 334(C).
    • Handle: RePEc:eee:appene:v:334:y:2023:i:c:s0306261923000247
    DOI: 10.1016/j.apenergy.2023.120660
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    5. Wang, Gongquan & Ping, Ping & Peng, Rongqi & Lv, Hongpeng & Zhao, Hengle & Gao, Wei & Kong, Depeng, 2023. "A semi reduced-order model for multi-scale simulation of fire propagation of lithium-ion batteries in energy storage system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 186(C).

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