Modeling Strategy for Progressive Failure Prediction in Lithium-Ion Batteries under Mechanical Abuse: Article No. 100098

Hanfeng Yin, Shuai Ma, Honggang Li, Guilin Wen, Shriram Santhanagopalan, Chao Zhang

Research output: Contribution to journalArticlepeer-review

64 Scopus Citations


The prediction for the internal failure of lithium-ion batteries (LIBs) under external mechanical abuse loading remains a challenge for safe design. This paper systematically studies the modeling approach for progressive failure simulation and short-circuit prediction. Hemispherical indentation experiments are conducted on a battery specimen containing 5 representative sandwich (RS) layers to examine the deformation and progressive failure behavior of battery components. Three different models, viz, a high-fidelity detailed model, an intermediate homogenized model and a fully homogenized model, are developed and employed to simulate the progressive failure in a multi-layer battery specimen. The simulation results obtained using the three models all correlate well with experimental phenomena, capturing the overall stress-strain response and ultimate failure of the battery structure. The numerical results can help us understand the failure behavior and the mechanism for mechanical abuse-induced short circuit in LIBs. The feasibility of the three models for use in progressive failure prediction is compared by analyzing the capability of the models in predicting the critical failure events, the computational efficiency of the models, and the feasibility to implement coupled mechanical-electrochemical-thermal simulations. The results of this work provide useful insights on practical choices for the modeling strategy and safety design of LIBs under mechanical abuse conditions.
Original languageAmerican English
Number of pages12
StatePublished - 2021

NREL Publication Number

  • NREL/JA-5700-76871


  • finite element analysis
  • high-fidelity detailed model
  • homogenized model
  • lithium-ion batteries
  • mechanical failure behavior


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