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<p>The demand for lithium-ion batteries is increasing, making it crucial to select materials that accommodate specific user needs and enhance overall performance. In this context, it is essential to provide solutions for characterizing battery performance through non-destructive methods such as electrochemical impedance spectroscopy (EIS), which enables electrochemical performance diagnosis of the cell.</p><p>In this study, a numerical model of a lithium-ion cell with an NCA electrode was developed using COMSOL Multiphysics. It enabled us to investigate the key variables that influence the electrochemical impedance response and their quantitative impacts through a sensitivity analysis. Furthermore, the investigations were interpreted with electrochemical kinetics. These findings indicate that optimizing parameters exhibiting high sensitivity offers a practical method to improve the fidelity of the model’s predictions with experimental observations. This enhances both accuracy and the quality of fit, and importantly, means fewer parameters need to be thoroughly investigated, leading to a more efficient workflow.</p>

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Electrochemical interpretation and sensitivity analysis of optimization parameters from electrochemical impedance spectroscopy (EIS)

  • 期刊论文

  • 发表日期：

    2026年5月12日

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  • Seoyeon Park,
  • Gwon Deok Han,
  • Jeeyoung Shin

摘要

The demand for lithium-ion batteries is increasing, making it crucial to select materials that accommodate specific user needs and enhance overall performance. In this context, it is essential to provide solutions for characterizing battery performance through non-destructive methods such as electrochemical impedance spectroscopy (EIS), which enables electrochemical performance diagnosis of the cell.

In this study, a numerical model of a lithium-ion cell with an NCA electrode was developed using COMSOL Multiphysics. It enabled us to investigate the key variables that influence the electrochemical impedance response and their quantitative impacts through a sensitivity analysis. Furthermore, the investigations were interpreted with electrochemical kinetics. These findings indicate that optimizing parameters exhibiting high sensitivity offers a practical method to improve the fidelity of the model’s predictions with experimental observations. This enhances both accuracy and the quality of fit, and importantly, means fewer parameters need to be thoroughly investigated, leading to a more efficient workflow.