This paper proposes a sensitivity-based group-wise parameter identification algorithm for the electrical model of Li-ion battery. A global sensitivity analysis method is first performed in the entire parameter space to evaluate the identifiability of the model parameters. Then, the parameters are sorted and grouped by the global sensitivity indices. Finally, a group-wise method embedded with the Levenberg-Marquardt algorithm is followed to identify the parameters. Numerical simulation results and comparisons demonstrate that the proposed group-wise identification algorithm can serve as a reliable tool for extracting parameters.
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Shen et al. (2017) studied this question.
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