Abstract
Electrochemical impedance spectrum of lithium-ion battery changes regularly with cycling, and is an effective tool for analyzing aging. However, due to the anomalous diffusions and non-exponential effects in battery, EIS-based model is generally identified in complex and time-consuming ways, which limits its online application. In this paper, a parameter identification method for EIS-based model is proposed using geometric analysis. By fitting the impedance spectrum at intermediate frequencies with two depressed semicircles, the parameters of EIS-based model are directly calculated, greatly reducing the computational complexity. Compared with the traditional optimization algorithms, the indexes of the proposed method are optimal, considering running time, file size and goodness of fit. Furthermore, six model parameters are identified based on EIS at different temperatures, states of charge and aging cycles, and their relationship with capacity decay is analyzed. The results show that the charge transfer resistance always has an excellent linear correlation with capacity decay, and the correlation coefficient exceeds 0.94 regardless of temperature and state of charge. It can be used as health indicator of battery. Moreover, one fractional-order parameter has a good correlation with the capacity only at high temperature.
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