SOH estimation method for lithium-ion batteries based on an improved equivalent circuit model via electrochemical impedance spectroscopy

Estimating the state of health (SOH) for lithium-ion batteries (LIBs) has always been one of the most important functions of battery management system (BMS). However, due to the LIBs' complex degradation mechanism, accurate estimation of SOH for the LIBs is still challenging now. As a typical electrochemical system test method, electrochemical impedance spectroscopy (EIS) of LIBs not only contains abundant internal information, but also is not susceptible to external environment. Therefore, in this paper, an EIS based method combining equivalent circuit model (ECM) and data-driven based method is proposed to estimate the SOH of LIBs. Firstly, to improve the fitting performance on EIS, a new equivalent circuit model with an added capacitor (ECMC) was constructed by improving the existing ECMs of LIBs. Then the parameters of the proposed ECMC were identified according to the EIS data, which can reflect the LIBs' degradation better. And the identified parameters, as the inputs to the gaussian process regression (GPR), were used to estimate the SOH of LIBs. The results show that when the parameters identified by the ECMC are used as the inputs of GPR, SOH of LIBs under different temperatures can be accurately estimated. The average root mean square error (RMSE) of this method is only 1.77 %, even for the cell with the worst estimation performance, its RMSE is only 2.95 %.