A Two-Stage Estimation Strategy Based on A Multi-State Model for State-of-Health of Lithium-Ion Batteries

The state of health (SOH) is a significant index for the safe and reliable performance of lithium-ion batteries (LIBs). Although electrochemical impedance spectroscopy (EIS) is a promising nondestructive technique for SOH estimation, existing investigations rarely apply EIS to establish SOH estimation mathematical models. Considering the SOH estimation model based on EIS is imposed by the nonlinear and coupled constraints including temperature and state of charge (SOC), in this paper, the charge transfer resistance is extracted first as the aging feature through EIS analysis under different conditions of SOH, SOC, and temperature. Then, a multi-state SOH model is developed based on the charge transfer resistance. The model quantitatively elucidates the interdependencies among charge transfer resistance, SOH, SOC, and temperature. A two-stage SOH estimation strategy is subsequently proposed based on the proposed model to address the inferior of accuracy from the traditional probabilistic model for SOH estimation due to inaccurate model parameters. Specifically, in the first stage, the SOH is initialized. In the second stage, SOH is re-estimated based on optimal point parameters selected by the SOH obtained in the first stage. Finally, the proposed estimation strategy for SOH is verified through experiments, where the estimation maximum RMSE is less than 0.04. Compared to the previous methods, the proposed strategy demonstrates more accuracy in SOH estimation.