An iterative identification method for equivalent circuit battery models

The exact battery model has always been a thorny problem in battery management system (BMS). In order to meet the actual working conditions, battery model parameters should be identified from a variety of experimental data (charging, discharging and rest periods). In this paper, we propose a parameter identification method based on iterative learning for the equivalent circuit battery models. This method can be used for parameter identification under complex operating conditions. Simulated and experimental studies validate the feasibility of the proposed method.