Online Identification of Lithium Battery Equivalent Circuit Model Parameters Based on a Variable Forgetting Factor Recursive Least Square Method

To accurately identify the parameters of the lithium battery equivalent circuit model online, this paper proposes a variable forgetting factor recursive least squares parameter identification method using the second-order RC equivalent circuit model for the study of lithium nickel-chromium-manganese(LiNMC) batteries. The method uses the system identification parameter terminal voltage and the measurement terminal voltage to open a window to calculate the error, and dynamically adjust the forgetting factor through the error to improve the least square method to improve the system parameter identification accuracy. The proposed method was validated by the experimental platform under Dynamic Stress Tset(DST) and Federal Urban Driving Schedule(FUDS), and the root mean square error of the terminal voltage was reduced by 24.8% and 16.4% respectively compared to the original fixed forgetting factor, showing that the proposed method has a higher discrimination accuracy.