Parameter Identification of Battery Model Based on Forgetting Factor Recursive Least Square Method

The accuracy of the lithium-ion battery model directly affects the reliability of the battery management system. Since the parameter values of the model vary with the operating conditions. Therefore, it is especially important to identify model parameters based on measured data. Based on the second-order RC equivalent circuit model, this paper uses the forgetting factor recursive least squares algorithm to realize the adaptive identification of battery model parameters. The comparison between the identification curve and the measured data shows that the recursive least squares algorithm with forgetting factor can fit the actual terminal voltage well, the calculation speed is fast, and the error of the identification result is small, which not only can guarantee the local identification accuracy, but also can achieve good identification effect for the whole.