Equivalent modeling and parameter identification of power lithium-ion batteries

The equivalent modeling and parameter identification of power lithium-ion batteries are important basis for describing the working characteristics of power lithium-ion batteries. To improve the estimation accuracy of the state of charge of a lithium battery in a complex working environment, this chapter studies and analyzes different battery modeling methods and determines the optimal order of the Thevenin equivalent circuit model and constructs an improved Thevenin equivalent circuit model. By analyzing different parameter identification methods, the Forgetting Factor Recursive Extended Least Squares algorithm is proposed to identify the model parameters online. The experimental results show that the algorithm can better identify the parameters of the high-power lithium-ion battery model by taking into account the influence of historical data when the current data is saturated and the influence of noise.