Lithium-ion battery SOC estimation based on an improved adaptive extended Kalman filter

Battery is an important driving force of electric vehicles. Reasonable utilization of battery energy is a key link of battery management system. The battery management system can ensure the safety and efficiency of the battery by accurately estimating the SOC of the battery. In this paper, based on the establishment of battery equivalent model and parameter identification, a new battery SOC estimation method is proposed. This method is improved on the extended Kalman filter, and an adaptive filtering algorithm is used to solve the noise problem. Firstly, the theoretical analysis of the algorithm is completed. Finally, the simulation is carried out in MATLAB environment to verify the feasibility of the algorithm.