Efficient SOC estimation for electric vehicles: Extended Kalman filter approach for lithium-ion battery systems

Abstract

This study investigates the estimation of the state of charge (SOC) in lithium-ion batteries by utilizing the extended Kalman filter (EKF) algorithm. A simulation model was developed in MATLAB, integrating the Thevenin model with the EKF algorithm to assess SOC levels. The results from the simulations confirm the accuracy and reliability of the proposed approach in estimating SOC. Moreover, a Simulink-based model of the Thevenin equivalent circuit and the EKF algorithm was implemented to further verify the effectiveness of the EKF in SOC estimation. This research underscores the potential of the EKF algorithm to deliver precise SOC estimates, which is crucial for optimizing battery management systems, particularly in electric vehicles.