Comparison of the SOC Estimation Method for Lithium Battery Based on Simulink

Abstract

Abstract SOC (State Of Charge, SOC) represents the state of charge of a battery and is one of the important indicators to measure the energy usage of the battery. In the field of automotive energy, accurate battery SOC estimation is of great significance for improving the range, service life, and safety of electric vehicles. It is an important part of battery management and energy management. The current SOC estimation methods are diverse, and the ampere-hour integration method has the advantages of high accuracy and simple implementation. The EKF (Extended Kalman Filter) algorithm provides solutions for nonlinear problems such as SOC estimation of batteries. Therefore, these two methods are the preferred choice for some vehicle manufacturers and BMS enterprises. This study selects a first-order RC equivalent circuit model for parameter identification, builds a circuit model on Simulink, and compares and verifies the error of the AH integration method and EKF algorithm.