Research On State Of Charge Estimation Of Power Battery Used On Electric Vehicle And Battery Management System Design

Due to the high energy utilization and low pollution emission,electric vehicle has become developing direction of car industry.As an important part of electric vehicle,battery management system has been widely studied around the world.Under this background,SOC(State of Charge)estimation strategy for Li-ion battery and design of battery management system are carefully studied in this paper.A comprehensive Kalman filtering algorithm is proposed for SOC estimation of Li-ion battery.Firstly,the battery model parameters are identified by recursive least squares algorithm(RLS).Secondly,applying the comprehensive Kalman filtering algorithm to estimate the battery SOC.In view of the model's linear part and nonlinear part,using linear Kalman filter(KF)and square-root high-degree cubature Kalman filter(SHCKF)respectively.The combination of two Kalman filtering algorithms can theoretically improve accuracy and reduce complexity.SHCKF combines the 5thdegree spherical–radial cubature quadrature rule and square-root filtering technology.SHCKF is more accurate and numerically stable,compared with traditional nonlinear filtering algorithms such as EKF,UKF,and CKF.The experimental results show the feasibility and effectiveness of the proposed comprehensive algorithm.In addition,a battery management system solution for karting is designed.The design scheme includes three parts: hardware circuit,software program and upper computer platform.The functions of the system include battery pack information acquisition,CAN communication,SOC estimation,fault alarming and relay control.