SOC Estimation Of LiFePO₄ Battery Based On Double Kalman Filter And Charging Voltage Curve

At present,the related technologies of electric vehicles are developing rapidly.As an important part of the battery management system for electric vehicles,battery SOC estimation has received extensive attention from researchers at home and abroad.In order to solve the existing problem of low accuracy and poor stability of battery SOC estimation results,the key technologies of double Kalman filtering based on the charging voltage curve are studied to improve the accuracy and stability of the battery SOC estimation results in this paper.Research is carried out from three aspects of LiFePO₄ battery characteristics,battery equivalent model construction and parameter identification and battery SOC estimation.The reliability of the battery SOC estimation method is verified by Xinwei test platform.First of all,this paper studies the characteristics of Li FePO₄ battery in depth.The method for finding the relation curve between the open-circuit voltage and the state of charge of the battery is explored,and the characteristics of the relationship curve is analyzed.The influence of the battery static time and the error adaptability on the open-cell voltage correction of battery SOC initial value are studied.Secondly,the author reference battery external nonlinear characteristics and practical feasibility LiFePO₄ battery equivalent circuit model is established,and compared with offline and online identification parameters as a result,proved the necessity of online identification model parameters and the advantages of kalman filtering algorithm parameter identification.In this topic,on the basis of kalman filtering algorithm,combined with the double kalman filter to estimate the battery SOC,results show that the proposed method to estimate the error is within 3%,at the same time,the robustness of the algorithm is verified by setting the initial deviation of the parameters.Finally,the author analyzes the influence of the battery voltage and current monitoring signal noise on the estimation accuracy of the battery SOC,and obtains the result that the monitoring signal noise caused the battery SOC to estimate the result deviation.Then the characteristics of charging voltage curve are analyzed,and a new method of estimating battery SOC based on double kalman filterfusion and charging voltage curve is proposed.The results show that the estimation method can eliminate the monitoring signal noise and ensure the accuracy of the battery SOC estimation,and improve the robustness of the estimation method.