Abstract:Efficient operation of new energy storage systems relies heavily on accurately estimating the state of charge (SOC)of lithiumion batteries.In order to improve the accuracy of estimating SOC of lithium batteries,a method based on fractional order unscented Kalman filter(FOUKF)algorithm and recursive least square method with adaptive forgetting factor(AFFRLS)is proposed to estimate SOC of lithium battery.Firstly,a second-order RC model based on fractional-order calculus theory was developed to model the lithium battery characteristics.Then perform a pulse characterization test to obtain the battery terminal voltage,and complete parameter identification based on AFFRLS.In addition,the proposed algorithm based on FOUKF is applied to estimateSOC in battery discharge experiments.Finally, comparedthe three prediction indicators of maximum absolute error(MAE),average absolute error(AAE)and root mean square error(RMSE)with the comparison method.The experimental results show that the estimated MAE of sOC by FOUKF algorithm is less than2%,and the AAEand RMSE are both lessthan0.8%.The experimental results show that the proposed algorithm has high accuracy and anti-interference ability.