SOC estimation of power batteries for an electric vehicle
TANG Xu
YE Jinlu
XIAO Jintao
TANG daokuan
SONG Haitao
TAN Xianlin
Abstract：In order to accurately evaluate the state of charge(SOC)of lithium-ion batteries for an electric vehicle,a second-order resistance capacitance equivalent circuit model is constructed.The parameters of the equivalent circuit model are identified using recursive least squares method,and the functional relationship between the open circuit voltage and SOC under dynamic stress test(DST)conditions is obtained through open circuit voltage discharge test.The SOC is estimated by open circuit voltage method,Kalman filter method,and extended Kalman filter method,and their errors are compared and analyzed under DST condition.The results show that the Kalman filter and extended Kalman filter algorithms are in good agreement with the SOC estimation results of the open circuit voltage method.The maximum SOC estimation error of the Kalman filtering method is 0.017,and the maximum SOC estimation error of the extended Kalman filtering method is 0.013,both of which meet the standard requirement of SOC estimation error not exceeding 0.050,however,the accuracy of the extended Kalman filtering algorithm is higher.
Keywords：electric vehiclelithium ion batterySOC estimationerror
Publication Date：2024-04-28
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：6( 97-102 )