This paper explores the state estimation method of lithium-ion battery pack through theoretical analysisand experimental research. Combining the advantages of the empirical models of variouselectrochemical models, a new type of composite electrochemistry-dual circuit polarization (E-DCP)model is proposed to better reflect the dynamic performance of the power lithium-ion battery under theconditions of meeting its safe and reliable energy supply requirements. Using the multi-innovation leastsquares (MILS) algorithm to identify the parameters in the E-DCP model online, so that it has thecharacteristics of high data utilization efficiency and high parameter identification accuracy. The batterycharge and discharge efficiency function is introduced to dynamically modify the battery capacity, andthe dynamic function is used to improve the Kalman gain in the extended Kalman filter (EKF), a newtype of based on dynamic function improvement and combined with actual capacity correction (FCDEKF) algorithm is applied to the estimation of battery pack operating characteristics, which solves theproblem that the traditional EKF algorithm is difficult to estimate errors when the system input changerate is large. The experimental results of urban dynamometer driving schedule (UDDS) and complexcharge-discharge cycle test show that the maximum error of terminal voltage does not exceed 0.04V, theaccuracy is 99.05%, and the errors of MILS algorithm combined with FC-DEKF algorithm for SOCestimation are all within 1%. The proposed equivalent circuit modeling method and state estimationcorrection strategy provide a theoretical basis for the reliable application of high-power lithium-ionbattery packs.
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