Research On SOC Estimation Method Of Lithium-ion Battery For Electric Vehicle

With the increasing environmental pollution problems and the growing shortage of traditional fossil fuels,countries all over the world have attached great importance to the development of electric vehicles.The design and manufacture of key components such as electric vehicle three-electric systems have also become the focus of research.The state of charge(SOC)is an extremely significant evaluation index in the battery management system in electric vehicle.It is very difficult to obtain accurate SOC value because that SOC is an internal state of batteries.And a s the power source of electric vehicles,the SOC estimation of the battery accurately is very important to prevent the battery from overcharging,overdischarging and prolonging the service life of the battery.This thesis takes 18650 lithium-ion battery as the research object and carries out the research on the SOC estimation method of lithium-ion battery,providing reference for accurate SOC estimation of the battery management system.The main works of this thesis are as follows:(1)The experimental data are used to study the voltage characteristics,internal resistance characteristics,cycle life and capacity characteristics of lithium-ion batteries.And the influences of discharge rate,temperature,self-discharge and battery aging on the SOC of lithium-ion batteries are analyzed,revealing the reasons of inaccuracy of the SOC estimation of lithium-ion batteries.(2)Using the research methods of combining simulation and experimental veri fication,the static capacity test experiment,the OCV-SOC rapid calibration experiment and DST experiment are designed.The recursive least square method is applied to identify the parameters of Thevenin battery model by using experimental data and validate the battery model.The results show that the mean relative error between the battery model simulaton and the experimental data is very small,the battery model can well reflect the operating characteristics of lithium-ion batteries.(3)An SOC estimation algorithm based on the cubature Kalman filter(CKF)is proposed.The state equation and measurement equation of the battery model are built.And using the DST experimental data,the extended Kalman filter(EKF)algorithm,the(uncented Kalman filter)UKF algorithm and CKF algorithm are compared and analyzed in SOC estimation.The results show that the CKF algorithm has the least error when the execution time is less more than EKF algorithm,so the accuracy of CKF algorithm is the highest.(4)The CKF algorithm is optimized and an SOC estimation algorithm based on adaptive square root cubature Kalman filter(ASRCKF)is proposed.The square root filter is introduced into CKF.At the same time,the covariance matching idea based on the output voltage residual sequence of the battery model is introduced to adaptively estimate the process and measurement noise.Using the experimental data of DST and UDDS,the CKF algorithm and the ASRCKF algorithm are compared.The results show that the ASRCKF algorithm is more stable and accurate than the CKF algorithm,and ASRCKF algorithm has better convergence.