SOC Estimation Of Lithium Ion Battery Based On Unscented Kalman Filter

With the growing development of electric vehicles,as the power source of electric vehicles,power batteries gradually become the focus of research in the field of electric vehicles.As one of the important parameters of the power battery,the battery state of charge(State of Charge,SOC),that is,the battery power is the focus of the study.In this paper,the work around the power of lithium-ion battery SOC estimation issues has been carried out from the following aspects :Firstly,the working principle of lithium ion battery is described,and the classical SOC estimation method and the complex estimation algorithm based on circuit model are introduced.The advantages of the Kalman filter algorithm chosen in this paper are discussed.Secondly,combined with the Thevenin battery equivalent circuit model,a second-order RC model which can reflect the lithium-ion battery is constructed,and the circuit equation is deduced.The experimental data of HPPC battery charge and discharge are processed in Matlab,and the model parameters are used to identify the parameters.And the simulation results are compared with the actual data to prove that the model is more accurate.Then,through the establishment of simulation conditions,the program is written in Matlab,and the on-line identification of the model parameters is carried out by using the recursive least squares method.It is proved that the algorithm is feasible on-line identification.Finally,the finite element Kalman filter is used to simulate the SOC of the lithium ion battery by writing the algorithm program in Matlab.By comparing the estimated value with the actual value and the error analysis under different working conditions,it is proved that the algorithm has high accuracy of SOC estimation and has a good effect on the system error and the initial deviation of SOC.