State of charge estimation for lithium-ion battery using an electrochemical model based on electrical double layer effect

Abstract

This paper focuses on an efficient fundamental approach of the electrochemical model of lithium-ion batteries (LIBs), especially considering the effect of Electrical Double Layer (EDL) potential on the over-potential of batteries. Firstly, the electrode solid phase and electrolyte liquid phase in LIBs are modelled by electrochemical theory, especially emphasizing the influence of EDL structure. Three-parameter parabola method is effectively employed to simplify the model. Furthermore, a parameter identification method based on genetic algorithm is proposed according to the structure characteristics of EDL model. The accuracy of model is verified by comparing the output voltage of the EDL model under 0.1∼2C charging/discharging, 1C pulse discharging and New European Driving Cycle (NEDC) condition with the experimental terminal voltage. Finally, the battery SOC estimation method is developed by using the extended Kalman filter (EKF) algorithm based on EDL model and is verified by the 1C pulse discharge and the NEDC condition experiments. The results show that the proposed algorithm can accurately estimate the SOC value of LIBs. In addition, the algorithm has a strong correction effect on the initial SOC error and convergence.