A Novel On-line Parameter Identification and State of Charge Estimation of Lithium-ion Power Battery for Electric Vehicle

摘要

Accurated estimation of the battery state of charge is one of the key technologies in the research of battery management system of electric vehicle. In order to estimate the state of charge of lithium-ion battery, we have chosen the Thevenin battery model as the lithium-ion battery equivalent circuit model. We established a state space model which had the advantage of simplicity and could be easily implemented based on the Thevenin battery model. And the Least Squares method is then applied to identificate the battery model parameters. Based on these, the model was linearizoed, and extended Kalman filter was applied in the estimation of the battery state of charge. Test and simulation results show that the Thevenin battery model can batter reflect the dynamic and static characteristics of the lithium-ion battery, and by one-line battery model parameters identification, the algorithm of extended Kalman filter can obtain better accuracy in the process of estimation of the state of charge. So the algorithm of extended Kalman filter has a strong application in the estimation of the state of charge.