Research On State Of Charge Estimation For Battery Electric Vehicle

Battery electric vehicle has a great role to become a new trend in the automotive industry due to its cleaness and no pollution. As the core of the technology and the production cost of electric vehicle, battery is of great significance in the current development. The focus is how to improve the accuracy of the battery state of charge(SOC). This paper centers with forgetting factor recursive least-squares algorithm, Kalman filtering method, open circuit voltage method and ampere hour method, making a research on SOC estimation for battery electric vehicles. This paper mainly includes four aspects as follows:(1) An analysis of the characteristics of lithium battery is made,combined with the advantages and disadvantages of the equivalent circuit model of lithium battery, to make improvements on the Thevenin model.The voltage source is transformed into equivalent capacitance, and the circuit model is derived, so to obtain the state space model.(2) The parameter identification of the equivalent circuit model with forgetting factor recursive least-squares algorithm is accomplished.According to the parameters of the battery model, the attempt into verifying the accuracy of lithium battery model is proposed.(3) The traditional SOC estimation methods and the basic principle of the Kalman filter are analyzed. Estimation of the battery SOC by Kalman filter is conducted and the comparison of the estimated value and the true value is made. A new Kalman filtering method combined with ampere hour method and open circuit voltage method is then proposed, gaining improvement on the space expression of battery equivalent circuit model and then the comparison of the estimated value and the true value is made.The results show that the combined method based on Kalman filteringalgorithm has a higher precision.(4) The NYCC is chosen to make the overall simulation of the vehicle to differ from UDDS. The results show that the improved equivalent circuit model and the combined method based on Kalman filtering algorithm are of higher accuracy.