Prediction Of The SOC Of Power Battery And Performance Simulation For EV

Electric Vehicles (EV) are a kind of environmentally friendly cars powered by batteries. The performance of batteries plays an important role on the whole performance of EV, and directly influences performance, such as, the range of driving, acceleration ability, climbing capacity and so on. Therefore a battery management system (BMS) is demanded for electric vehicles. This thesis focuses on modeling and simulation of battery characteristics, and the prediction of the SOC of batteries which is one of the key issues of BMS.The paper firstly gave a brief review on some conventional SOC prediction methods. Then, based on the charge/discharge experiment on in house developed EV-3, the electrochemistry characteristics of Ni-MH battery, and the relationships between voltage, current, temperature and capacity, respectively, were studied in-depth. In order to predict the SOC of batteries accurately, a voltage descent model was proposed based on the charge/discharge experimental data of EV-3. Further on, a BP neural network has also been proposed which indicates the correlation between open circuit voltage and SOC. Tests and simulations results show that the intelligent methods can accurately predict the SOC of Ni-MH batteries.The performance of power battery directly affects the vehicle performances; Therefore, the simulation of battery is one of the important steps. The paper firstly has introduced the development status of power batteries'modeling; then attempts to model Ni-MH battery with modified RINT model of ADVISOR which contains two open-circuit-voltages to distinguish charge and discharge. But the results have shown that it isn't so acceptable although it has been more accurate than RINT model. The paper has introduced a new battery model named mesh model with more generality. The simulation results are reasonable and acceptable, and are in good agreement with the experimental results.The research of this paper will be valuable and helpful for improving BMS system and establishing battery simulation system; and for a reliable control strategies simulation and implementation.