Design Of Lithium Battery Management System For Formula Student Electric Racing Car

Under the guidance of the country’s policy of new energy vehicles, Formula Student pure electric racing car is gaining popularity among colleges and universities. Pure electric racing car requires lightweight design, high reliability and safety, but the battery and battery management technology restrict its development. Through the research of lithium polymer battery, one kind of battery management system was designed to real-time monitor status of the battery pack, grasp the remaining capacity of the battery pack, implementing effective equilibrium management and timely handling of hazardous conditions. Therefore, the batteries can be safe, reliable and efficient operation.In this paper, lithium polymer battery was regarded as the object and its open circuit voltage and rebound voltage were analyzed through charging and discharging experiments. Then one battery model based on second-order RC network was established and the model parameters were identified by using exponential fitting method. The model simulation test was carried out with MATLAB/Simulink by applying pulse current and user-defined current. The simulation results fit the experimental data quite well and the accuracy of the battery model and parameters has been verified.Through the analysis of estimation methods of State of Charge(SOC), the extended Kalman filter(EKF) algorithm was selected as the paper’s SOC estimation method. The EKF algorithm ignores the high-order terms of Taylor expansion, which leads to some errors. The finite difference method was adopted to amend its high-order terms. With the combination of finite difference EKF algorithm(FDEKF) and the battery model, the estimation of SOC was performed. The simulation of EKF algorithm and FDEKF algorithm was carried out with MATLAB/Simulink. Compared to the experimental data, the simulation results show that the estimation error of FDEKF algorithm does not exceed 3% and the FDEKF algorithm has better estimation accuracy.The equalization strategy simply based on cell voltage or SOC has some deficiency. One new equalization strategy combined cell voltage with SOC was studied. Different equalization criteria and thresholds were formulated at different stages of charging or discharging and the equalization strategy was also developed. The equalization circuit was established based on the battery model and the simulation of equalization strategy was carried out with MATLAB/Simulink. The simulation and experiment results show that the strategy can improve energy utilization, prevent battery overcharge and over discharge effectively.Hardware and software were designed for lithium polymer battery management system. The part of hardware is one kind of master-slave distributed structure, which has a master control unit(BMU) and six distributed units(BDU). The functions of estimation of SOC, detection of total voltage and current of the battery pack, CAN communication between modules were completed with BMU. Each BDU manages 16 cells, responsible for detection of cell voltage, temperature and equalization control. The part of software was listed flow charts of the system. Finally, the performance test for the battery pack was conducted to detect the sampling and estimation accuracy of the system. Experiment results show that the battery management system can achieve the desired goals.