Construction of a battery management system in electric vehicle

Abstract

Due to their advantages of high energy density, relatively long life time and lack of memory effect, lithium ion (Li-ion) batteries are very popular and are widely used in electric vehicle (EV) applications. However, overcharging or over discharging them could bring loss in performance and result in potentially dangerous situations. Therefore additional requirements on safety, reliability and modularity of battery management system (BMS) have to be considered. In order to achieve these requirements, the BMS needs to balance the state of charge (SOC) of each cell during battery operations based on the inputs such as the voltage, current and temperature of each cell. In this report, the working principle of a traditional BMS will be explained and evaluation of several different SOC estimation methods will be done so as to adopt the most accuracy and efficient SOC estimation. Methods to determine the state of health (SOH) and remaining useful life (RUL) of the battery will also be discussed. Different cell balancing techniques will also be evaluated and the most efficient cell balancing technique will be adopted. The BMS will be built by using Xilinx FPGA and soft processor cores from Xilinx, PicoBlaze, to provide control over the discrete electronic components for measuring voltage, current and temperature. It also will implement the SOC estimation and controlling the cell balancing circuits. The circuitry design on monitoring the voltage, current and temperature of the battery will be discussed in detailed. Accuracy of these parameters and the effectiveness of the cell balancing technique will be shown so as to ensure the reliability and effectivity of the BMS. Problem that arises from building the BMS will also be discussed and further recommendations for future work will be made.