Design and implementation of software and hardware of battery management system based on a novel state of charge estimation method Online publication date: Fri, 16-Sep-2022
by Mingyue Zhang; Xiaobin Fan
International Journal of Electric and Hybrid Vehicles (IJEHV), Vol. 14, No. 3, 2022
Abstract: The battery management system (BMS) of new energy vehicles is a research hotspot for its importance to security. A typical BMS is designed in this paper to collect the status parameters (voltage, current, and temperature) and estimate state of charge (SOC) of the battery, which includes the battery pack, the lower computer and the upper computer. The lower computer mainly collected the status parameters. The upper computer mainly displayed the status of battery pack and controlled the working mode. For SOC estimation, the improved ampere-hour (Ah) integral algorithm in the lower computer considered the charge and discharge efficiency, temperature, and ageing factors; the improved extended Kalman filter (EKF) algorithm in the upper computer includes the dual polarisation (DP) model. Finally, the 1C constant current discharge experiment shows that the SOC estimation accuracy is good; especially the improved EKF is only ±0.02% and also tracks voltage fluctuations well.
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