전기자동차 모델링 및 확장 칼만필터를 이용한 배터리 SOC 추정에 관한 연구

Abstract

In order to improve battery state of charge (SOC) estimation methods, this research developed an electric vehicle (EV) model using Matlab/Simulink software and compared the modelled performance with test data of an EV developed for actual use. To develop a 28 kW EV using an induction motor, a gearbox with a 1 : 5.5 ratio was used in the powertrain. We utilized an 11.1 kWh battery pack, which included a battery management system (BMS), using 20x2 lithium-polymer battery cells. An on-board charger (OBC) with 220V (AC) input and 22A output was used to charge the battery pack. The technical specifications were obtained through various experiments. Accurate estimation of battery SOC is one of the key problems in a BMS. This paper proposes a battery SOC estimation method using an extended Kalman filter for lithium-polymer batteries. An electric circuit model (ECM) was set up to represent different degrees of parameter shift due to chemistry, charging, discharging, temperature, and age. Numerical simulation and hardware test results indicate that the proposed algorithm is very useful with respect to improving the accuracy of battery SOC estimation.