Charge State Estimation of Power Battery Based on CARMA Model - HUANG Yusha; CHEN Yushan; QIN Linlin; SHI Chun; WU Gang (Kongzhi Yu Xinxi Jishu)
In order to perfect main functions of electric vehicle battery management system, this paper aims to realize accurate battery modeling and state of charge(SOC) estimation. In this paper, based on the second-order RC equivalent circuit model, a controlled auto regressive moving average (CARMA) of the battery was established. The optimal estimation of open circuit voltage (OCV) is derived from the CARMA model, and battery SOC estimation is realised by OCV-SOC segmentation model. The method realizes online real-time identification of battery model parameters and real-time SOC estimation, which solves the problem of unreasonable initial value setting that affects the accuracy of SOC estimation. Simulation results show that under the operating conditions of the federal city in the United States, the absolute value of the SOC estimation error does not exceed 2.39%, and a more accurate SOC estimation is achieved.