基于改进卡尔曼滤波的电池SOC估算

发布时间：2019-01-08 17:43

【摘要】：以研究电动汽车动力电池管理系统为背景,以电池荷电状态估算为关键技术,介绍了荷电状态与其主要影响因素的非线性动态关系,建立了二阶RC等效电池模型.在此基础上,考虑了温度对电池内阻的影响,采用卡尔曼滤波算法、改进的安时计量法和开路电压法,结合基于温度的电池模型参数在线辨识,对电池荷电状态进行估算,通过MATLAB仿真,并与基于经验公式的卡尔曼滤波算法进行了对比,平均误差为2.46%,提高了估算精度,验证了算法的可行性和可靠性.
[Abstract]:Based on the research of electric vehicle power battery management system and the key technology of battery charge state estimation, the nonlinear dynamic relationship between charged state and its main influencing factors is introduced, and a second-order RC equivalent battery model is established. On this basis, considering the effect of temperature on the internal resistance of the battery, using the Kalman filter algorithm, the improved amperometric method and open-circuit voltage method, combined with the on-line identification of the parameters of the battery model based on temperature, the charged state of the battery is estimated. Through MATLAB simulation, and compared with the Kalman filter algorithm based on empirical formula, the average error is 2.46, which improves the estimation accuracy and verifies the feasibility and reliability of the algorithm.
【作者单位】：北京航空航天大学机械工程及自动化学院;
【分类号】：TM912

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