A novel adaptive sliding mode observer for SOC estimation of lithium batteries in electric vehicles

Y. Huangfu, J. N. Xu, S. Zhuo, M. Xie, Y.T. Liu
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引用次数: 10

Abstract

On the basis of the established second order RC equivalent circuit model, a novel adaptive sliding mode observer (ASMO) is proposed to estimate the state of charge (SOC) of lithium battery in the electric vehicle. The ASMO can adaptively adjust the switching gain according to the system output deviation. The Lyapunov stability theory is employed to prove the convergence of ASMO. Three different discharge curves are carried out, and the comparisons with conventional sliding mode observer (CSMO) and adaptive extended Kalman filter (AEKF) are also presented to evaluate the performance of ASMO. The results show that: (1) compared with CSMO, ASMO can solve the contradiction between the SOC convergence speed and the chattering (2) compared with AEKF, ASMO has the similar SOC estimation accuracy, but possesses faster convergence speed, stronger robustness and less computation time.
一种用于电动汽车锂电池荷电状态估计的自适应滑模观测器
在建立二阶RC等效电路模型的基础上,提出了一种新的自适应滑模观测器(ASMO)来估计电动汽车锂电池的荷电状态。ASMO可以根据系统输出偏差自适应调节开关增益。利用Lyapunov稳定性理论证明了ASMO的收敛性。给出了三种不同的放电曲线,并与传统滑模观测器(CSMO)和自适应扩展卡尔曼滤波器(AEKF)进行了比较,评价了ASMO的性能。结果表明:(1)与CSMO相比,ASMO能够解决SOC收敛速度与抖振之间的矛盾;(2)与AEKF相比,ASMO具有相似的SOC估计精度,但具有更快的收敛速度、更强的鲁棒性和更少的计算时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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