摘要
应用滑模观测器方法进行了荷电状态估计的研究.基于改进的Thevenin等效电路模型建立了电池的状态空间模型,设计了一种能改善抖动问题的滑模状态观测器.为分析观测器的稳定性,对模型中的非线性项进行了分析,根据其导数有界的特性,利用拉格朗日中值定理给出了保证观测器收敛的条件,并由此确定观测器的设计参数.并且在Matlab环境下对该方法进行了仿真,与扩展卡尔曼滤波方法进行了比较,结果表明在电池的建模误差相同的情况下该方法具有更高的估计精度.所以,用滑模观测器进行荷电状态的估计可以有效地减小由模型误差引入的荷电状态估计误差.
A method to estimate SOC （state of charge） using sliding mode observer is studied. First, a modified Thevenin model was used to establish the state space model of a battery. Then a sliding mode observer was designed. In order to analyze the stability of the observer, the nonlinear feature of the battery model was analyzed, which is used along with the theorem of Lagrange＇s mean to design a stable observer. Finally, a simulation experiment was carried out using Matlab. The result shows that this method has better predicting performance comparing to the extended Kalman filter method when there exists the same modeling errors. The uncertainty and model errors caused by the simple model are compensated by the sliding mode observer.
出处
《东南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第B09期97-101,共5页
Journal of Southeast University：Natural Science Edition
关键词
电动汽车
电池荷电状态
滑模观测器
electric vehicle
state of charge
sliding mode observer
