中国电机工程学报Issue(1)：185-191,7.DOI:10.13334/j.0258-8013.pcsee.2015.01.023
基于离散滑模观测器的锂电池荷电状态估计
Charge State Estimation of Li-ion Batteries Based on Discrete-time Sliding Mode Observers
摘要
Abstract
Estimation of the state of charge (SOC) is the key technique in the power management system for a li-ion power battery. For the inherent nonlinear property of the li-ion power battery, a method of SOC estimation is proposed applied to batteries, and the design of the algorithm for battery SOC estimation based on discrete-time sliding mode observers (DSMO) is given and the stability proof of DSMO is proven. Based on the Thevenin equivalent model, the detailed procedures of this estimation method are exhibited,and the model parameters are identified at different current rate and ambient temperature. The accuracy, the robustness and the time complexity of the extended Kalman filter (EKF) and the proposed method are analyzed in this comparative study. Experiments show that the arithmetic of the discrete-time sliding mode observers can be used to compute the battery SOC quickly and accurately with the dynamic error of 3%, and that the feasibility of the proposed algorithm is verified.关键词
锂电池/荷电状态/离散滑模观测器/扩展卡尔曼滤波器Key words
Li-ion battery/state of charge/discrete-time sliding mode observer/extended Kalman filter分类
交通工程引用本文复制引用
孙冬,陈息坤..基于离散滑模观测器的锂电池荷电状态估计[J].中国电机工程学报,2015,(1):185-191,7.基金项目
国家863高技术基金项目(2011AA11A247)。The National High Technology Research and Development of China 863 Program (2011AA11A247) （2011AA11A247）
