Research on State of Charge Estimation for Power Battery of Electric Vehicle

被引：0
|
作者：
Zong, Changfu [1 ]
Xiang, Haiou [1 ]
He, Lei [1 ]
Chen, Dongxue [1 ]
机构：
[1] Jilin Univ, State Key Lab Automot Simulat & Control, Changchun 130023, Peoples R China
来源：
INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS II, PTS 1-3 | 2013年 / 336-338卷
关键词：
State of Charge; Extended Kalman Filter; Parameter Identification; Electric Vehicle;
D O I：
10.4028/www.scientific.net/AMM.336-338.799
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An optimized battery state of charge (SOC) estimation method has been proposed in this paper. The method is based on extended Kalman filter (EKF) and combines Ah counting method and open-circuit voltage (OCV) method. According to the current excitation-response of a battery, the internal parameters of the battery model were identified by the method of least squares. Then the proposed estimation method is verified by experiments. The results show that the estimation method can reduce the cumulative error caused by long discharge and it can estimate the battery SOC effectively and accurately.
引用
收藏
页码：799 / 803
页数：5
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