State of Charge Estimation of Lithium-Ion Batteries with Unknown Model Parameters

被引：0
|
作者：
Ouyang, Quan [1 ]
Chen, Jian [1 ]
You, Keyou [2 ,3 ]
机构：
[1] Zhejiang Univ, Coll Control Sci & Engn, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China
[2] Tsinghua Univ, Dept Automat, Beijing 10084, Peoples R China
[3] Tsinghua Univ, TNList, Beijing 10084, Peoples R China
来源：
2016 AMERICAN CONTROL CONFERENCE (ACC) | 2016年
基金：
中国国家自然科学基金;
关键词：
EXTENDED KALMAN FILTER; MANAGEMENT-SYSTEM; OF-CHARGE; CAPACITY ESTIMATION; ELECTRIC VEHICLES; SOC; PERFORMANCE; ENERGY;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a scheme for estimating the state of charge (SOC) of lithium-ion batteries is proposed based on an battery equivalent circuit model. The equivalent circuit model is simplified and the model parameters are treated as unknown values here. An extended Kalman filter (EKF) is designed to online estimate the model parameters and SOC of the battery with a saturation algorithm complemented to keep the estimation of the parameters in a suitable compact subset to improve the estimation performance. Experimental results are provided to demonstrate the performance of the proposed approach.
引用
收藏
页码：4012 / 4017
页数：6
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