Estimation for SOC of Li-ion battery based on two-order RC temperature model

被引：0
|
作者：
Zhang, Qun-Zhi [1 ]
Wang, Xin-Yue [1 ]
Yuan, Hui-Mei [1 ]
机构：
[1] Capital Normal Univ, Informat Engn Coll, Beijing, Peoples R China
来源：
PROCEEDINGS OF THE 2018 13TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2018) | 2018年
关键词：
Li-ion battery; Battery model; State of Charge; Extended Kalman Particle Filter;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
With energy and environmental problems getting more and more seriously, electric vehicles (EVs) have attracted great attention at home and abroad. This paper mainly studies the battery model and State of Charge (SOC) estimation of EVs. Based on the traditional two-order RC circuit equivalent model, a new two-order RC model considering temperature factor is proposed, and the Extended Kalman Particle Filter (EKPF) algorithm is used to estimate the SOC of battery. Experimental results show that, the two-order RC temperature model has high accuracy, it can simulate the battery state at different temperatures and has a certain practical value.
引用
收藏
页码：2601 / 2606
页数：6
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