SOC Estimation of Li-Ion Battery Based on Unscented Kalman Filter

被引：0
|
作者：
Li, Zheng [1 ]
Chen, Qiushuo [1 ]
Yue, Feihong [1 ]
Zhang, Yan [1 ]
机构：
[1] Hebei Univ Sci & Technol, Sch Elect Engn, Shijiazhuang 050018, Hebei, Peoples R China
来源：
2018 21ST INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS) | 2018年
基金：
中国国家自然科学基金;
关键词：
li-ion battery model; SOC Online estimation; Unscented Kalman 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：
The accurately estimating the battery charging state is a key problem in battery management system. In this paper, an adaptive lithium-ion battery (SOC) estimation method is presented based on the the Unscented Filter(UKF). The common equivalent circuit model is enhanced, which includes the effect of different discharge rate and temperature on SOC. The SOC estimation algorithm is improved and verified in different types of lithium-ion batteries. An adaptive joint estimation of the battery SOC is then presented to enhance system robustness with battery aging. The results show that this method can provide accurate SOC estimation and high computational efficiency, which is suitable for the embedded system applications.
引用
收藏
页码：2177 / 2182
页数：6
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