State of Charge Estimation of a Lithium-Ion Battery for Electric Vehicle based on Particle Swarm Optimization

被引：0
|
作者：
Ismail, Nur Hazima Faezaa [1 ]
Toha, Siti Fauziah [1 ]
机构：
[1] Int Islamic Univ Malaysia, Dept Mechatron, Fac Engn, Kuala Lumpur 50728, Malaysia
来源：
2013 IEEE INTERNATIONAL CONFERENCE ON SMART INSTRUMENTATION, MEASUREMENT AND APPLICATIONS (ICSIMA 2013) | 2013年
关键词：
State of Charge; LiFePO4; battery; electric vehicle; PSO;
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：
Lithium-ion battery plays important roles in electric drive vehicles. It has several advantages among other battery technologies such as high energy density and specific energy. The primary concerns of Lithium-ion batteries are to maintain optimum battery performance and extend the battery's life. An accurate state of charge (SOC) estimation can improve the performance of Lithium-ion battery. In this paper, a method for SOC estimation for LiFePO4 using the particle swarm optimization (PSO) algorithm is presented. The results indicate the SOC estimation using PSO optimized algorithm has good performance. The simulation result has also been validated and complies within specific confidence level.
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页数：4
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