DocumentCode
676257
Title
State of charge estimation of a Lithium-ion battery for electric vehicle based on particle swarm optimization
Author
Ismail, Nur Hazima Faezaa ; Toha, S.F.
Author_Institution
Dept. of Mechatron., Int. Islamic Univ. Malaysia, Kuala Lumpur, Malaysia
fYear
2013
fDate
25-27 Nov. 2013
Firstpage
1
Lastpage
4
Abstract
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.
Keywords
battery powered vehicles; lithium compounds; particle swarm optimisation; secondary cells; LiFePO4; PSO algorithm; SOC estimation; electric drive vehicle; high energy density; lithium-ion battery; optimum battery performance; particle swarm optimization; state of charge estimation; Batteries; Battery charge measurement; Estimation; Integrated circuit modeling; Mathematical model; Particle swarm optimization; System-on-chip; LiFePO4 battery; PSO; State of Charge; electric vehicle;
fLanguage
English
Publisher
ieee
Conference_Titel
Smart Instrumentation, Measurement and Applications (ICSIMA), 2013 IEEE International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4799-0842-4
Type
conf
DOI
10.1109/ICSIMA.2013.6717978
Filename
6717978
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