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
Link To Document :
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