State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization

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 li...

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Main Authors:	Ismail, Nur Hazima Faezaa, Toha, Siti Fauziah
Format:	Conference or Workshop Item
Language:	English
Published:	2013
Subjects:	T175 Industrial research. Research and development
Online Access:	http://irep.iium.edu.my/34110/ http://irep.iium.edu.my/34110/1/ICSIMA_SOC_PSO_DR_Fauziah_MCT.pdf

id	iium-34110
recordtype	eprints
spelling	iium-341102014-01-13T04:04:11Z http://irep.iium.edu.my/34110/ State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization Ismail, Nur Hazima Faezaa Toha, Siti Fauziah T175 Industrial research. Research and development 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. 2013 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/34110/1/ICSIMA_SOC_PSO_DR_Fauziah_MCT.pdf Ismail, Nur Hazima Faezaa and Toha, Siti Fauziah (2013) State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization. In: 2013 IEEE International Conference on Smart Instrumentation, Measurement and Applications, 26-27 Nov 2013, Royal Bintang Kuala Lumpur.
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T175 Industrial research. Research and development
spellingShingle	T175 Industrial research. Research and development Ismail, Nur Hazima Faezaa Toha, Siti Fauziah State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization
description	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.
format	Conference or Workshop Item
author	Ismail, Nur Hazima Faezaa Toha, Siti Fauziah
author_facet	Ismail, Nur Hazima Faezaa Toha, Siti Fauziah
author_sort	Ismail, Nur Hazima Faezaa
title	State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization
title_short	State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization
title_full	State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization
title_fullStr	State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization
title_full_unstemmed	State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization
title_sort	state of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization
publishDate	2013
url	http://irep.iium.edu.my/34110/ http://irep.iium.edu.my/34110/1/ICSIMA_SOC_PSO_DR_Fauziah_MCT.pdf
first_indexed	2023-09-18T20:49:13Z
last_indexed	2023-09-18T20:49:13Z
_version_	1777409881065652224

State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization

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