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: Proceeding Paper
Language:English
Published: 2013
Subjects:
Online Access:http://irep.iium.edu.my/34110/
http://irep.iium.edu.my/34110/1/ICSIMA_SOC_PSO_DR_Fauziah_MCT.pdf
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author Ismail, Nur Hazima Faezaa
Toha, Siti Fauziah
author_facet Ismail, Nur Hazima Faezaa
Toha, Siti Fauziah
author_sort Ismail, Nur Hazima Faezaa
building IIUM Repository
collection Online Access
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.
first_indexed 2025-11-14T15:40:20Z
format Proceeding Paper
id iium-34110
institution International Islamic University Malaysia
institution_category Local University
language English
last_indexed 2025-11-14T15:40:20Z
publishDate 2013
recordtype eprints
repository_type Digital Repository
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 Proceeding Paper 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.
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
title 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_short 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
topic T175 Industrial research. Research and development
url http://irep.iium.edu.my/34110/
http://irep.iium.edu.my/34110/1/ICSIMA_SOC_PSO_DR_Fauziah_MCT.pdf