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...
| Main Authors: | , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/34110/ http://irep.iium.edu.my/34110/1/ICSIMA_SOC_PSO_DR_Fauziah_MCT.pdf |
| _version_ | 1848780857931726848 |
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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 |