Application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management

Energy management system is an area of emerging interest in a full electric vehicle research. With the increasing moves to a more sustainable vehicle, there is a need to extend the battery range that simultaneously satisfying the conflicting demand between battery capacity and vehicle weight or volu...

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Main Authors: Tengku Mohd, Tengku Azman, Hassan, Mohd Khair, Aris, Ishak, Che Soh, Azura, Ksm Kader Ibrahim, Babul Salam
Format: Article
Language:English
Published: Indonesian Society for Knowledge and Human Development 2017
Online Access:http://psasir.upm.edu.my/id/eprint/60908/1/Application%20of%20fuzzy%20logic%20in%20multi-mode%20driving%20for%20a%20battery%20electric%20vehicle%20energy%20management.pdf
http://psasir.upm.edu.my/id/eprint/60908/
https://pdfs.semanticscholar.org/79cb/f4bed81459277b5ab04ade18b62c08fc92e0.pdf
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Institution: Universiti Putra Malaysia
Language: English
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spelling my.upm.eprints.609082019-03-25T08:25:31Z http://psasir.upm.edu.my/id/eprint/60908/ Application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management Tengku Mohd, Tengku Azman Hassan, Mohd Khair Aris, Ishak Che Soh, Azura Ksm Kader Ibrahim, Babul Salam Energy management system is an area of emerging interest in a full electric vehicle research. With the increasing moves to a more sustainable vehicle, there is a need to extend the battery range that simultaneously satisfying the conflicting demand between battery capacity and vehicle weight or volume. This paper presents a research conducted in the Universiti Putra Malaysia, focusing on the energy management strategy of a battery-powered electric vehicle. Three vehicle driving modes; sport, comfort, and eco have been individually modelled. Each mode is capable to dominate different driving environments; highway, suburban, and urban. In European driving cycle simulation test, comfort and eco modes have shown large extension in driving range with the maximum of 7.33% and 19.70% respectively. However the speeds have been confined by certain specific limits. The proposed of integrated multi-mode driving using fuzzy logic has enabled an adaptive driving by automatically select the driving parameters based on the speed conditions. The results have proven its ability in reducing the energy consumption as much as 32.25%, and increasing the driving range of 4.21% without downgrading the speed performance. Indonesian Society for Knowledge and Human Development 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/60908/1/Application%20of%20fuzzy%20logic%20in%20multi-mode%20driving%20for%20a%20battery%20electric%20vehicle%20energy%20management.pdf Tengku Mohd, Tengku Azman and Hassan, Mohd Khair and Aris, Ishak and Che Soh, Azura and Ksm Kader Ibrahim, Babul Salam (2017) Application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management. International Journal on Advanced Science, Engineering and Information Technology, 7 (1). 284 - 290. ISSN 2088-5334; ESSN: 2460-6952 https://pdfs.semanticscholar.org/79cb/f4bed81459277b5ab04ade18b62c08fc92e0.pdf 10.18517/ijaseit.7.1.1960
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Energy management system is an area of emerging interest in a full electric vehicle research. With the increasing moves to a more sustainable vehicle, there is a need to extend the battery range that simultaneously satisfying the conflicting demand between battery capacity and vehicle weight or volume. This paper presents a research conducted in the Universiti Putra Malaysia, focusing on the energy management strategy of a battery-powered electric vehicle. Three vehicle driving modes; sport, comfort, and eco have been individually modelled. Each mode is capable to dominate different driving environments; highway, suburban, and urban. In European driving cycle simulation test, comfort and eco modes have shown large extension in driving range with the maximum of 7.33% and 19.70% respectively. However the speeds have been confined by certain specific limits. The proposed of integrated multi-mode driving using fuzzy logic has enabled an adaptive driving by automatically select the driving parameters based on the speed conditions. The results have proven its ability in reducing the energy consumption as much as 32.25%, and increasing the driving range of 4.21% without downgrading the speed performance.
format Article
author Tengku Mohd, Tengku Azman
Hassan, Mohd Khair
Aris, Ishak
Che Soh, Azura
Ksm Kader Ibrahim, Babul Salam
spellingShingle Tengku Mohd, Tengku Azman
Hassan, Mohd Khair
Aris, Ishak
Che Soh, Azura
Ksm Kader Ibrahim, Babul Salam
Application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management
author_facet Tengku Mohd, Tengku Azman
Hassan, Mohd Khair
Aris, Ishak
Che Soh, Azura
Ksm Kader Ibrahim, Babul Salam
author_sort Tengku Mohd, Tengku Azman
title Application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management
title_short Application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management
title_full Application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management
title_fullStr Application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management
title_full_unstemmed Application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management
title_sort application of fuzzy logic in multi-mode driving for a battery electric vehicle energy management
publisher Indonesian Society for Knowledge and Human Development
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/60908/1/Application%20of%20fuzzy%20logic%20in%20multi-mode%20driving%20for%20a%20battery%20electric%20vehicle%20energy%20management.pdf
http://psasir.upm.edu.my/id/eprint/60908/
https://pdfs.semanticscholar.org/79cb/f4bed81459277b5ab04ade18b62c08fc92e0.pdf
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