Optimal Power Allocation Scheme for Plug-in Hybrid Electric Vehicles using Swarm Intelligence Technique

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Bibliographic Details
Main Author: Rahman, Imran
Format: Thesis
Published: 2016
Subjects:
Online Access:http://utpedia.utp.edu.my/id/eprint/25290/
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id oai:utpedia.utp.edu.my:25290
record_format eprints
spelling oai:utpedia.utp.edu.my:252902023-09-26T09:07:18Z http://utpedia.utp.edu.my/id/eprint/25290/ Optimal Power Allocation Scheme for Plug-in Hybrid Electric Vehicles using Swarm Intelligence Technique Rahman, Imran Q Science (General) 2016 Thesis NonPeerReviewed Rahman, Imran (2016) Optimal Power Allocation Scheme for Plug-in Hybrid Electric Vehicles using Swarm Intelligence Technique. Masters thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
topic Q Science (General)
spellingShingle Q Science (General)
Rahman, Imran
Optimal Power Allocation Scheme for Plug-in Hybrid Electric Vehicles using Swarm Intelligence Technique
format Thesis
author Rahman, Imran
author_facet Rahman, Imran
author_sort Rahman, Imran
title Optimal Power Allocation Scheme for Plug-in Hybrid Electric Vehicles using Swarm Intelligence Technique
title_short Optimal Power Allocation Scheme for Plug-in Hybrid Electric Vehicles using Swarm Intelligence Technique
title_full Optimal Power Allocation Scheme for Plug-in Hybrid Electric Vehicles using Swarm Intelligence Technique
title_fullStr Optimal Power Allocation Scheme for Plug-in Hybrid Electric Vehicles using Swarm Intelligence Technique
title_full_unstemmed Optimal Power Allocation Scheme for Plug-in Hybrid Electric Vehicles using Swarm Intelligence Technique
title_sort optimal power allocation scheme for plug-in hybrid electric vehicles using swarm intelligence technique
publishDate 2016
url http://utpedia.utp.edu.my/id/eprint/25290/
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score 13.160551