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18-05-2019

Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle

Authors: Pandian Vasant, Jose Antonio Marmolejo, Igor Litvinchev, Roman Rodriguez Aguilar

Published in: Wireless Networks | Issue 7/2020

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Abstract

Currently, there is a remarkable focus on green technologies for taking steps towards more use of renewable energy sources within the sector of transportation and also decreasing pollution. At this point, employment of plug-in hybrid electric vehicles (PHEVs) needs sufficient charging allocation strategy, by running smart charging infrastructures and smart grid systems. In order to daily usage of PHEVs, daytime charging stations are required and at this point, only an appropriate charging control and a management of the infrastructure can lead to wider employment of PHEVs. In this study, four swarm intelligence based optimization techniques: particle swarm optimization (PSO), gravitational search algorithm (GSA), accelerated particle swarm optimization, and hybrid version of PSO and GSA (PSOGSA) have been applied for the state-of-charge optimization of PHEVs. In this research, hybrid PSOGSA has performed very well in producing better results than other stand-alone optimization techniques.

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Title: Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle
Authors: Pandian Vasant
Jose Antonio Marmolejo
Igor Litvinchev
Roman Rodriguez Aguilar
Publication date: 18-05-2019
Publisher: Springer US
Published in: Wireless Networks / Issue 7/2020
Print ISSN: 1022-0038
Electronic ISSN: 1572-8196
DOI: https://doi.org/10.1007/s11276-019-01993-w

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