relation: https://khub.utp.edu.my/scholars/11122/
title: Hybrid particle swarm and gravitational search optimization techniques for charging plug-in hybrid electric vehicles
creator: Rahman, I.
creator: Vasant, P.
creator: Singh, B.S.M.
creator: Abdullah-Al-Wadud, M.
description: Electrification of Transportation has undergone major modifications since the last decade. Success of combining smart grid technology and renewable energy exclusively depends upon the large-scale participation of Plug-in Hybrid Electric Vehicles (PHEVs) towards reach the desired pollution-free transportation industry. One of the key Performance pointers of hybrid electric vehicle is the State-of-Charge (SoC) which needs to be enhanced for the advancement of charging station using computational intelligence methods. In this Chapter, authors applied Hybrid Particle swarm and gravitational search Optimization (PSOGSA) technique for intelligently allocating energy to the PHEVs considering constraints such as energy price, remaining battery capacity, and remaining charging time. Computational experiment results attained for maximizing the highly non-linear fitness function estimates the performance measure of both the techniques in terms of best fitness value and computation time. © 2020, IGI Global. © 2020 by IGI Global. All rights reserved.
publisher: IGI Global
date: 2019
type: Book
type: PeerReviewed
identifier:   Rahman, I. and Vasant, P. and Singh, B.S.M. and Abdullah-Al-Wadud, M.  (2019) Hybrid particle swarm and gravitational search optimization techniques for charging plug-in hybrid electric vehicles.     IGI Global, pp. 195-228.  ISBN 9781799809494; 9781799809487     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095762083&doi=10.4018%2f978-1-7998-0948-7.ch008&partnerID=40&md5=b1911768f3d1e4b4762d0e019ba3b843
relation: 10.4018/978-1-7998-0948-7.ch008
identifier: 10.4018/978-1-7998-0948-7.ch008