TY  - JOUR
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925271998&doi=10.1007%2f978-3-319-15705-4_3&partnerID=40&md5=31b697a6c60662babc3dba9cf02ee7f6
PB  - Springer Verlag
N1  - cited By 7; Conference of 7th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2015 ; Conference Date: 23 March 2015 Through 25 March 2015; Conference Code:115609
SP  - 22
TI  - Hybrid swarm intelligence-based optimization for charging plug-in hybrid electric vehicle
SN  - 03029743
ID  - scholars6369
A1  - Rahman, I.
A1  - Vasant, P.
A1  - Singh, B.S.M.
A1  - Abdullah-Al-Wadud, M.
Y1  - 2015///
AV  - none
N2  - Plug-in hybrid electric vehicle (PHEV) has the potential to facilitate the energy and environmental aspects of personal transportation, but face a hurdle of access to charging system. The charging infrastructure has its own complexities when it is compared with petrol stations because of the involvement of the different charging alternatives. As a result, the topic related to optimization of Plug-in hybrid electric vehicle charging infrastructure has attracted the attention of researchers from different communities in the past few years. Recently introduced smart grid technology has brought new challenges and opportunities for the development of electric vehicle charging facilities. This paper presents Hybrid particle swarm optimization Gravitational Search Algorithm (PSOGSA)-based approach for state-of-charge (SoC) maximization of plug-in hybrid electric vehicles hence optimize the overall smart charging. © Springer International Publishing Switzerland 2015.
VL  - 9012
JF  - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
KW  - Artificial intelligence; Charging (batteries); Database systems; Electric power transmission networks; Hybrid vehicles; Particle swarm optimization (PSO); Smart power grids; Vehicles
KW  -  Plug in hybrid electric vehicles; PSOGSA; Smart charging; State of charge; Swarm Intelligence
KW  -  Plug-in hybrid vehicles
EP  - 30
ER  -