Hybrid Swarm Intelligence-Based Optimization for Charging Plug-in Hybrid Electric Vehicle

Rahman, Imran and Vasant, Pandian and Mahinder Singh, Balbir Singh and Abdullah-Al-Wadud, M. (2015) Hybrid Swarm Intelligence-Based Optimization for Charging Plug-in Hybrid Electric Vehicle. In: 7th Asian Conference, ACIIDS 2015, Bali, Indonesia., March 23-25, 2015, Bali, Indonesia..

[img] PDF

Official URL: http://link.springer.com/chapter/10.1007%2F978-3-3...


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.

Item Type:Conference or Workshop Item (Paper)
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Academic Subject One:Mission Oriented Research - Green Technologies - Water - Natural gas - Optimization
Academic Subject Two:Academic Department - Electrical And Electronics - Instrumentation and Control - Robotics - Hybrid vehicle
Departments / MOR / COE:Departments > Fundamental & Applied Sciences
ID Code:11902
Deposited By: Pandian Vasant
Deposited On:07 Oct 2016 01:42
Last Modified:07 Oct 2016 01:42

Repository Staff Only: item control page

Document Downloads

More statistics for this item...