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

• Main Authors: Rahman, Imran, Vasant, Pandian, Mahinder Singh, Balbir Singh, Abdullah-Al-Wadud, M.
• Format: Conference or Workshop Item
• Published: 2015
• Subjects: QA75 Electronic computers. Computer science; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utp.edu.my/11902/1/chp%253A10.1007%252F978-3-319-15705-4_3.pdf; http://link.springer.com/chapter/10.1007%2F978-3-319-15705-4_3; http://eprints.utp.edu.my/11902/
• Institution: Universiti Teknologi Petronas

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.