Swarm intelligence based State-of-Charge optimization for charging Plug-in Hybrid Electric Vehicles

• 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/11903/1/ESS14023FU1.pdf; http://www.witpress.com/elibrary/wit-transactions-on-ecology-and-the-environment/206/33184; http://eprints.utp.edu.my/11903/
• Institution: Universiti Teknologi Petronas

Transportation electrification has undergone major changes since the last decade. Success of the smart grid with renewable energy integration solely depends upon the large-scale penetration of Plug-in Hybrid Electric Vehicles (PHEVs) for a sustainable and carbon-free transportation sector. One of the key performance indicators in the hybrid electric vehicle is the State-of-Charge (SoC), which needs to be optimized for the betterment of charging infrastructure using stochastic computational methods. In this paper, a newly emerged accelerated particle swarm optimization (APSO) technique was applied and compared with standard Particle swarm optimization (PSO), considering charging time and battery capacity. Simulation results obtained for maximizing the highly non-linear objective function indicate that APSO achieves some improvement in terms of best fitness and computation time.