Swarm Intelligence Based State-of-Charge Optimization for Charging Plug-in Hybrid Electric Vehicles

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.

• Record URL:
  https://doi.org/10.2495/ESS140231
• Availability:
  • Find a library where document is available. Order URL: http://www.witpress.com/books/978-1-78466-095-6
• Supplemental Notes:
  • Abstract reprinted with permission from WIT Press.
• Corporate Authors:

  WIT Press

  Ashurst Lodge
  Ashurst, Southampton  United Kingdom  SO40 7AA
• Authors:
  • Rahman, I
  • Vasant, P M
  • Singh, B S M
  • Abdullah-Al-Wadud, M
• Conference:
  • 5th International Conference on Energy and Sustainability
  • Location: Putrajaya , Malaysia
  • Date: 2014-12-16 to 2014-12-18
• Publication Date: 2015

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 11p
• Monograph Title: Energy and Sustainability V: Special Contributions
• Serial:
  • WIT Transactions on Ecology and the Environment
  • Volume: 206
  • Publisher: WIT Press
  • ISSN: 1743-3541
  • Serial URL: http://www.witpress.com/elibrary/wit-transactions-on-ecology-and-the-environment

Subject/Index Terms

• TRT Terms: Battery chargers; Electric vehicle charging; Infrastructure; Optimization; Plug-in hybrid vehicles; Simulation; Stochastic processes; Sustainable development
• Candidate Terms: Smart grid
• Subject Areas: Energy; Environment; Vehicles and Equipment; I91: Vehicle Design and Safety;

Filing Info

• Accession Number: 01588469
• Record Type: Publication
• ISBN: 9781784660963
• Files: TRIS
• Created Date: Jan 28 2016 9:01AM