Rahman, Imran and Vasant, Pandian and Mahinder Singh, Balbir Singh and Abdullah-Al-Wadud, M. (2015) Swarm Intelligence-Based Optimization for PHEV Charging Stations. In: Handbook of Research on Swarm Intelligence in Engineering. IGI Global, pp. 374-405. ISBN 978-1-4666-8291-7
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Abstract
In this chapter, Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO) technique were applied for intelligent allocation of energy to the Plug-in Hybrid Electric Vehicles (PHEVs). Considering constraints such as energy price, remaining battery capacity, and remaining charging time, they optimized the State-of-Charge (SoC), a key performance indicator in hybrid electric vehicle for the betterment of charging infrastructure. Simulation results obtained for maximizing the highly nonlinear objective function evaluates the performance of both techniques in terms of global best fitness and computation time.
Item Type: | Book Section |
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Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Departments / MOR / COE: | Departments > Fundamental & Applied Sciences |
Depositing User: | Pandian Vasant |
Date Deposited: | 07 Oct 2016 01:42 |
Last Modified: | 07 Oct 2016 01:42 |
URI: | http://scholars.utp.edu.my/id/eprint/11901 |