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Swarm Intelligence-Based Optimization for PHEV Charging Stations

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
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:11901
Deposited By: Pandian Vasant
Deposited On:07 Oct 2016 01:42
Last Modified:07 Oct 2016 01:42

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