Title :
A fuzzy - genetic algorithm approach for finding a new HEV control strategy idea
Author :
Nejhad, Arash Zargham ; Asaei, Behzad
Author_Institution :
Department of Electrical and Computer Engineering, University of Tehran, P.O. Box 14395-515, Iran
Abstract :
In this paper, a novel control strategy for hybrid electric vehicles (HEVs) is presented. The proposed method is based on global optimization for energy management system of a conventional parallel HEV. A rule based fuzzy control strategy is considered for optimization of the system. The fuzzy membership function boundaries are kept constant and the fuzzy rule table is optimized by using genetic algorithm for different types of cycles. The results of the proposed optimization method suggest that fixing the internal combustion engine (ICE) torque constant is prior to keeping the state of charge (SOC) of the batteries constant. It confirms that the electric machine should provide dynamic power of the load and static power should be supplied by the ICE.
Keywords :
Batteries; Electric machines; Energy management; Fuzzy control; Genetic algorithms; Hybrid electric vehicles; Ice; Internal combustion engines; Optimization methods; Torque; Fuzzy; Genetic algorithm; Hybrid electric vehicle; control strategy;
Conference_Titel :
Power Electronic & Drive Systems & Technologies Conference (PEDSTC), 2010 1st
Conference_Location :
Tehran, Iran
Print_ISBN :
978-1-4244-5944-5
DOI :
10.1109/PEDSTC.2010.5471825