Title :
Optimal drivetrain component sizing for a Plug-in Hybrid Electric transit bus using Multi-Objective Genetic Algorithm
Author :
Desai, Chirag ; Berthold, Florence ; Williamson, Sheldon S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, QC, Canada
Abstract :
Plug-in Hybrid Electric Vehicles (PHEVs) can significantly reduce petroleum consumption and the only difference from hybrid electric vehicles (HEVs) is the ability of PHEVs to use off-board electricity generation to recharge their energy storage system. The fuel economy of PHEV is highly dependent on All-Electric-Range (AER), drivetrain component size and control strategy parameter. In this study we consider PHEV version of parallel hybrid NOVA transit bus model developed with the Powertrain System Analysis Toolkit (PSAT). A genetic based derivative free algorithm called Multi-Objective Genetic Algorithm (MOGA) is used to optimize conflicting drivetrain and control strategy parameters. The AER, fuel economy, emissions and main performance constraints of the PHEVs will be compared for the initial design and final optimal design.
Keywords :
electric drives; energy storage; fuel economy; genetic algorithms; hybrid electric vehicles; petroleum; power transmission (mechanical); all electric range; control strategy parameters; energy storage system; fuel economy; multiobjective genetic algorithm; off-board electricity generation; optimal drive train component sizing; petroleum consumption; plug-in hybrid electric transit bus; powertrain system analysis toolkit;
Conference_Titel :
Electric Power and Energy Conference (EPEC), 2010 IEEE
Conference_Location :
Halifax, NS
Print_ISBN :
978-1-4244-8186-6
DOI :
10.1109/EPEC.2010.5697242