Title :
Multi-objective parameter optimization of a series hybrid electric vehicle using evolutionary algorithms
Author :
Zhang, Bingzhan ; Chen, Zhihang ; Mi, Chris ; Murphey, Yi L.
Author_Institution :
Sch. of Mech. & Automotive Eng., Hefei Univ. of Technol., Hefei, China
Abstract :
Hybrid powertrain control strategy and component sizing significantly affect vehicle performance, fuel economy and emissions in hybrid vehicles. Recent research activities in this field show that component sizing and the control strategy are quite intertwined in such a way that concurrent optimization of component sizing and control strategy is warranted. In this paper, we study the total optimization problem in a series HEV and apply evolutionary algorithms to the optimization problem. We will show through experiments that the proposed optimization method has the capability of providing a set of trade-off optimal solutions among the fuel economy and various emissions.
Keywords :
evolutionary computation; hybrid electric vehicles; optimisation; evolutionary algorithms; fuel economy; multi-objective parameter optimization; series hybrid electric vehicle; Automotive engineering; Design optimization; Evolutionary computation; Fuel economy; Genetic algorithms; Hybrid electric vehicles; Mechanical power transmission; Optimization methods; Road vehicles; Sorting; Control Strategy; Hybrid Electric Vehicle; evolutional algorithms; multi-objective Optimization;
Conference_Titel :
Vehicle Power and Propulsion Conference, 2009. VPPC '09. IEEE
Conference_Location :
Dearborn, MI
Print_ISBN :
978-1-4244-2600-3
Electronic_ISBN :
978-1-4244-2601-0
DOI :
10.1109/VPPC.2009.5289749