Genetic Algorithm for UTS Plug-in Hybrid Electric Vehicle Parameter Optimization

Publisher:
University of Canterbury, Christchurch, New Zealand
Publication Type:
Conference Proceeding
Citation:
Proceedings of the 13th Asia-Pacific Vibration Conference (APVC 09), 2009, pp. 1 - 8
Issue Date:
2009-01
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This paper covers modeling, energy management strategy development, genetic algorithm (GA) optimization and simulation results based on the model of the UTS plug-in hybrid electric vehicle (PHEV). The UTS PHEV configuration consists of energy storage system, electric machine (EM), power control unit and internal combustion engine. The difference between the UTS PHEV and the conventional powertrain configurations is that the existing configurations need two EMs to function as the electric generator and motor, respectively, while the UTS PHEV needs only one EM to function as either a generator or electric motor in different time intervals specified by the energy management strategy and therefore, can save space, weight and cost. Extensive research has been conducted on the modeling and comparison of the new and existing powertrain configurations. The objective of this paper is to minimize the fuel consumption and greenhouse gas emissions by optimizing the powertrain parameters. The powertrain was simulated for a standard U.S environmental protection agency drive cycle, the highway drive cycle, and the optimization was performed by using the GA.
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