Optimization of the component sizing for a plug-in hybrid electric vehicle using a genetic algorithm

Abstract

This paper describes a methodology to optimize the component sizes of a plug-in hybrid electric vehicle in a blended control strategy using a genetic algorithm. For this purpose, first, a fuzzy logic controller with two operating modes is developed for the energy management system of a parallel plug-in hybrid electric vehicle. Then, the battery requirements to drive the vehicle during the all-electric range are determined. In order to optimize the transmission components, multi-objective constrained optimization based on a genetic algorithm is developed, where the objective function consists of the weighted fuel consumption and the weighted exhaust emissions. Also, the driving performance requirements of the vehicle are considered as the constraint functions from which, when they exceed their allowable bounds, the penalty functions are evaluated and added to the objective function. Finally, the results of optimization of the component sizing in a blended control strategy are compared for the optimized data and their default component sizes. The simulation results demonstrate the effectiveness of the approach and noticeable reductions in the equivalent fuel consumption and in the exhaust emissions while ensuring a good longitudinal vehicle performance in various driving cycles.