Multi Objective Optimization of Toyota Hybrid System Using Nondominated Sorting Ga

This paper is aimed to optimize the charge pattern and fuel consumption of a plug-in hybrid electric vehicle. The optimization objectives are handled in the structure of a multi objective problem. Non-dominated sorting genetic algorithm (NSGA-II) is used to simulate the multi -objective optimization problem. Pareto-optimal solution set is presented. The hybrid vehicle considered in this paper is Toyota Hybrid System (THS) which combines the benefits of the series and parallel hybrid vehicles. The two different driving cycles, US06 and SC03 are used for controlling strategy optimization. Simulation results show the effectiveness of proposed optimization strategy.

Keywords:

Particle swarm optimization , State of charge , Fuel consumption , Pptimization , Nondominated sorting genetic algorithm , Multi objective