IJSRP, Volume 5, Issue 11, November 2015 Edition [ISSN 2250-3153]
El-Said A. Othman, Sherif K. Nawar, Faten H. Fahmy, Abd El-Shafy A. Nafeh
This paper, will present a two optimization techniques (genetic algorithm (GA) and particle swarm optimization (PSO)) are adopted to optimize the sizing of a power train for a fuel cell electric vehicle (FCEV). The power train comprised of a fuel cell as the main energy source to supply the vehicle power demand during steady state, battery and supercapacitor as the auxiliary energy storage sources (ESS). It assist the FC during transient state and recovers the energy during braking or deaccelaration. The optimization objective is to achieve the minimum cost, volume, and weight of the power train. Because of a hybrid powertrain, component sizing significantly affects vehicle performance, hence taking into account the constraints of vehicle performance, such as the energy characteristics, power limitations and a DC-link voltage. Optimal sizing of the power train components using GA and PSO algorithms will be presented. Moreover, the calculation and the analysis of the vehicle dynamics and detailed model of the power train is built in MATLAB /SIMULINK.