Genetic algorithm based optimal powertrain component sizing and control strategy design for a fuel cell hybrid electric bus

Recent trends shows that hydrogen powered fuel cell vehicles (FCVs) are gaining universal attention, because of the need for more fuel-efficient vehicles. Advancement in fuel-cell technology has ignited interest in all-electric propulsion systems. Regardless of some drawbacks in terms of number of electrical storage components being used and relatively larger capacity of on-board energy storage required, compared to hybrid electric vehicles, all-electric propulsion systems offer the most effective solution for achieving zero emissions drive-trains. Both the sizing of powertrain components as well as the control strategy affects vehicle performance, due to their interdependency. Moreover, during sizing, various design constraints should also be satisfied simultaneously. Hence, optimization of fuel cell vehicle components can be simply treated as a multi-objective constrained nonlinear optimization. This paper considers a fuel cell powered electric transit bus, with battery and ultracapacitor as additional sources of power, to improve the overall drive performance and efficiency. Optimal sizing of the powertrain components is carried out, in conjunction with optimizing the overall control strategy design, through a suitably devised multi objective genetic algorithm method. The main goal is to achieve higher fuel economy with minimum power train cost.