Abstract: The usage of multi-objective cost functions (MOCFs) in sizing and energy management strategy (EMS) of fuel cell hybrid electric vehicles (FCHEVs) has expanded due to the participation of multiple technological and economic disciplines. To better understand the impact of price fluctuation on the component size and EMS of an FCHEV, this article proposed a sensitivity analysis methodology. First, a two-step optimization approach that considers hydrogen consumption, system degradation, and trip cost is used to minimize a MOCF of the Can-Am Spyder electric motorcycle simulator. Then, an effect analysis is carried out for the cost-optimal results under two driving profiles to understand the link between cost variation and system performance. These simulations indicate that each might result in different system sizes and EMS compromise. After that, an online optimization EMS based on sequential quadratic programming is used on a reduced-scale hardware-in-the-loop configuration to evaluate the simulation results with varied weights. Experimental results indicate that when an adequate size is used for each pair of weights, the EMS results in a 6% decrease in the trip cost.