Fuel cell trucks (FCTs) have obtained favors and rapid development due to relatively fixed route and fewer infrastructure requirements. However, high cost including powertrain capital cost and operation cost still prevents large scale commercialization of FCTs. This paper proposes a nested powertrain component size design method using genetic algorithm (GA) and dynamic programming (DP) to optimize vehicle powertrain component size and energy management actions. Firstly, considering changeable powertrain mass caused by various size parameters, the initial size parameters range of fuel cell rated power and battery energy capacity can be determined with the premise of satisfying all vehicle power demand. Due to temporary vehicle high-power demand, the vehicle powertrain can satisfy temporary vehicle high-power demand with smaller power source size due to the rapid dynamics and high specific power of battery. Finally, the inner loop implements energy management by DP and the outer loop seeks the optimal size parameters by GA until obtaining the optimal powertrain component size. The results show that the proposed component size design scheme can obtain optimal powertrain configuration, the size optimization design results of different objective functions are compared and analyzed. Compared with objective function not including component degradation cost, the powertrain configuration of objective function minimizing total operation cost can save operation cost by 1.41%-8.04% under different driving cycles. The universality is verified by applying the proposed method in a plug-in fuel cell vehicle, the proposed optimization scheme can save vehicle operation cost by 27.14%, 39.35% and 49.90% under three driving cycles compared with simultaneous approach, which proves the superiority of the proposed method. In addition, the analyses of operation cost influenced by size parameters under different operation conditions are conducted to provide references to select powertrain component size according to distinct demand.