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In this paper, a new conceptual design methodology for a hybrid propulsion system consisting of the battery and hydrogen fuel cells is presented based on the minimum energy consumption of the UAV. In this context, an optimization problem with non-linear constraints is constituted to determine the wing loading, aspect ratio, stall velocity, endurance velocity, battery power, fuel cell power, maximum lift coefficient, and zero-lift drag coefficient of the UAV. The solution to this optimization problem, based on the UAV’s minimum energy consumption for the endurance and cruising flight modes, is implemented by meta-heuristic algorithms: particle swarm optimization, cuckoo search algorithm, artificial bee colony, and genetic algorithm. The results of these algorithms are compared in terms of energy consumption. This article contributes to the literature on sizing fuel cell-powered small UAVs based on minimum energy consumption and comparing different metaheuristics. According to the results, the lowest power consumption of the UAV is obtained by the particle swarm optimization algorithm as 2018.63 W. Additionally, the weight ratios calculated with the parameters obtained from the sizing optimization for the UAV propulsion system components and flight stages are compared with a benchmark study in the literature. Finally, the payload weight ratio is also increased by 28.5% by sizing optimization.

energy sources, part a: recovery, utilization, and environmental effects

Conceptual design and optimal sizing of a small unmanned aerial vehicle with fuel cell and battery-powered hybrid propulsion system by meta-heuristic algorithms based on energy consumption