The manuscript presents the conceptual design phase of an unmanned aerial vehicle, with the objective of a systems approach towards the integration of a hydrogen fuel-cell system and Li-ion batteries into an aerodynamically efficient platform representative of future aircraft configurations. Using a classical approach to aircraft design and a combination of low- and high-resolution computational simulations, a final blended wing body UAV was designed with a maximum take-off weight of 25 kg and 4 m wingspan. Preliminary aerodynamic and propulsion sizing demonstrated that the aircraft is capable of completing a 2 h long mission powered by a 650 W fuel cell, hybridized with a 100 Wh battery pack, and with a fuel quantity of 80 g of compressed hydrogen.

Coaxial rotor systems are appealing for multirotor drones, as they increase thrust without increasing the vehicle’s footprint. However, the thrust of a coaxial rotor system is reduced compared to having the rotors in line. It is of interest to increase the efficiency of coaxial systems, both to extend mission time and to enable new mission capabilities. While some parameters of a coaxial system have been explored, such as the rotor-to-rotor distance, the influence of rotor pitch is less understood. This work investigates how adjusting the pitch of the lower rotor relative to that of the upper one impacts the overall efficiency of the system. A methodology based on blade element momentum theory is extended to coaxial rotor systems, and in addition blade-resolved simulations using computational fluid dynamics are performed. A coaxial rotor system for a medium-sized drone with a rotor diameter of 71.12 cm is used for the study. Experiments are performed using a thrust stand to validate the methods. The results show that there exists a peak in total rotor efficiency (thrust-to-power ratio), and that the efficiency can be increased by 2% to 5% by increasing the pitch of the lower rotor. The work contributes to furthering our understanding of coaxial rotor systems, and the results can potentially lead to more efficient drones with increased mission time.