Optimal Endurance Prediction for a Battery-Powered Unmanned Aerial Vehicle with High Aspect Ratio Wings

Due to the limitation of the battery technology and the efficiency of propulsion systems, the flight time of a typical unmanned aerial vehicle is significantly reduced. By optimising the aerodynamic features of the aircraft, there is still some design space for improvement of the endurance. By achieving more efficient aerodynamic features, higher endurance can be achieved without significantly increasing battery capacity, and this can help save energy. On the other hand, longer endurance helps reduce recharging times and improve the flight mission radius, which enables the UAV to perform better in critical missions. This research work focuses on the implementation of a bi-fidelity optimization approach to endurance prediction and improvement of a battery-powered UAV. A 1D analytical code for endurance estimation is integrated with high-fidelity CFD simulations of UAV lift-to-drag predictions. At cruise flight conditions, an optimum endurance of 2.41 hours was achieved by optimising the aerodynamic features of the UAV compared with the only analytical method of 2.22 hours for fixed power system and constant weight. It was observed that winglets with large cant angles showed poor performance in providing lift and were only able to provide comparatively higher lift-to-drag ratio at large angles of attack. Moreover, the tail, in comparison with the wing, was not efficient in providing lift mostly due to the main wing wakes. final wing design of this U A V was a partially tapered wing with a straight winglet, which provided the highest lift coefficient and lift-to-drag ratio.