High Payload Fraction UAV Design and Performance Evaluation 2024-26-0442

Unmanned Aerial Vehicles (UAVs), or drones, are aerial platforms with diverse applications. Their design is shaped by specific constraints, driving a multidisciplinary, iterative process encompassing aerodynamics, structures, flight mechanics and other domains. This paper describes the design of a fixed-wing UAV tailored to competition requirements. The payload comprises golf balls with specific weight and dimensions. The requirements included maintaining a thrust-to-empty weight ratio below 1 and achieving a high payload fraction, calculated as the ratio of payload weight to total UAV weight. An optimization approach was introduced, altering the conventional UAV sizing process to enhance the payload fraction. This was achieved by adjusting the design points within the solution space derived from constraint analysis. Furthermore, a novel structural optimization method was applied, utilizing critical points from the V-n diagram as design points, where the primary emphasis was on reducing the airframe weight while ensuring an acceptable level of safety. The design of each component was done through a general iterative process, with the constraints being the requirements and the assumptions made in the sizing process. Aerodynamic coefficients were determined via the vortex particle wake method using flow5 software. A mathematical model, employing state space representation, assessed dynamic characteristics at the trim position. Stability analysis confirmed UAV stability in both static and dynamic conditions. Flight test of the prototype validated the design, demonstrating UAVs ability to achieve intended payload fraction with good controllability and stability. The UAVs superior performance, attributed to the trade-off performed between its size and the payload fraction while satisfying the performance constraints (takeoff distance, climb rate etc), surpasses similar commercially available fixed wing UAVs in payload fraction. Future work involves building the actual model and integrating autonomous flight modes