UAV Wing Design via Efficient Global Optimization

Effective wing design plays an important role in determining the flight performance of fixed-wing unmanned aerial vehicles (UAVs), which require basic aerodynamic principles. The process of engineering such aircraft is entrenched in navigating intricate computational challenges, especially in the realm of aerodynamics computation, mostly within computationnal fluid dynamics. This study utilizes of the Efficient Global Optimization (EGO) algorithm as a robust and innovative approach tailored to address the multi-faceted complexities inherent in UAV wing design. This study employs the Efficient Global Optimization (EGO) algorithm to solve the challenges inherent in UAV wing design. Implementing Latin Hypercube Sampling (LHS) strategically for experiment designing and adding sampling points guided by the Expected Improvement (EI) for single-objective optimization, the primary objective is to enhance the lift-to-drag ratio, a crucial metric defining overall operational efficiency. The solution of this method was obtained with aerodynamic evaluation performed through Vortex Lattice simulation in VSPAERO software. These design methodologies for optimizing UAV wing design focus on achieving an efficiency increase of up to 16.56% in the lift-to-drag ratio when compared to the initial rectangular wing configuration. This enhancement represents the efficacy of the proposed approach in enhancing UAV wing designs, contributing to improved flight performance.