Design and Transition Optimization of Hybrid e-VTOL UAV

This study presents a Multidisciplinary Design Optimization (MDO) approach to the design of a Tilt-Rotor Unmanned Aerial Vehicle (UAV), focusing on improving stability and performance during the critical hover-to-cruise transition. The primary objective is to minimize All-Up Weight (AUW) and transition time, while accounting for the impact of external factors such as wind speed, altitude, and stall speed at each stage of flight. A MATLAB-based framework was developed to enable trajectory planning and optimize tilt angles, energy consumption, and transition rates across multiple phases. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) were implemented and compared, with PSO managing constrained optimization through penalty functions, and GA employing a multi-objective approach to maximize Pareto front diversity. Simulation results showed that both algorithms yielded similar optimal configurations, demonstrating their effectiveness in solving UAV MDO problems with complex stability and control requirements. The optimized trajectory and tilt control strategy achieved significant improvements in stability and efficiency, marking a robust solution for UAV applications requiring seamless hover-to-cruise transitions.