A unified and experimentally validated design framework for long-endurance solar UAVS using model-based multi-objective multidisciplinary optimization

Abstract Designing long-endurance, solar-powered unmanned aerial vehicles (UAVs) requires careful coordination across aerodynamic, structural, and energy subsystems, particularly when targeting flexible, high-aspect-ratio configurations. This paper presents a mission-driven design and optimization framework for solar-powered long-endurance UAVs, tailored to post-disaster urban surveillance scenarios. A modular, multidisciplinary approach is adopted to account for the coupled effects of structural deformation and solar energy availability, both of which critically affect flight endurance. A key feature of the framework is the simultaneous integration of aeroelastic constraints and a time-dependent solar power and battery model, capturing realistic energy generation and storage behavior over diurnal cycles. This energy model is experimentally validated using a custom-built testbed and incorporated directly into the design loop. The framework is implemented using a Multidisciplinary Design Optimization (MDO) architecture that employs a coupling strategy to effectively manage interdependencies among subsystems. A comprehensive sensitivity analysis using Latin Hypercube Sampling highlights key performance-driving parameters. The final UAV design is fabricated and flight-tested, demonstrating the satisfaction of mission-level requirements derived from a simulated post-earthquake damage assessment in Adana, Türkiye. Battery state-of-charge, trajectory, and attitude data collected during flight tests demonstrate that the UAV operates in accordance with design predictions, despite environmental variability. The study highlights how the integration of validated subsystem models within an established optimization process can lead to reliable, application-specific solar UAV designs suitable for real-world deployment.