Akademik Veri Yönetim Sistemi
Journal of the Faculty of Engineering and Architecture of Gazi University, cilt.41, sa.1, ss.29-46, 2026 (SCI-Expanded, Scopus, TRDizin)
In this study, the Particle Swarm Optimization (PSO) algorithm was applied to optimize the design parameters of a solar-powered Low Altitude Long Endurance (LALE) class unmanned aerial vehicle (UAV). The main objective is to extend the flight duration beyond 24 hours while minimizing energy consumption and ensuring the system's energy balance conditions. Throughout the optimization process, variables such as wingspan, flight speed, mass, and battery capacity were evaluated, and outputs including required power, total electrical power, and energy demand were calculated. Considering Kayseri, a region in Türkiye with limited annual solar irradiance, the energy production capacity was modeled within realistic constraints. The PSO algorithm employed a penalty function under energy deficiency conditions to maintain solution validity. The results show that the required power was reduced to 62.47 W, the total electrical energy was optimized to approximately 8.46 MJ, and a balance between the battery and solar panel was achieved, making continuous flight feasible. This approach presents an efficient and applicable optimization method, particularly for the design of LALE-class solar-powered UAVs.