A Semi-Markov Stochastic Model for Assessing Solar-Powered UAV Mission Feasibility Under High-Variability Conditions

This paper presents a generic stochastic simulation framework for evaluating the operational feasibility of solar-powered unmanned aerial vehicles (UAVs) executing an invariant trajectory in high-variability climates. Unlike conventional approaches relying on idealised irradiance conditions, the proposed framework combines a modified ASHRAE radiation model corrected for local bias and variability with a semi-Markov process modelling stochastic transitions between cloud and sunlight states using parametrised state duration times. The environmental model is further extended with diurnal temperature variation and standard atmosphere effects. UAV motion is represented using a rigid body flight dynamics model combined with a cascaded trajectory tracking controller and an energy subsystem incorporating a lithium-ion battery model. Warsaw (Dfb climate) is used as a representative Central European test case characterised by frequent radiation deficits and highly variable atmospheric conditions. The simulations quantify the influence of environmental uncertainty and selected battery capacities on mission success probability across different solar-to-wing area ratios, with the mission entry at 70% initial battery state of charge and no additional manoeuvre losses or external atmospheric perturbations. The evaluations were conducted for a fixed mission start at solar noon on 15 July and were supplemented by an optimised mission scheduling analysis to establish upper flight-time limits. The results demonstrate the strong sensitivity of solar-assisted UAV operations to stochastic cloud conditions and support the design and mission planning for low-altitude long-endurance aircraft.