High-Fidelity Solar Power Income Modeling for Solar-Electric UAVs: Development and Flight Test Based Verification
This work addresses the need for accurate solar power prediction in UAV design and operations, offering a domain-specific improvement over highly simplified existing models.
The authors tackled the problem of inaccurate solar power modeling for solar-electric UAVs by developing a high-fidelity model that accounts for aircraft attitude, geometry, and physical effects, achieving an error of less than 5% in predicting average solar power income compared to previous models with about 18% error.
Solar power models are a crucial element of solar-powered UAV design and performance analysis. During the conceptual design phase, their accuracy directly relates to the accuracy of the predicted performance metrics and thus the final design characteristics of the solar-powered UAV. Likewise, during the operations phase of a solar-powered UAV accurate solar power income models are required to predict and assess the solar power system performance. However, the existing literature on solar-powered UAVs uses highly simplified solar power models. This technical report therefore, first, introduces a high-fidelity solar power model that takes into account the exact aircraft attitude, aircraft geometry, and physical effects such as temperature and the sun radiation's angle-of-incidence that influence the overall solar power system efficiency. Second, models that require a reduced set of input data and are thus more appropriate for the initial design phase of solar-powered UAVs are derived from the high-fidelity model. Third, the models are compared and verified against flight data from a 28-hour continuous day/night solar-powered flight. The results indicate that our high-fidelity model allows a prediction of the average solar power income with an error of less than 5% whereas previous models were only accurate to about 18%.