Integrated Power Modeling for a Solar-Powered, Computationally-Intensive Unmanned Aircraft

In recent years, we have seen an uptrend in the popularity of UAVs driven by the desire to apply these aircraft to areas such as precision farming, infrastructure and environment monitoring, surveillance, surveying and mapping, search and rescue missions, weather forecasting, and more. The traditional approach for small size UAVs is to capture data on the aircraft, stream it to the ground through a high power data-link, process it remotely (potentially off-line), perform analysis, and then relay commands back to the aircraft as needed. Given the finite energy resources found onboard an aircraft (battery or fuel), traditional designs greatly limit aircraft endurance since significant power is required for propulsion, actuation, and the continuous transmission of visual data. All the mentioned application scenarios would benefit by carrying a high performance embedded computer system to minimize the need for data transmission. A major technical hurdle to overcome is that of drastically reducing the overall power consumption of these UAVs so they can be powered by solar arrays, and for long periods of time. This paper describes an integrated power model for a solar-powered, computationally-intensive unmanned aircraft that includes power models for solar generation, aircraft propulsion, and avionics. These power consumption and generation models are described, derived, and integrated into a cohesive system-wide aircraft power model that is presented in the form of a systemic flow diagram. Power balance expressions are also imposed based on temporal and physical constraints. Compared to works in the existing literature, the integrated model presented follows a holistic approach for UAV modeling that encompasses aircraft, propulsion, and solar models under realistic assumptions. Additionally, in order to enable high fidelity estimation while requiring minimal computation power, the model was developed to estimate the power consumption and generation based on flight path state, without needing precise aerodynamic measurements, e.g. angle-of-attack. Several of the methods have already been evaluated by means of ground and flight testing, as well as simulation, and showed errors ranging from negligible to approximately 5%. The motivation behind this work is the development of computationally-intensive, long-endurance solar-powered unmanned aircraft, the UIUC Solar Flyer, which will have continuous daylight ability to acquire and process high resolution visible and infrared imagery. Therefore, having a holistic integrated power model that can encompass power generation and consumption allows further aircraft and mission design and optimization can be performed.