M. Ing. / Solar powered UAV's have gained world wide attention with aircraft such as Solar Impulse and Quinetiq's Zephyr. UAV's in general are becomming increasingly popular, in 2006 80% of all US military ights over Iraq were UAV ights [38]. UAV's are the the most dynamic growth sector in the world aerospace industry having spent $3:4 billion in 2008 and is expected to be $5:8 billion in 2014. Solar Impulse has a budget of $94 million, Quinetiq has been awarded a $44:9 million contract to build 7 zephyrs. NASA has had several solar powered UAV projects. With advancements in solar and battery technologies solar powred UAV's are fast becomming a reality. The disadvantage of projects such as the Solar Impulse, Zephyr, Solong and Sky Sailor is they have extremely large budgets and have access to non commercial and highy specialized Chapter 1 | Problem Statement 10 products. The main purpose of the project is to develop a solar power system using only commercial products which can substancially increase the ight time of a UAV under sunny conditions. The project has several advantages: The project also provides a clean, green energy aspect. Because the energy provided by the solar cells is free and has no carbon footprint, the project is environmentally friendly; The project uses only commercially available products so it can easily be implemented and reproduced; The system developed for the project is not only limited to UAV's/ the project can be used in other applications such as Solar powered cars or robots. Due to the commercial nature of the big 4 solar aircraft information about their solar power systems is not easily available. The work presented here is an acedemic venture and will be freely available The project has many unknowns such as the size of the UAV, power requirements and available components. The research methodolgy used allows the unknowns to be determined using mathematical models and simulations. The models and simulations are further veri ed and altered accordingly to the actual implementation of the system. The project provides a step by step procedure to building a power system for a solar powered UAV. There are several building blocks in the project. Each building block forms a vital part of the system but can also be designed and implemented as a sigle entity. Only once each building block has achieved its own indavidual speci cations will they be integrated together to form the complete system. There are many risks and limitations within the project. The project is dependant on the type of UAV with respect to power requirements. Therefore the power system needs to provide as much solar power as possible to the UAV. If the available solar power is not su cient for level ight, the solar power must supliment the original power supply of the aircraft in a safe manner. There are many dangers when ying a UAV, if the UAV loses control it could potentially injure or even kill a person. Therefore outmost care needs to be taken to mitigate these risks. By the end of the project a solar power supply, capable of powering a UAV, will be delivered. With the given resources and the current state of technology the project should be a success.

An investigation was conducted into the feasibility of using an unconventional flight technique, asymmetric flight, to improve overall efficiency of solar aircraft. In this study, asymmetric flight is defined as steady level flight in a non-wings-level state in- tended to improve solar incidence angle. By manipulating aircraft orientation through roll angle, solar energy collection is improved but aerodynamic efficiency is worsened due to the introduction of additional trim drag. A point performance model was devel- oped to investigate the trade-off between improvement in solar energy collection and additional drag associated with asymmetric flight. A mission model with a focus on aircraft orbits was then developed via integration of the point performance model over a set of discrete points. It is shown that there is a non-zero bank angle where optimal net power is achieved for a given aircraft orientation, flight condition, and sun position. The study also shows that there is improvement in overall efficiency over conventional flight for various orbit shapes and winds aloft. This indicates that there is potential value in not only flight path planning, but also in orientation planning for solar aircraft.

Design optimization is a method that can be used to automate the design process to obtain better results. When applied to aeroelastic structures, design optimization often leads to the creation of highly flexible aeroelastic structures. There are, however, a number of conventional design procedures that must be modified when dealing with highly flexible aeroelastic structures. First, the deformed geometry must be the baseline for weight, structural, and stability analyses. Second, potential couplings between aeroelasticity and rigid-body dynamics must be considered. Third, dynamic analyses must be modified to handle large nonlinear displacements. These modifications to the conventional design process significantly increase the difficulty of developing an optimization framework appropriate for highly flexible aeroelastic structures. As a result, when designing these structures, often either gradient-free optimization is performed (which limits the optimization to relatively few design variables) or optimization is simply omitted from the design process. Both options significantly decrease the design exploration capabilities of a designer compared to a scenario in which gradient-based optimization is used. This dissertation therefore presents various contributions that allow gradient-based optimization to be more easily used to optimize highly flexible aeroelastic structures. One of our primary motivations for developing these capabilities is to accurately capture the design constraints of solar-regenerative high-altitude long-endurance (SR-HALE) aircraft. In this dissertation, we therefore present a SR-HALE aircraft optimization framework which accounts for the peculiarities of structurally flexible aircraft while remaining suitable for use with gradient-based optimization. These aircraft tend to be extremely large and light, which often leads to significant amounts of structural flexibility. Using this optimization framework, we design an aircraft that is capable of flying year-round at \SI{35}{\degree} latitude at \SI{18}{\kilo\meter} above sea level. We subject this aircraft to a number of constraints including energy capture, energy storage, material failure, local buckling, stall, static stability, and dynamic stability constraints. Critically, these constraints were designed to accurately model the actual design requirements of SR-HALE aircraft, rather than to provide a rough approximation of them. To demonstrate the design exploration capabilities of this framework, we also performed several parameters sweeps to determine optimal design sensitivities to altitude, latitude, battery specific energy, solar efficiency, avionics and payload power requirements, and minimum design velocity. Through this optimization framework, we demonstrate both the potential of gradient-based optimization applied to highly flexible aeroelastic structures and the challenges associated with it. One challenge associated with the gradient-based optimization of highly flexible aeroelastic structures, is the ability to accurately, efficiently, and reliably model the large deflections of these structures in gradient-based optimization frameworks. To enable large-scale optimization involving structural models with large deflections to be performed more easily, we present a finite-element implementation of geometrically exact beam theory which is designed specifically for gradient-based optimization. A key feature of this implementation of geometrically exact beam theory is its compatibility with forward and reverse-mode automatic differentiation, which allows accurate design sensitivities to be obtained with minimal development effort. Another key feature is its native support for unsteady adjoint sensitivity analysis, which allows design sensitivities to be obtained efficiently from time-marching simulations. Other features are also presented that build upon previous implementations of geometrically exact beam theory, including a singularity-free rotation parameterization based on Wiener-Milenkovi\'c parameters, an implementation of stiffness-proportional structural damping using a discretized form of the compatibility equations, and a reformulation of the equations of motion for geometrically exact beam theory from a fully implicit index-1 differential algebraic equation to a semi-explicit index-1 differential algebraic equation. Several examples are presented which verify the utility and validity of each of these features. Another challenge associated with the gradient-based optimization of highly flexible aeroelastic structures is the ability to reliably track and constrain individual dynamic stability modes across the design iterations of an optimization framework. To facilitate the development of mode-specific dynamic stability constraints in gradient-based optimization frameworks we develop a mode tracking method that uses an adaptive step size in order to maintain an arbitrarily high degree of confidence in mode correlations. This mode tracking method is then applied to track the modes of a linear two-dimensional aeroelastic system and a nonlinear three-dimensional aeroelastic system as velocity is increased. When used in a gradient-based optimization framework, this mode tracking method has the potential to allow continuous dynamic stability constraints to be constructed without constraint aggregation. It also has the potential to allow the stability and shape of specific modes to be constrained independently. Finally, to facilitate the development and use of highly flexible aeroelastic systems for use in gradient-based optimization frameworks, we introduce a general methodology for coupling aerodynamic and structural models together to form modular monolithic aeroelastic systems. We also propose efficient methods for computing the Jacobians of these coupled systems without significantly increasing the amount of time necessary to construct these systems. For completeness we also discuss how to ensure that the resulting system of equations constitutes a set of first-order index-1 differential algebraic equations. We then derive direct and adjoint sensitivities for these systems which are compatible with automatic differentiation so that derivatives for gradient-based optimization can be obtained with minimal development effort.