<p dir="ltr">The electrification of pneumatic or hydraulic system on aircraft has been shown effective in reducing the fuel burn. Recently, electrifying propulsive loads has attracted a lot of atten- tion to further improve fuel economy. This work focuses on tools to facilitate more electric aircraft at conceptual design stage, particularly assuming a turbo-generator architecture. Specifically, we develop a simulation tool, mimicking SUAVE [1], which allows mission and fuel burn analysis. Major differences from SUAVE include more detailed models of compo- nents in the electric propulsive branch and degrees of freedom to adjust the velocity profile along the entire mission. Based on the simulator, this work further proposes to leverage a gradient-free optimization technique, which optimizes the optimal velocity profile along the entire mission to minimize fuel burn. Simulation results on two aircraft designs, a con- ventional Boeing 737-800 and NASA-STARC-ABL, verify the effectiveness of the proposed tools.</p>

This thesis proposes an advanced architecting methodology. This methodology allows for the sizing and optimization of aircraft system architecture concepts and the establishment of subsystem development strategies. The process is implemented by an architecting team composed of subsystem experts and architects. The methodology organizes the architecture definition using the SysML language. Using meta-modeling techniques, this definition is translated into an analysis model which automatically integrates subsystem analyses in a fashion that represents the specific architecture concept described by the team. The resulting analysis automatically sizes the subsystems composing it, synthesizes their information to derive architecture-level performance and explores the architecture internal trade-offs. This process is facilitated using the Coordinated Optimization method proposed in this dissertation. This method proposes a multi-level optimization setup. An architecture-level optimizer orchestrates the subsystem sizing optimizations in order to optimize the aircraft as whole. The methodologies proposed in this thesis are tested and demonstrated on a proof of concept based on the exploration of turbo-electric propulsion aircraft concepts.

Recently, the environmental impact of aircraft and rising fuel prices have become an increasing concern in the aviation industry. To address these problems, organizations such as NASA have set demanding goals for reducing aircraft emissions, fuel burn, and noise. In an effort to reach the goals, a movement toward more-electric aircraft and electric propulsion has emerged. With this movement, the number of critical electrical loads on an aircraft is increasing causing power system reliability to be a point of concern. Currently, power system reliability is maintained through the use of back-up power supplies such as batteries and ram-air-turbines (RATs). However, the increasing power requirements for critical loads will quickly outgrow the capacity of the emergency devices. Therefore, reliability needs to be addressed when designing the primary power distribution system. Power system reliability is a function of component reliability and redundancy. Component reliability is often not determined until detailed component design has occurred; however, the amount of redundancy in the system is often set during the system architecting phase. In order to meet the capacity and reliability requirements of future power distribution systems, a method for redundancy allocation during the system architecting phase is needed. This thesis presents an aircraft power system design methodology that is based upon the engineering decision process. The methodology provides a redundancy allocation strategy and quantitative trade-off environment to compare architecture and technology combinations based upon system capacity, weight, and reliability criteria. The methodology is demonstrated by architecting the power distribution system of an aircraft using turboelectric propulsion. The first step in the process is determining the design criteria which includes a 40 MW capacity requirement, a 20 MW capacity requirement for the an engine-out scenario, and a maximum catastrophic failure rate of one failure per billion flight hours. The next step is determining gaps between the performance of current power distribution systems and the requirements of the turboelectric system. A baseline architecture is analyzed by sizing the system using the turboelectric system power requirements and by calculating reliability using a stochastic flow network. To overcome the deficiencies discovered, new technologies and architectures are considered. Global optimization methods are used to find technology and architecture combinations that meet the system objectives and requirements. Lastly, a dynamic modeling environment is constructed to study the performance and stability of the candidate architectures. The combination of the optimization process and dynamic modeling facilitates the selection of a power system architecture that meets the system requirements and objectives.