Today, the electrification of flight is more popular than ever, creating a wide array of concept aircraft and associated power system topologies. In order to gain insights into benefits of these varying architectures, this paper introduces the development of a framework for electric aircraft power system (EAPS) optimization. The proposed framework accepts inputs from a designer in the form of component parameters and desired flight mission characteristics. A collective graph representing many possible architectures is formed, from which, subgraphs that describe power system topologies meeting the flight requirements are extracted and analyzed. Optimal EAPS architectures with respect to goals of minimizing mass while maximizing efficiency and reliability can be subsequently selected from these subgraphs. The framework is exemplified on a 500kW rated aircraft using data collected from surveys of component parameters such as power density and efficiency. The presented results show a comparative analysis of different EAPS types with respect to the competing performance metrics of mass, efficiency, and survivability.

Document Type


Publication Date


Notes/Citation Information

Published in IEEE Transactions on Transportation Electrification.

© 2021 IEEE Copyright Notice. “Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”

The document available for download is the authors’ final manuscript version. The final published version is copyrighted by IEEE and is available as: D. Lawhorn, V. Rallabandi, and D. M. Ionel, “Multi-objective Optimization for Aircraft Power Systems using a Graph Network Representation,” in IEEE Transactions on Transportation Electrification, doi: 10.1109/TTE.2021.3066123.

Digital Object Identifier (DOI)


Funding Information

The support of this research by the National Aeronautics and Space Administration, through the NASA Grant no. KY GF-19-051, is gratefully acknowledged.