University of Illinois Urbana-Champaign

System-level optimization of high-specific-power electric machines for aircraft propulsion applications

Bose, Anubhav

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https://hdl.handle.net/2142/120464

Description

Title
System-level optimization of high-specific-power electric machines for aircraft propulsion applications
Author(s)
Bose, Anubhav
Issue Date
2023-05-04
Director of Research (if dissertation) or Advisor (if thesis)
Haran, Kiruba
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
  • Electric Motors
  • Aircraft Electric Propulsion
Abstract
High Specific Power and High Efficiency electric machines, particularly in the megawatt class of power, are considered to be key enabling technologies for aircraft electric propulsion. Future aircraft are expected to have a much greater degree of electrification in the propulsion powertrain, which necessitates the development of large electric machines specifically tailored for that purpose. Additionally, weight is at a premium inside an aircraft, which necessitates that the electric powertrain be as light and efficient as possible to maximize the benefits of electrification. Due to the specialized nature of aerospace propulsion applications, it is imperative that electric machines are specifically designed to fit the particular needs of the specific aircraft. Additionally, the motor needs to integrate seamlessly into the rest of the electric powertrain and the aircraft structure and thermal management systems. Thus, the machine design process needs to account for the considerations derived from these other systems & structures. Developing a motor design & optimization framework that accounts for these considerations is one of the objectives of this thesis work, and the model development, optimization process, and key insights are discussed in the next chapters. The initial results from this design & optimization process indicate that significant gains in the power density & efficiency of the electric machine can be achieved over the current state-of-the-art, even without changing any assumptions regarding the technology readiness levels or material properties. Additionally, the developed optimization toolset can provide further insight into the different trends of key performance indices of the machines, thus helping the designer understand how these improvements are being achieved.
Graduation Semester
2023-05
Type of Resource
Thesis
Copyright and License Information
Copyright 2023 Anubhav Bose

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