Sizing methodologies for aircraft with multiple energy systems
Abstract/Contents
- Abstract
- Electric aircraft have been a topic of significant interest, especially in recent years. A wide variety of different aircraft configurations that utilize electric propulsion at short ranges have been proposed and are currently under development. However, physical limits in battery technology have significantly hampered their entry-into-service. A proposed solution has been to use hybrid-electric or hybrid battery approaches that allow the user to leverage multiple energy systems with contrasting specific energy and specific power properties to allow for lighter, more feasible aircraft along with the opening of new regions in the design space. Many of the designs, particularly those that use distributed electric propulsion possess a complex trade-space that needs global optimization methods to properly evaluate. This dissertation develops a methodology for basic sizing of aircraft that enables the designer to employ global optimization methods at the earliest stages of the design process with substantial improvements in code speed, and, depending on the method used, robustness. Furthermore, it reveals an inherent weakness in developing and sizing electric and hybrid-electric aircraft that only use a single value for specific energy and specific power; the results here show representative cases where modeling off-design performance rather than simply taking a nominal value can reduce aircraft weight by as much as factor of two. This also illustrates that for electric aircraft, making intelligent design decisions in the earliest stages of the design process is much more crucial than in traditional designs where specific energy is not nearly as limiting. Additionally, it explores and diagnoses several unusual issues that may arise in the context of solving aircraft design problems that possess multiple energy systems, while offering algorithmic solutions that improve both code speed and robustness. More specifically, these designs show an unsettling characteristics in that, at the basic level, solutions to the aircraft sizing problem may be nonunique. Now, it should be noted that different methods are more susceptible to finding extraneous solutions which will be discussed in greater detail. Finally, it develops frameworks utilizing machine learning regression techniques that learn the trade space of sizing solutions, meaning that what may be computationally expensive calculations can be initiated from a nearly converged starting point.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Vegh, Julius Michael |
|---|---|
| Degree supervisor | Alonso, Juan José, 1968- |
| Thesis advisor | Alonso, Juan José, 1968- |
| Thesis advisor | Cantwell, Brian |
| Thesis advisor | Kroo, Ilan |
| Thesis advisor | Saunders, Michael A |
| Degree committee member | Cantwell, Brian |
| Degree committee member | Kroo, Ilan |
| Degree committee member | Saunders, Michael A |
| Associated with | Stanford University, Department of Aeronautics and Astronautics. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Julius Michael Vegh. |
|---|---|
| Note | Submitted to the Department of Aeronautics and Astronautics. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Julius Michael Vegh
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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