Electric Propulsion Architecture Assessment via Signomial Programming

Aidan P. Dowdle, David K. Hall, Jeffrey H. Lang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

This paper presents the application of signomial programming to the assessment and multidisciplinary optimization of electric propulsion systems. Analytic models for electrical and mechanical propulsion system components are developed that are compatible with the signo-mial programming objective and constraint forms. These models capture the dependence of mass and efficiency on material properties and operating conditions. Standalone optimization of the electrical cable and motor model illustrates a trade-off between mass and efficiency at the component level. These component models are subsequently integrated into various propulsion architectures and are optimized while taking into account the component dependencies (e.g., fan and motor shaft speed). Specifically, turbofan, turboelectric and geared turboelectric propulsion architectures are optimized on the metrics of fuel consumption and propulsion system mass. The results show that the optimal component masses and efficiencies depend on the propulsion architecture, operating point, and performance metric under consideration, and that signomial programming is useful for determining them.

Original languageEnglish (US)
Title of host publication2018 AIAA/IEEE Electric Aircraft Technologies Symposium, EATS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781624105722
DOIs
StatePublished - Nov 29 2018
Event2018 AIAA/IEEE Electric Aircraft Technologies Symposium, EATS 2018 - Cincinnati, United States
Duration: Jul 12 2018Jul 14 2018

Publication series

Name2018 AIAA/IEEE Electric Aircraft Technologies Symposium, EATS 2018

Conference

Conference2018 AIAA/IEEE Electric Aircraft Technologies Symposium, EATS 2018
Country/TerritoryUnited States
CityCincinnati
Period7/12/187/14/18

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering

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