Genetic Algorithm Enabled Multi-Objective Design Optimization of Current Source Converters for Turboelectric Aircraft Propulsion

Benjamin Luckett, Jiang Biao He

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The advent of electrified aviation has ushered in a greater need for energy efficient, power dense, reliability-oriented design of power conversion systems. Conventionally, the entire design process consumes large quantities of time, effort, and engineering resources. To address this problem, this paper proposes a genetic algorithm enabled multi-objective design optimization framework by which one can quickly generate many iterations of a back-to-back current source converter for turboelectric aircraft propulsion systems. The automated design methodology can locate optimal trade-offs between design objectives (i.e., reliability, power density, energy efficiency, cost, etc.) and generate the Pareto front for a user-specified optimization problem.

Original languageEnglish
Title of host publicationITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific
ISBN (Electronic)9798350314274
DOIs
StatePublished - 2023
Event2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023 - Chiang Mai, Thailand
Duration: Nov 28 2023Dec 1 2023

Publication series

NameITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific

Conference

Conference2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023
Country/TerritoryThailand
CityChiang Mai
Period11/28/2312/1/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • current source power converter
  • high efficiency
  • high power density
  • high reliability
  • multi-objective design optimization
  • Turboelectric aircraft propulsion

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Aerospace Engineering
  • Automotive Engineering
  • Electrical and Electronic Engineering
  • Transportation

Fingerprint

Dive into the research topics of 'Genetic Algorithm Enabled Multi-Objective Design Optimization of Current Source Converters for Turboelectric Aircraft Propulsion'. Together they form a unique fingerprint.

Cite this