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

Benjamin Luckett; Jiang Biao He

doi:10.1109/ITECAsia-Pacific59272.2023.10372295

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 proceeding › Conference contribution › peer-review

2 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 language	English
Title of host publication	ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific
ISBN (Electronic)	9798350314274
DOIs	https://doi.org/10.1109/ITECAsia-Pacific59272.2023.10372295
State	Published - 2023
Event	2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023 - Chiang Mai, Thailand Duration: Nov 28 2023 → Dec 1 2023

Publication series

Name	ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific

Conference

Conference	2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023
Country/Territory	Thailand
City	Chiang Mai
Period	11/28/23 → 12/1/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Funding

ACKNOWLEDGMENT This work was supported by the U.S. Department of Education’s GAANN Fellowship Program through the University of Kentucky Electrical and Computer Engineering Department.

Funders
University of Kentucky Department of Electrical and Computer Engineering
U.S. Department of Education, OSERS

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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

Access to Document

10.1109/ITECAsia-Pacific59272.2023.10372295

Cite this

Luckett, B., & He, J. B. (2023). Genetic Algorithm Enabled Multi-Objective Design Optimization of Current Source Converters for Turboelectric Aircraft Propulsion. In ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific). https://doi.org/10.1109/ITECAsia-Pacific59272.2023.10372295

Luckett, Benjamin ; He, Jiang Biao. / Genetic Algorithm Enabled Multi-Objective Design Optimization of Current Source Converters for Turboelectric Aircraft Propulsion. ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific. 2023. (ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific).

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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.",

keywords = "current source power converter, high efficiency, high power density, high reliability, multi-objective design optimization, Turboelectric aircraft propulsion",

author = "Benjamin Luckett and He, \{Jiang Biao\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023 ; Conference date: 28-11-2023 Through 01-12-2023",

year = "2023",

doi = "10.1109/ITECAsia-Pacific59272.2023.10372295",

language = "English",

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Luckett, B & He, JB 2023, Genetic Algorithm Enabled Multi-Objective Design Optimization of Current Source Converters for Turboelectric Aircraft Propulsion. in ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific. ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023, Chiang Mai, Thailand, 11/28/23. https://doi.org/10.1109/ITECAsia-Pacific59272.2023.10372295

Genetic Algorithm Enabled Multi-Objective Design Optimization of Current Source Converters for Turboelectric Aircraft Propulsion. / Luckett, Benjamin; He, Jiang Biao.
ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific. 2023. (ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Luckett B, He JB. Genetic Algorithm Enabled Multi-Objective Design Optimization of Current Source Converters for Turboelectric Aircraft Propulsion. In ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific. 2023. (ITEC Asia-Pacific 2023 - 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific). doi: 10.1109/ITECAsia-Pacific59272.2023.10372295

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

Abstract

Publication series

Conference

Bibliographical note

Funding

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this