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Techno-economic-environmental evaluation of aircraft propulsion electrification: Surrogate-based multi-mission optimal design approach

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journal contribution
posted on 2024-03-05, 11:20 authored by J Zhang, I Roumeliotis, X Zhang, A Zolotas
Driven by the sustainability initiatives in the aviation sector, the emerging technologies of aircraft propulsion electrification have been identified as the promising approach to realize sustainable and decarbonized aviation. This study proposes a surrogate-based multi-mission optimal design approach for aircraft propulsion electrification, which innovatively incorporates realistic aviation operations into the electric aircraft design, with the aim of improving the overall aircraft fuel economy over multiple flight missions and conditions in practical scenarios. The proposed optimal design approach starts with the flight route data analysis to cluster the flight operational data using gaussian mixture model, so that a concise representation of flight mission profiles can be achieved. Then, an optimal orthogonal array-based Latin hypercubes are employed to generate sampling points of design variables for electrified aircraft propulsion. The mission analysis is performed with coupled propulsion-airframe integration in order to propose energy management strategy for mission-dependent aircraft performance. Consequently, fuel economy surrogate model is established via support vector machines to obtain the optimal design points of electrified aircraft propulsion. For assessing the viability of novel propulsion technologies, techno-economic evaluation is conducted using sensitivity analysis and breakeven electricity prices under a series of environmental regulatory policy scenarios.

History

Citation

Renewable and Sustainable Energy Reviews 175 (2023) 113168

Author affiliation

Engineering

Version

  • VoR (Version of Record)

Published in

Renewable and Sustainable Energy Reviews

Volume

175

Publisher

Elsevier BV

issn

1364-0321

eissn

1879-0690

Acceptance date

2024-01-04

Copyright date

2023

Available date

2024-03-05

Language

en

Deposited by

Miss Jinning Zhang

Deposit date

2024-02-12

Data Access Statement

Data will be made available on request.

Rights Retention Statement

  • No