AI-Driven Pre-Design Predictions of a 90-Passenger Hybrid-Electric Aircraft
Erick ESPINOSA-JUÁREZ, Álvaro GÓMEZ-RODRÍGUEZ, Felix MARTINEZ-RIOS, Christopher JOUANNET, Kristian AMADORI
Abstract. As the numerous aircraft concepts using electric or hybrid-electric propulsion remain at low technology readiness levels, there are no operational statistical data, and information on these concepts is comparatively scarce. The objective of this study is to explore alternative methods for early-stage estimations by evaluating and comparing design parameter predictions derived from conventional statistical methods and artificial intelligence (AI) for a 90-passenger hybrid-electric aircraft. The findings highlight the potential of AI as a tool for the early phases of aircraft conceptual design.
Keywords
Artificial Intelligence, Aircraft Conceptual Design, Fully Electric Aircraft, Hybrid-Electric Aircraft, Correlation Analysis, Singular Value Decomposition (SVD)
Published online 7/20/2026, 6 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Erick ESPINOSA-JUÁREZ, Álvaro GÓMEZ-RODRÍGUEZ, Felix MARTINEZ-RIOS, Christopher JOUANNET, Kristian AMADORI, AI-Driven Pre-Design Predictions of a 90-Passenger Hybrid-Electric Aircraft, Materials Research Proceedings, Vol. 69, pp 558-563, 2026
DOI: https://doi.org/10.21741/9781644904251-100
The article was published as article 100 of the book CEAS – AIDAA Conference 2025
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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