AI-Driven Fuel Optimization in VTOL Aircraft: A Comprehensive Review

Authors

  • Kanishk Mahaveer Jain Department of Mechanical Engineering, Birla Institute of Technology and Science, Pilani Dubai.

DOI:

https://doi.org/10.61359/11.2106-2532

Keywords:

VTOL, Aircraft, Fuel Optimization, Performance Analysis

Abstract

Artificial Intelligence (AI) is transforming fuel efficiency optimization into Vertical Take-Off and Landing (VTOL) aircraft through advanced machine learning algorithms, adaptive control systems, and predictive maintenance strategies. This review examines the current state of AI applications in VTOL fuel optimization, analyzing key methodologies including route optimization, real-time adaptive control, hybrid power management, and predictive maintenance. Recent field trials demonstrate energy savings ranging from 5% to 18%, with notable implementations by NASA, GE Aviation, and Bell Nexus. We discuss the technical challenges, regulatory considerations, and future directions that will shape the integration of AI in next-generation urban air mobility systems.

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Published

2025-06-30

How to Cite

Kanishk Mahaveer Jain. (2025). AI-Driven Fuel Optimization in VTOL Aircraft: A Comprehensive Review. Acceleron Aerospace Journal, 4(6), 1176–1185. https://doi.org/10.61359/11.2106-2532

Issue

Vol. 4 No. 6 (2025): Acceleron Aerospace Journal (AAJ), Volume 4, Issue 5, 2025

Section

Articles

Categories

License

Copyright (c) 2025 Acceleron Aerospace Journal

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The Acceleron Aerospace Journal, with ISSN 2583-9942, uses the CC BY 4.0 International License. You're free to share and adapt its content, as long as you provide proper attribution to the original work.