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Identification of induced inflow factor of tiltrotor based on augmented dynamic inflow model

Published online by Cambridge University Press:  24 March 2026

Lan Yang Open the ORCID record for Lan Yang [Opens in a new window] ,
Xing Wang Open the ORCID record for Xing Wang [Opens in a new window] ,
Dong Han Open the ORCID record for Dong Han [Opens in a new window] ,
Dong Wang ,
Wubin Kong  and
Yuchao Hu
Lan Yang
Affiliation:
School of Electrical and Electronic Enginnering, Huazhong University of Science and Technology - Main Campus: Huazhong University, Wuhan, China
Xing Wang*
Affiliation:
National Key Laboratory of Electromagnetic Energy, Naval University of Engineering, Wuhan, China
Dong Han
Affiliation:
College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, NanJing, China
Dong Wang
Affiliation:
National Key Laboratory of Electromagnetic Energy, Naval University of Engineering, Wuhan, China
Wubin Kong
Affiliation:
School of Electrical and Electronic Enginnering, Huazhong University of Science and Technology - Main Campus: Huazhong University, Wuhan, China
Yuchao Hu
Affiliation:
National Key Laboratory of Electromagnetic Energy, Naval University of Engineering, Wuhan, China
*
Corresponding author: Xing Wang; Email: wangxing_23@nue.edu.cn
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Abstract

Aerodynamic modeling of tiltrotor aircraft is inherently limited by incomplete aerofoil data for blades constructed from multiple aerofoil sections. This data deficiency leads fundamental errors into the blade element theory (BET) inputs, resulting in inaccurate induced velocity and unsteady load predictions that compromise flight control design. To overcome this limitation, a corrective induced inflow factor k is introduced into an augmented Pitt–Peters dynamic inflow model. For fixed tilt angles, k is efficiently identified via an optimisation framework. The fmincon algorithm attains the optimal k with a computational speed 5–6 times faster than the genetic algorithm, while maintaining thrust coefficient errors within 1.26%. For continuous tilting, a direction-aware, time-varying quadratic model for k(t) is proposed, which uses the Fréchet distance metric to accurately reconstruct the aerodynamic hysteresis loop and eliminate spurious load predictions during rotation reversal. Validated through wind tunnel tests, the framework reduces the maximum thrust prediction error in dynamic tilting from 34.10 to 10.70%. The corrected aerodynamic model supports real-time simulation and provides a reliable foundation for advanced tiltrotor control system design.

Keywords

dynamic inflow modeleVTOL aircraftoptimisation algorithmsparameter identificationtiltrotor aerodynamicsunsteady loads

Information

Type
Research Article
Information
The Aeronautical Journal , Volume 130 , Issue 1347 , May 2026 , pp. 1726 - 1743
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Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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Footnotes

†

This article has been updated since original publication. A notice detailing the change has been published.

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