Initial Weight Modeling and Parameter Optimization for Collectible Rotor Hybrid Aircraft in Conceptual Design Stage

A collectible rotor hybrid aircraft (CRHA) represents a novel type of vertical takeoff and landing (VTOL) unmanned aircraft configuration, combining the typical rotor and transmission systems of helicopters with the wing and propulsion systems of fixed-wing aircraft. Its weight estimation and parameter design during the conceptual design stage cannot directly use existing rotorcraft or fixed-wing methods. This paper presents a rapid key design parameter sizing and maximum takeoff weight (MTOW) estimation approach tailored to CRHA, explicitly scoped to the 5–8-metric-ton (t) MTOW class. Component weight models are first formulated as explicit functions of key design parameters—including rotor disk loading, power loading, and wing loading. Segment-specific fuel weight fractions for VTOL and transition flight are then updated from power calculations, yielding a complete mission fuel model for this weight class. A hybrid optimization framework that minimizes MTOW is constructed by treating the key design parameters as design variables and combining a genetic algorithm (GA) with sequential quadratic programming (SQP). The empty-weight model, fuel-weight model, and optimization framework are validated against compound-helicopter, tilt-rotor, and twin-turboprop benchmarks, and parameter sensitivities are evaluated locally and globally. Results show prediction errors of roughly 10% for empty weight, fuel weight, and MTOW. Sensitivity analysis indicates that at the baseline design point, wing loading exerts the greatest influence on MTOW, followed by power loading and disk loading.

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Publication Details

Journal
Drones
Published
2025-10-07
DOI
https://doi.org/10.3390/drones9100690
Primary Topic
Advanced Aircraft Design and Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Initial Weight Modeling and Parameter Optimization for Collectible Rotor Hybrid Aircraft in Conceptual Design Stage

Ruobing Dong, Jingwei Chen, Menglin Yang, De Yan et al.
Drones
Advanced Aircraft Design and Technologies
article

Initial Weight Modeling and Parameter Optimization for Collectible Rotor Hybrid Aircraft in Conceptual Design Stage

Ruobing Dong, Jingwei Chen, Menglin Yang, De Yan, Zhiqiang Wan
article en

Abstract

A collectible rotor hybrid aircraft (CRHA) represents a novel type of vertical takeoff and landing (VTOL) unmanned aircraft configuration, combining the typical rotor and transmission systems of helicopters with the wing and propulsion systems of fixed-wing aircraft. Its weight estimation and parameter design during the conceptual design stage cannot directly use existing rotorcraft or fixed-wing methods. This paper presents a rapid key design parameter sizing and maximum takeoff weight (MTOW) estimation approach tailored to CRHA, explicitly scoped to the 5–8-metric-ton (t) MTOW class. Component weight models are first formulated as explicit functions of key design parameters—including rotor disk loading, power loading, and wing loading. Segment-specific fuel weight fractions for VTOL and transition flight are then updated from power calculations, yielding a complete mission fuel model for this weight class. A hybrid optimization framework that minimizes MTOW is constructed by treating the key design parameters as design variables and combining a genetic algorithm (GA) with sequential quadratic programming (SQP). The empty-weight model, fuel-weight model, and optimization framework are validated against compound-helicopter, tilt-rotor, and twin-turboprop benchmarks, and parameter sensitivities are evaluated locally and globally. Results show prediction errors of roughly 10% for empty weight, fuel weight, and MTOW. Sensitivity analysis indicates that at the baseline design point, wing loading exerts the greatest influence on MTOW, followed by power loading and disk loading.

DronesVol. 9(10)
Zhejiang International Studies University (CN), Beihang University (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 74%
Advanced Aircraft Design and Technologies
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