Translational dynamics of bridled kites: a reduced-order model in the course reference frame

Journal Article (2026)
Author(s)

O. Cayon (TU Delft - Wind Energy)

V.D. van Deursen (Student TU Delft)

R. Schmehl (TU Delft - Wind Energy)

Research Group
Wind Energy
DOI related publication
https://doi.org/10.5194/wes-11-1097-2026 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Wind Energy
Journal title
Wind Energy Science
Issue number
3
Volume number
11
Pages (from-to)
1097–1121
Downloads counter
11
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Abstract

The design and control of airborne wind energy systems requires fast, validated reduced-order models. Because the aerodynamic identification of soft, bridled kites is challenging, models that minimise the number of parameters to be identified can be particularly valuable. This paper presents a reduced-order model for the translational dynamics of bridled kites, consisting of a wing supported by multiple bridle lines. The kite is modelled as a point mass in a spherical reference frame aligned with the instantaneous tangential flight direction, referred to as the course reference frame. The angle of attack follows geometrically from a constant angle between the wing chord and the bridle line system, under the assumption that the wing instantaneously aligns with the pull direction, i.e. the rotational dynamics are neglected. The formulation retains gravitational and inertial terms introduced by the curvilinear reference frame and applies a quasi-steady condition of zero-path-aligned acceleration, modelling the motion as a sequence of quasi-steady (trimmed) states that relate the trim speed and angle of attack. Model validation is based on public flight datasets from two different soft-wing kites and on dynamic simulations that cover higher wing loadings. Results show that for low wing loadings typical of soft kites, the quasi-steady approximation reproduces the dynamic trajectories with less than 1 % deviation in mean reel-out power. For higher loadings and hard-wing kites, inertia introduces substantial phase lag and amplitude damping, causing power deviations of up to 14 %. Overall, the proposed model provides a computationally efficient framework for analysing the translational dynamics of bridled kites. The formulation is well suited to trajectory optimisation, parametric studies, and control design in airborne wind energy systems.