Viability assessment of a rigid wing airborne wind energy pumping system

Licitra, Giovanni; Koenemann, Jonas; Horn, Greg; Williams, Paul; Ruiterkamp, Richard; Diehl, Moritz

doi:10.1109/pc.2017.7976256

Cited by 7 publications

(6 citation statements)

References 34 publications

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“…For this reason, the solution of the FPR problem is the first step toward aerodynamic parameter identification for AWE systems. Recent works have tackled this problem for rigid-wing AWE pumping systems [27,28].…”

mentioning

confidence: 99%

Flight-Path Reconstruction and Flight Test of Four-Line Power Kites

Borobia-Moreno

Sánchez‐Arriaga

Serino

et al. 2018

Journal of Guidance, Control, and Dynamics

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A flight-path reconstruction algorithm for tethered aircraft, which is based on an extended Kalman filter, is presented. The algorithm is fed by the measurements of a set of onboard and ground-based instruments and provides the optimal estimation of the system state-space trajectory, which includes typical aircraft variables such as position and velocity, as well as an estimation of the aerodynamic force and torque. Therefore, it can be applied to closed-loop control in airborne wind energy systems and it is a first step toward aerodynamic parameter identification of tethered aircraft using flight-test data. The performance of the algorithm is investigated by feeding it with real flight data obtained from a low-cost and highly portable experimental setup with a four-line kite. Several flight tests, which include pullup and lateral-directional steering maneuvers with two kites of different areas, are conducted. The coherence of the estimations provided by the filter, such as the kite state-space trajectory and aerodynamic forces and torques, is analyzed. For some standard variables, such as kite Euler angles and position, the results are also compared with a second independent onboard estimator.

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mentioning

confidence: 99%

Flight-Path Reconstruction and Flight Test of Four-Line Power Kites

Borobia-Moreno

Sánchez‐Arriaga

Serino

et al. 2018

Journal of Guidance, Control, and Dynamics

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“…This was confirmed by the experimental study from Behrel et al (2018a) who find lift coefficient of the same magnitude for similar geometries. However, recent studies on rigid wings highlight a potential lift coefficient up to 1.5 as shown by Licitra et al (2017). Bauer et al (2018) even computes a lift coefficient of 4.5 on a multi-element airfoil.…”

Section: Influential Aerodynamic Parametersmentioning

confidence: 99%

Influence of Kite Characteristics on Propulsive Power Applied to Ship Auxiliary Propulsion

Penloup¹,

Roncin

Parlier³

2021

Journal of Sailing Technology

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A Design of Experiment method was applied combined with a performance prediction program to assess the influence of four design parameters on the propulsive capacity of kites used as auxiliary propulsion for merchant vessels. Those parameters are the lift coefficient, the lift to drag ratio or drag angle, the maximal load bearable by the kite and the ratio of the tether length on the square root of the kite area. These parameters are independent from the kite area and, therefore, they could be used with various kite ranges and types. The maximum wing load parameter is the one that shows the most influence on the propulsive force. Over 50% of the gains obtained through this study are directly attributable to it. Then the ratio of the tether length on the square root of the kite area comes as the second greatest influence factor for true wind angles above 70°. While the drag angle is more influential for the narrower angles. In fact, the most substantial gains are made upwind.

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“…The aircraft is subject to forces

{boldf}_{false{boldc, boldp, boldg false}}^{boldb}

and moments

{boldm}_{false{boldc, boldp, boldg false}}^{boldb}

coming from the c able, p ropellers and g ravity, whereas

{boldf}_{bolda}^{boldb} = {false[normalX, normalY, normalZ false]}^{⊤}

and

{boldm}_{bolda}^{boldb} = {false[normalL, normalM, normalN false]}^{⊤}

denote the aerodynamic forces and moments, respectively. The mathematical formulation in () is extensively used for pattern generation using an optimal control approach …”

Section: Modeling Of a Rigid‐wing Awesmentioning

confidence: 99%

“… The aerodynamic model (), () neglects the influence of parameter variation through time . One can account for such a model mismatch either by introducing a first‐order differential equation involving the angle of attack rate

\overset{α}{true}

or by designing flight trajectories customized for energy production that allow the aircraft to perform mild maneuvers The mathematical model () relies on Euler's equations, which describe the motion of rigid bodies only, hence flexible modes are implicitly neglected.…”

Section: Modeling Of a Rigid‐wing Awesmentioning

confidence: 99%

“…The mathematical formulation in (1) is extensively used for pattern generation using an optimal control approach. 20,21 In order to identify the aerodynamic forces f b a and moments m b a , one has to either discard or have good models of the other contributions. For this application, it is convenient to perform untethered flight tests to both simplify the overall system modeling and avoid disturbances caused by tether vibrations.…”

Section: Modeling Of Awes In Natural Coordinatesmentioning

confidence: 99%

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Aerodynamic model identification of an autonomous aircraft for airborne wind energy

Licitra

Bürger

Williams³

et al. 2019

Optim Control Appl Methods

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Summary Airborne wind energy (AWE) refers to a novel technology capable of harvesting energy from wind by flying crosswind patterns with tethered autonomous aircraft. Successful design of flight controllers for AWE systems relies on the availability of accurate mathematical models. Due to an expected nonconventional structure of the airborne component, the system identification procedure must be ultimately addressed via an intensive flight test campaign to gain additional insight about the aerodynamic properties. In this paper, the longitudinal dynamics of a rigid‐wing, high lift, autonomous aircraft for AWE are identified from experimental data obtained within flight tests. The aerodynamic characteristics are estimated via an efficient time‐domain multiple experiments model‐based parameter estimation algorithm.

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Viability assessment of a rigid wing airborne wind energy pumping system

Cited by 7 publications

References 34 publications

Flight-Path Reconstruction and Flight Test of Four-Line Power Kites

Flight-Path Reconstruction and Flight Test of Four-Line Power Kites

Influence of Kite Characteristics on Propulsive Power Applied to Ship Auxiliary Propulsion

Aerodynamic model identification of an autonomous aircraft for airborne wind energy

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