Quantitative study of a full-scale pedaling mannequin for wind tunnel testing

(Quantitative Untersuchung einer lebensgroßen tretenden Puppe für Windkanaltests)

Human participants introduce variability in cycling wind tunnel testing due to fatigue, resulting in slight inconsistencies in position. To address these limitations, this study introduces a dynamic, full-scale pedaling mannequin, capable of generating repeatable and controlled pedaling movements. This study focuses on three main objectives: (1) validating the mannequin`s kinematics by comparing its pedaling motion to an idealized mechanical model, (2) quantifying the dynamic forces generated by the mannequin during operation and assessing their impact on measurement stability, and (3) evaluating the variability of aerodynamic measurements across different pedaling cadences and wind speeds. Experiments were conducted in a low-turbulence wind tunnel, with kinematic analysis performed using computer vision and force measurements recorded at multiple cadences and wind speeds. Results demonstrate that the mannequin produces highly repeatable pedaling motions with a minimal and a maximal standard deviation of 0.24 and 0.88% across all tested conditions. The smallest detectable meaningful power change in optimal conditions was 1.61 W at 50 km/h and at a pedaling frequency of 67 rotations per minute. Pedaling-induced forces were shown to influence the aerodynamic drag measurements, highlighting the importance of distinguishing dynamic and aerodynamic components of the force signal. These findings establish the mannequin as a reliable tool for controlled aerodynamic analysis, with applications in both scientific research and performance optimization in competitive cycling.
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Bibliographische Detailangaben
Schlagworte:
Notationen:Naturwissenschaften und Technik Ausdauersportarten
Tagging:Kinematik
Veröffentlicht in:Sports Engineering
Sprache:Englisch
Veröffentlicht: 2025
Online-Zugang:https://doi.org/10.1007/s12283-025-00514-7
Jahrgang:28
Heft:2
Seiten:Article 31
Dokumentenarten:Artikel
Level:hoch