Abstract
Virtual cycling engagement has seen a significant increase in the last decade, with a recognizable surge in 2020 due to the pandemic. To ensure a fair competition field, a testing apparatus was designed to test direct-drive bicycle smart trainers from various manufacturers. Smart trainers were tested for error on two main metrics: power measurement error and resistance error. Given that the integrity of virtual racing relies upon accurate power readings sent from the smart trainer to a cloud-based competition software, discrepancies in these metrics are most likely to affect the outcome of an event. The testing apparatus used a motor in place of a human rider to control the repeatability and capability of the testing system. Power measurements consisting of a torque and rotational velocity sensor were connected to the motor output to determine the precise power delivered to a smart trainer. The known input power was compared to the power reported by the smart trainer as transmitted over the ANT+ wireless protocol and compared across the testing metrics. An electromagnetic brake system was incorporated to characterize the transmission losses from the motor to the smart trainer, enabling the accurate determination of the actual power input into the smart trainers. The testing procedure covered each virtual gradient ranging from − 8 to 15% at every power level between 100 and 800 watts. The power reading error of smart trainers ranged from \(\approx\) 0 to > 16%, and the resistance error ranged from < 1% to over 100%. These large errors show how critical the homologation of smart trainers is for fair competition.
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Acknowledgements
The smart trainer apparatus team would like to thank the Ray Ewry Sports Engineering Center at Purdue University for financial support on this project. We would also like thank the contributions made by student researchers Patrick Cavanaugh and Eleanor Dyas, in addition to the valuable input from Wim Sweldens during the conception of the project.
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Dr. Jan-Anders Mansson served as a guest editor for the Topical Collection on The Engineering of Sport 14, but was not involved in the blind peer review process of this work.
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Dowd, T., Heflin, D., Miller, J. et al. Apparatus and methodology for smart trainer homologation analysis. Sports Eng 27, 6 (2024). https://doi.org/10.1007/s12283-023-00447-z
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DOI: https://doi.org/10.1007/s12283-023-00447-z