Quantifying cross-country ski–snow friction using real-time kinematic positioningShow others and affiliations
2025 (English)In: Friction, ISSN 2223-7690, E-ISSN 2223-7704, Vol. 13, no 4, article id 9441011
Article in journal (Refereed) Published
Abstract [en]
In cross-country skiing, athletes expend large amounts of energy to overcome friction as their skis interact with snow. Even minor reductions in the friction can significantly influence race outcomes. Over the years, researchers have found many ways of quantifying ski–snow friction, but there are only a few methods that consider the glide of real-sized skis under natural conditions during both accelerating and decelerating movements. This study introduces a novel experimental setup, consisting of a sled equipped with authentic cross-country skis and a base station that uses satellite receivers to communicate via radio, constituting a real-time kinematic positioning system with centimetre accuracy. While the sled was running on a classic ski track with natural height variations, altitude and velocity data were recorded for quantification of the coefficient of friction (COF), both for accelerating and decelerating motion, employing a model based on Newton’s second law. The results show that the COF during acceleration was more than 20% higher than during deceleration, demonstrating dynamic changes in the frictional behaviour between these phases. This finding is crucial for the execution of all types of cross-country skiing techniques, where the athlete either accelerates or decelerates while moving forward. The ability of the current experimental set-up to distinguish between the COF during acceleration and deceleration has considerable implications for further developments.
Place, publisher, year, edition, pages
Tsinghua University Press , 2025. Vol. 13, no 4, article id 9441011
Keywords [en]
winter sports, cross-country ski, snow, friction, real-time kinematic (RTK)–global navigation satellite system (GNSS), tribometer
National Category
Sport and Fitness Sciences
Research subject
Machine Elements; Physiotherapy and Health Promotion
Identifiers
URN: urn:nbn:se:ltu:diva-112085DOI: 10.26599/frict.2025.9441011ISI: 001443628700002OAI: oai:DiVA.org:ltu-112085DiVA, id: diva2:1946752
Note
Validerad;2025;Nivå 2;2025-03-24 (u5);
Full text license: CC BY 4.0;
2025-03-242025-03-242025-04-22Bibliographically approved