Abstract
Road cycling time trials have a long history in all sports, and the individual time trial is one of the most important events in road cycling time trials. Due to the long distance, complex sections, and uncertain natural environment of road cycling individual time trials, in addition to the performance of the bicycle itself, the rider’s ability and physical ability, the athlete’s planning of the ride during the distance is also an important factor affecting the performance of this sport. Therefore, it is important to create a model that can facilitate cyclists’ planning decisions for cy- cling. In constructing the initial model, we compared the training and competition data of cyclists with other types of athletes by referring to various literature to find commonalities and individ- ualities between road cycling time trials and other sports, thereby refining the data, and finally determined a power curve model related to power functions using knowledge of ordinary differ- ential equations and fitting.The model can infer the instantaneous power from the rider’s riding time, and when combined with the external force data such as wind and gravity, the rider’s kinetic energy can be derived. The model also incorporates the fact that the total energy of the rider is limited, which guarantees the feasibility and reasonableness of the model
Publisher
Darcy & Roy Press Co. Ltd.
Reference6 articles.
1. Ebert, T. R., Martin, D. T., McDonald, W., Victor, J., Plummer, J., & Withers, R.T. (2005). Power output during women’s World Cup Road cycle racing. European journal of applied physiology, 95(5), 529-536.
2. Zhang TaiMing (2015). Effect of different pre-cooling methods on athletes’ power cycling incremental load exercise capacity in high temperature and high humidity environment[D]. Capital University of Physical Education and Sports.
3. Ding Danhua, Qiu Guomin. (2018). Mechanics in bicycle turning. Explorations in Physics Teaching (07), 62-64.
4. https://cyklopedia.cc/cycling-tips/power-profile/
5. https://www.cyclinganalytics.com/blog/2013/06/Comparative-statistics