Time Trial Pacing Optimization Strategy Based on Muscle Fatigue and Aerobic and Anaerobic Respiration

Authors

  • Li Ding
  • Junlei Zhu
  • Beiying Huang

DOI:

https://doi.org/10.54097/ajst.v2i2.1072

Keywords:

Aerobic and anaerobic respiration, Image processing, Muscle fatigue and recovery.

Abstract

 In the time trial, the rider should organize his/her power wisely so that he/she can minimize the time for the entire contest. In order to design the optimal power output strategy for different riders in different road situations , we build a model to describe the rider based on the aerobic and anaerobic respiration and muscle fatigue and recovery process . Then we use the greedy algorithm to obtain the optimal pacing strategy for the rider on the plane road. Then we use the image processing to get the road data in UCI and Tokyo Olympics and use modify the model so that it can give the optimal pacing strategy on the roads with turns and slope.

References

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Published

28 July 2022

How to Cite

Ding, L., Zhu, J., & Huang, B. (2022). Time Trial Pacing Optimization Strategy Based on Muscle Fatigue and Aerobic and Anaerobic Respiration. Academic Journal of Science and Technology, 2(2), 17–25. https://doi.org/10.54097/ajst.v2i2.1072

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Section

Articles