Experimental Modeling of Cyclists Fatigue and Recovery Dynamics Enabling Optimal Pacing in a Time Trial

TL;DR

This paper develops a mathematical model of cyclist fatigue and recovery based on Critical Power and Anaerobic Work Capacity, and uses it to optimize pacing strategies for a 10.3 km time trial simulation.

Contribution

It introduces a novel model combining CP and AWC to optimize cyclist pacing strategies during time trials.

Findings

Model accurately predicts fatigue and recovery dynamics.

Optimized pacing improves simulated cyclist performance.

Model validated against real cyclist data.

Abstract

Improving a cyclist performance during a time-trial effort has been a challenge for sport scientists for several decades. There has been a lot of work on understanding the physiological concepts behind it. The concepts of Critical Power (CP) and Anaerobic Work Capacity (AWC) have been discussed often in recent cycling performance related articles. CP is a power that can be maintained by a cyclist for a long time; meaning pedaling at or below this limit, theoretically, can be continued for infinite amount of time. However, there is a limited source of energy for generating power above CP. This limited energy source is AWC. After burning energy from this tank, a cyclist can recover some by pedaling below CP. In this paper we utilize the concepts of CP and AWC to mathematically model muscle fatigue and recovery of a cyclist. Then, the models are used to formulate an optimal control problem for a time trial effort on a 10.3 km course located in Greenville SC. The course is simulated in a laboratory environment using a CompuTrainer. At the end, the optimal simulation results are compared to the performance of one subject on CompuTrainer.