Predictive Dynamic Simulation of Seated Start-Up Cycling Using Olympic Cyclist and Bicycle Models

Predictive dynamic simulation is a useful tool for analyzing human movement and optimizing performance. Here it is applied to Olympic-level track cycling. A seven degree-of-freedom, two-legged cyclist and bicycle model was developed using MapleSim. GPOPS-II, a direct collocation optimal control software, was used to solve the optimal control problem for the predictive simulation. The model was validated against ergometer pedaling performed by seven Olympic-level track cyclists from the Canadian team. The simulations produce joint angles and cadence/torque/power similar to experimental results. The results indicate optimal control can be used for predictive simulation with a combined cyclist and bicycle model. Future work needed to more accurately model an Olympic cyclist and a standing start is discussed.