Article Text

Comprehensive model to enhance road cycling performance
  1. P Cangley1,
  2. L Passfield2,
  3. H Carter1,
  4. M Bailey1
  1. 1Chelsea School, University of Brighton, Eastbourne, East Sussex, UK
  2. 2Centre for Sports Studies, University of Kent, Medway, UK

Abstract

Modelling has been utilised in competitive road cycling to identify performance optimisations that would conventionally require extensive experimental testing. However, the validity of current models is limited by incomplete representation of the cycling environment and insufficient frequency of simulation. A three dimensional road cycling model has been developed that extends existing models by combining bicycle mechanics, rider biomechanics and environmental conditions into a single dynamic system. A system of rigid bodies linked by joints and driven by actuators has been built using the MATLAB toolboxes Simulink and SimMechanics. Each body is defined in respect of mass, inertia tensor, dimension and centre of gravity. The system operates in forward dynamics mode such that a simulation inputs forces to the equations of motion which are numerically integrated at <0.1 s time steps and output system motion. Bicycle freedoms include longitudinal/lateral translation together with roll, pitch and yaw rotation. Submodels reproduce transmission, tires, wheels, frame and steering geometry. A 16 segment rider applies experimentally obtained pedal forces coordinated with upper body roll and steering input. Environmental parameters include course track and gradient obtained from digital maps together with experimentally measured wind speed/direction. The model has been validated in a trial with 20 experienced time trialists riding a 2.5 mile undulating section of the Cycling Time Trials course G10/42 at competitive pace. The course track/profile and the cyclist characteristics were loaded into the model and a simulation predicted individual completion times. Mean actual time was within 1.4 (±0.7)% of the mean predicted time. The model was then used to optimise application of a variable power pacing strategy over the same course1. A 2.9 (±0.9)% time saving was obtained which would typically represent a 40 s advantage over a full 10 mile time trial. Further model applications include investigating the mechanical performance advantages of factors that are both difficult and time consuming to examine experimentally such as saddle position, bicycle/rider weight and tire characteristics.

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