Optimising sprint cyclists' position for maximum speed: a modelling and simulation approach

Lead Research Organisation: University of Cambridge
Department Name: Engineering

Abstract

In recent years, the sport of cycling has seen many advances in equipment, training and strategy due to the application of science and technology. However there is still a great level of uncertainty surrounding how to best utilise rider position in order to achieve higher output power and reduce aerodynamic drag. Previous studies conducted in this area have used small groups of elite cyclist to investigate bike setup. This introduces significant bias into the results as elite cyclists are adapted to riding in a certain position through many hours of training. This project will adopt a new investigative method involving the modelling and simulation of cyclists' biomechanics and any acting resistive forces in order to provide a non-biased assessment of how to optimise bike setups for a cyclist's maximum achievable speed in the velodrome.

There are three novel engineering design aspects to this project that are relevant to the EPSRC's engineering design research area. First, using methodologies from the literature, a muscle actuated forward dynamics model of a sprint cyclist and bike will be developed. This will be the first simultaneous modelling of biomechanics and aerodynamics for use within an optimisation framework of a track cyclist's position as it will incorporate modelling of the cyclist's skeletal system, muscular system and nervous system, the dynamics of the bicycle and a model for the cyclist's aerodynamic drag and rolling resistance.

Secondly, while previous studies have investigated effects of individual bike fit parameters (e.g. saddle height, crank arm length, chain ring geometry etc.) or muscle activation dynamics on a cyclist's ability to produce power, there is currently no work consolidating the combined effects of all of these potential variables. This project will address this by developing an optimisation framework to optimise muscle activation timings and multiple bike fit parameters simultaneously.

Finally, a methodology to make the models subject specific will be developed. There are many parameters within current neuromuscularskeletal models that have to be given generalised values as they cannot be easily measured experimentally from an individual's anatomy. This project will use the previously developed biomechanics model along with experimental data from constrained motion maximal effort dynamometer tests and an optimisation routine to determine subject specific value for these neuromuscularskeletal parameters.

This project also relates to the EPSRC's assistive technology, rehabilitation and musculoskeletal biomechanics research area as it will allow the modelling of specific individuals and analysis of the forces experiences by the musculoskeletal system under certain movements.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509620/1 01/10/2016 30/09/2021
1643407 Studentship EP/N509620/1 01/10/2016 30/09/2020 Samuel George Brockie