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Influence of wind speed and road grade on the estimation of drag area in cycling.

Alejandra PolancoSergio RoaDaniel R SuárezOmar LópezLuis Muñoz
Published in: Sports biomechanics (2021)
The estimation of aerodynamic drag in cycling through road tests has the advantage of considering actual cycling conditions. The main drawback is that its accuracy depends on factors of the testing scenario as the wind speed vw and the road grade θ. For that reason, the effect of vw and θ on the estimation of drag area (CDA) was studied. Numerical and experimental approaches were combined. The numerical approach investigated the sensitivity of CDA to vw and θ perturbations. The experimental approach analysed the effect of including or not vw and θ on the identification of CDA by comparing the changes in the prediction of power delivered. It was found that disregarding small values of vw (e.g. 0.5 m/s) and θ (e.g. gradient of 0.05%) leads to errors in the estimation of CDA of around 10%, referred to the actual value. It was also obtained that the average error of the power prediction when considering vw and θ for the identification of the parameters is about 4.4% and about 25.5% when vw and θ are neglected. It is concluded that including vw and θ data reduces the error on the identification of CDA through outdoor road experiments.
Keyphrases
  • high intensity
  • bioinformatics analysis
  • air pollution
  • electronic health record
  • machine learning
  • deep learning
  • data analysis