School of Engineering, Pontifical Javeriana University (Pontificia Universidad Javeriana), Bogota, Colombia.
Department of Mechanical Engineering, University of Los Andes, Bogota, Colombia.
Sports Biomech. 2024 Feb;23(2):222-240. doi: 10.1080/14763141.2020.1837925. Epub 2021 Jan 12.
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 and the road grade . For that reason, the effect of and on the estimation of drag area () was studied. Numerical and experimental approaches were combined. The numerical approach investigated the sensitivity of to and perturbations. The experimental approach analysed the effect of including or not and on the identification of by comparing the changes in the prediction of power delivered. It was found that disregarding small values of (. 0.5 m/s) and (. gradient of 0.05%) leads to errors in the estimation of of around 10%, referred to the actual value. It was also obtained that the average error of the power prediction when considering and for the identification of the parameters is about 4.4% and about 25.5% when and are neglected. It is concluded that including and data reduces the error on the identification of through outdoor road experiments.
通过道路测试估算自行车的空气动力阻力具有考虑实际骑行条件的优势。主要缺点是其准确性取决于测试场景的因素,如风速和道路坡度。因此,研究了 和 对阻力面积( )估算的影响。结合了数值和实验方法。数值方法研究了 对 和 摄动的敏感性。实验方法通过比较功率预测的变化来分析通过包含或不包含 和 来识别 的效果,从而分析了 的影响。结果发现,忽略小的 和 值(. 0.5 m/s 和. 0.05%的坡度)会导致对 的估计误差约为 10%,相对于实际值。还得出结论,当考虑 和 来识别参数时,功率预测的平均误差约为 4.4%,而忽略 和 时,平均误差约为 25.5%。结论是,通过户外道路实验包含 和 数据可以减少对 的识别误差。