A low-cost experimental-numerical method for the prediction of on-road comfort of city bicycles is presented. Experimental tests are performed by exciting the wheels of the bicycle with impulsive vibrations and measuring the frequency response functions (FRFs) between different sensitive points of the bicycle (i.e. seatpost and steerer tube) and the wheels. Laboratory tests are carried out with the rider on the bicycle, and the posture is carefully checked. A mathematical model is employed to predict the accelerations experienced by the rider on the road, considering tyre and wheelbase filtering. As a verification of the proposed methodology, comfort predictions obtained with the experimental-numerical method are compared with reference data obtained from road tests. A general agreement in terms of the root mean square values and power spectral densities is found.

Cyclists are exposed to vibration due to road roughness. The levels of vibration that the cyclists experience have a major effect on comfort and depend on the bicycle, rider and road characteristics. It is known that the posture of the cyclist has a relevant effect on the bicycle-cyclist system vibration response. Nevertheless, this effect has been scarcely quantified. This study focuses on the measurement of the effect of body posture on comfort while riding a bicycle. A laboratory methodology based on the measurement of the impulsive response of sensitive points of the bicycle was implemented to predict the comfort of cyclists on the road. The posture on the sagittal plane was verified during the tests. The methodology was implemented to predict the comfort of two cyclists riding a city bicycle in two postures: upright and bent forward. Experimental results showed that in the bent forward posture the acceleration levels had a significant increment for the handlebar stem and a non-significant increment for the seatpost.

Cyclists usually define their posture according to performance and comfort requirements. However, when modifying their posture, cyclists experience a trade-off between these requirements. In this research, an optimization methodology is developed to select the posture of cyclists giving the best compromise between performance and comfort. Performance was defined as the race time estimated from the power delivery capacity and resistive forces. Comfort was characterized using pressure and vibration indices. The optimization methodology was implemented to select the aerobars’ height for five cyclists riding on 20-km time-trial races with different wind speed and road grade conditions. The results showed that the reduction of the aerobars’ height improved the drag area (−10.7% ± 3.1%) and deteriorated the power delivery capacity (−9.5% ± 5.4%), pressure on the saddle (+16.5% ± 11.5%), and vibrations on the saddle (+6.5% ± 4.0%) for all the tested cyclists. It was observed that the vibrations on the saddle imposed the greatest constraint for the cyclists, limiting the feasible exposure time and, in some cases, modifying the result obtained if the posture was selected considering only performance. It was concluded that optimal posture selection should be performed specifically for each cyclist and race condition due to the dependence of the results on these factors.

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 $\left(v_w\right)$ and the road grade $\left(\theta \right)$. For that reason, the effect of $v_w$ and $\theta$ on the estimation of drag area ( $C_{D}A$) was studied. Numerical and experimental approaches were combined. The numerical approach investigated the sensitivity of $C_{D}A$ to $v_w$ and $\theta$ perturbations. The experimental approach analysed the effect of including or not $v_w$ and $\theta$ on the identification of $C_{D}A$ by comparing the changes in the prediction of power delivered. It was found that disregarding small values of $v_w$ (e.g. 0.5 m/s) and $\theta$ (e.g. gradient of 0.05%) leads to errors in the estimation of $C_{D}A$ of around 10%, referred to the actual value. It was also obtained that the average error of the power prediction when considering $v_w$ and $\theta$ for the identification of the parameters is about 4.4% and about 25.5% when $v_w$ and $\theta$ are neglected. It is concluded that including $v_w$ and $\theta$ data reduces the error on the identification of $C_{D}A$ through outdoor road experiments.

The aerodynamic drag force has a relevant effect on cycling performance since it is one of the major resistive forces acting on the bicycle. For this reason, this paper presents the development of an experimental methodology to estimate the aerodynamic parameters of a bicycle-cyclist set. The methodology combines outdoor measurements to estimate the drag area with indoor measurements to measure the projected frontal area. The methodology was implemented to quantify the effect of posture in the aerodynamic parameters of a group of cyclists. The tests were performed to characterize the drag parameters associated with three postures defined by the position of the grip on the handlebar: tops, hoods, and drops. Significant differences in the aerodynamic parameters were found for the postures studied through the proposed methodology. The posture variation led to reductions of up to 11.8% in the drag area of the cyclists when passing from tops to drops posture. The results obtained are in agreement with the literature indicating that the implementation of the methodology is feasible for the estimation of the aerodynamic parameters in cycling.