Evaluation of aerodynamic and rolling resistances in mountain-bike field conditions

An Algorithm to Predict E-Bike Power Consumption Based on Planned Routes

E-bikes, i.e., bikes equipped with a small electrical engine, are becoming increasingly widespread, thanks to their positive contribution to mobility and sustainability. A key component of an e-bike is the battery that feeds the drive unit: clearly, the higher the capacity of the battery, the longer the distances that the biker will cover under engine support. On the negative side, the additional weight incurred by the electric components is likely to ruin the riding experience in case the battery runs out of power. For this reason, an integrated hardware-software system that provides accurate information about the remaining range is essential, especially for older or “not-in-shape” bikers. Many e-bikes systems are already equipped with a small control unit that displays useful information, such as speed, instantaneous power consumption, and estimated range as well. Existing approaches rely on machine learning techniques applied to collected data, or even on the remaining battery capacity and the assistance level required by the drive unit. They do not consider crucial aspects of the planned route, in particular the difference in altitude, the combined weight of bike and biker, and road conditions. In this paper, we propose a mathematical model implemented in an application to compute battery consumption, and hence the presumed remaining range, in a more accurate way. Our application relies on external sources to compute the route and the elevation data of a number of intermediate points. We present the mathematical model on which our application is based, we show the implemented application in shape of an app, and we report the results of the experiments.

Caveats and Recommendations to Assess the Validity and Reliability of Cycling Power Meters: A Systematic Scoping Review

A large number of power meters have become commercially available during the last decades to provide power output (PO) measurement. Some of these power meters were evaluated for validity in the literature. This study aimed to perform a review of the available literature on the validity of cycling power meters. PubMed, SPORTDiscus, and Google Scholar have been explored with PRISMA methodology. A total of 74 studies have been extracted for the reviewing process. Validity is a general quality of the measurement determined by the assessment of different metrological properties: Accuracy, sensitivity, repeatability, reproducibility, and robustness. Accuracy was most often studied from the metrological property (74 studies). Reproducibility was the second most studied (40 studies) property. Finally, repeatability, sensitivity, and robustness were considerably less studied with only 7, 5, and 5 studies, respectively. The SRM power meter is the most used as a gold standard in the studies. Moreover, the number of participants was very different among them, from 0 (when using a calibration rig) to 56 participants. The PO tested was up to 1700 W, whereas the pedalling cadence ranged between 40 and 180 rpm, including submaximal and maximal exercises. Other exercise conditions were tested, such as torque, position, temperature, and vibrations. This review provides some caveats and recommendations when testing the validity of a cycling power meter, including all of the metrological properties (accuracy, sensitivity, repeatability, reproducibility, and robustness) and some exercise conditions (PO range, sprint, pedalling cadence, torque, position, participant, temperature, vibration, and field test).

Influence of wheel rim width on rolling resistance and off-road speed in cross-country mountain biking

The rim width of cross-country mountain bike wheel sets has increased in recent years, but the effect of this increase on performance remains unknown. The aim of this study was to analyse the influence of rim width on rolling resistance and off-road speed. We compared 3 tubeless wheel sets: 25 mm inner width as baseline, 30 mm width with the same tyre stiffness, and 30 mm width with the same tyre pressure. Three riders conducted 75 rolling resistance tests for each wheel set on a cross-country course. We determined rolling resistance using the virtual elevation method and calculated off-road speeds for flat and uphill conditions using a mathematical model. Baseline rolling resistance (C_r) was 0.0298, 90% CI [0.0286, 0.0310], which decreased by 1.4%, [0.7, 2.2] with the wider rim and the same tyre stiffness and increased by 0.9%, [0.1, 1.6] with the wider rim and the same tyre pressure. The corresponding effects on off-road speed were most likely trivial (0.0% to 0.7% faster and 0.1% to 0.6% slower, respectively). Because the effect of rim width on off-road speed seems negligible, athletes should choose the rim width that offers the best bike handling and should experiment with low tyre pressures.

Physical characteristics and resistance parameters of typical urban cyclists

This study investigates the rolling and drag resistance parameters and bicycle and cargo masses of typical urban cyclists. These factors are important for modelling of cyclist speed, power and energy expenditure, with applications including exercise performance, health and safety assessments and transportation network analysis. However, representative values for diverse urban travellers have not been established. Resistance parameters were measured utilizing a field coast-down test for 557 intercepted cyclists in Vancouver, Canada. Masses were also measured, along with other bicycle attributes such as tire pressure and size. The average (standard deviation) of coefficient of rolling resistance, effective frontal area, bicycle plus cargo mass, and bicycle-only mass were 0.0077 (0.0036), 0.559 (0.170) m², 18.3 (4.1) kg, and 13.7 (3.3) kg, respectively. The range of measured values is wider and higher than suggested in existing literature, which focusses on sport cyclists. Significant correlations are identified between resistance parameters and rider and bicycle attributes, indicating higher resistance parameters for less sport-oriented cyclists. The findings of this study are important for appropriately characterising the full range of urban cyclists, including commuters and casual riders.

The categorization of amateur cyclists as research participants: findings from an observational study

Sampling bias is an issue for research involving cyclists. The heterogeneity of cyclist populations, on the basis of skill level and riding purpose, can generate incorrect inferences about one specific segment of the population of interest. In addition, a more accurate categorization would be helpful when physiological parameters are not available. This study proposes using self-reported data to categorize amateur cyclist types by varying skill levels and riding purposes, therefore improving sample selection in experimental studies. A total of 986 cyclists completed an online questionnaire between February and October 2016. Two-step cluster analyses were performed to generate distinct groups, and dependent variables of these groups were compared (demographics and characteristics of cycling practice). The cluster analysis relied on 4 descriptors (cycling weekly volume, average cycling speed, riding purpose, and cycling discipline) and yielded five distinct groups: competitive road, recreational road, competitive mountain bike (MTB), recreational MTB and competitive triathlon. Among these groups, averages and distributions for age, height, body mass, body mass index, training volume and intensity, and years of experience varied. This categorization can potentially help researchers recruit specific groups of cyclists based upon self-reported data and therefore better align the sample characteristic with the research aims.

Validity of a device designed to measure braking power in bicycle disc brakes

Real-world cycling performance depends not only on exercise capacities, but also on efficiently traversing the bicycle through the terrain. The aim of this study was to determine if it was possible to quantify the braking done by a cyclist in the field. One cyclist performed 408 braking trials (348 on a flat road; 60 on a flat dirt path) over 5 days on a bicycle fitted with brake torque and angular velocity sensors to measure brake power. Based on Newtonian physics, the sum of brake work, aerodynamic drag and rolling resistance was compared with the change in kinetic energy in each braking event. Strong linear relationships between the total energy removed from the bicycle-rider system through braking and the change in kinetic energy were observed on the tar-sealed road (r² = 0.989; p < 0.0001) and the dirt path (r² = 0.952; p < 0.0001). T-tests revealed no difference between the total energy removed and the change in kinetic energy on the road (p = 0.715) or dirt (p = 0.128). This study highlights that brake torque and angular velocity sensors are valid for calculating brake power on the disc brakes of a bicycle in field conditions. Such a device may be useful for investigating cyclists' ability to traverse through various terrains.

Reliability of the virtual elevation method to evaluate rolling resistance of different mountain bike cross-country tyres

Although a low rolling resistance is advantageous in mountain bike cross-country racing, no studies have used the virtual elevation method to compare tyres from different manufacturers as used in international competitions so far. The aims of this study were to assess the reliability of this method, to compare the off-road rolling resistance between tyres and to calculate the influence on off-road speed. Nine 29-in. mountain bike cross-country tyres were tested on a course representing typical ground surface conditions 5 or 6 times. The coefficient of rolling resistance was estimated with the virtual elevation method by 3 investigators and corresponding off-road speeds were calculated. The virtual elevation method was highly reliable (typical error = 0.0006, 2.8%; limits of agreement <0.0005, r ≥ 0.98). The mean coefficient of rolling resistance was 0.0219 and differed from 0.0205 to 0.0237 (P < 0.001) between tyres. The calculated differences in off-road speed amounted to 2.9-3.2% (0% slope) and 2.3-2.4% (10% slope) between the slowest and the fastest tyre. The reliability of the method and the differences in rolling resistance between the tyres illustrate the value of testing tyres for important competitions on a representative ground surface using the virtual elevation method.

Performance differences when using 26- and 29-inch-wheel bikes in Swiss National Team cross-country mountain bikers

The purpose of this study was to analyse the effect of bike type - the 26-inch-wheel bike (26" bike) and the 29-inch-wheel bike (29" bike) - on performance in elite mountain bikers. Ten Swiss National Team athletes (seven males, three females) completed six trials with individual start on a simulated cross-country course with 35 min of active recovery between trials (three trials on a 26" bike and three trials on a 29" bike, alternate order, randomised start-bike). The course consisted of two separate sections expected to favour either the 29" bike (section A) or the 26" bike (section B). For each trial performance, power output, cadence and heart rate were recorded and athletes' experiences were documented. Mean overall performance (time: 304 ± 27 s vs. 311 ± 29 s; P < 0.01) and performance in sections A (P < 0.001) and B (P < 0.05) were better when using the 29" bike. No significant differences were observed for power output, cadence or heart rate. Athletes rated the 29" bike as better for performance in general, passing obstacles and traction. The 29" bike supports superior performance for elite mountain bikers, even on sections supposed to favour the 26" bike.

The influence of tyre characteristics on measures of rolling performance during cross-country mountain biking

This investigation sets out to assess the effect of five different models of mountain bike tyre on rolling performance over hard-pack mud. Independent characteristics included total weight, volume, tread surface area and tread depth. One male cyclist performed multiple (30) trials of a deceleration field test to assess reliability. Further tests performed on a separate occasion included multiple (15) trials of the deceleration test and six fixed power output hill climb tests for each tyre. The deceleration test proved to be reliable as a means of assessing rolling performance via differences in initial and final speed (coefficient of variation (CV) = 4.52%). Overall differences between tyre performance for both deceleration test (P = 0.014) and hill climb (P = 0.032) were found, enabling significant (P < 0.0001 and P = 0.049) models to be generated, allowing tyre performance prediction based on tyre characteristics. The ideal tyre for rolling and climbing performance on hard-pack surfaces would be to decrease tyre weight by way of reductions in tread surface area and tread depth while keeping volume high.