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Bicycle change strategy for uphill time-trial races
Abstract
In uphill time-trial cycling races, riders have to travel along routes characterized by high-gradient variations in the shortest time possible. Due to this gradient variation, the appropriate selection among time-trial bicycles and traditional road bicycles is essential to reduce the power demand. For some uphill courses, the bicycle selection is not necessarily unique, with the possibility of a bicycle change during the race to take advantage of the performance of each type of bicycle for specific sections of the route. In this study, a method for planning the bicycle-changing strategy is proposed. A dynamic model to predict the race time for two types of bicycles is implemented, and an optimization problem for minimizing the race time is presented. A case study is analyzed in which the uphill time-trial route of the Giro d’Italia 2014 is studied in the context of professional cyclists’ performance. It was found that the use of the bicycle change strategy led to a time saving of about 43 s with respect to the time obtained when using only a road bicycle. It was also found that a combination of the bicycle change strategy with an optimal pacing strategy led to a time saving of about 92 s.
... Some approaches focus on reducing the resistive forces opposing the motion, for example, by reducing aerodynamic drag [1]. Some aim at improving the forces driving the motion, for example, by selecting components [2,3]. Some others seek to improve the path used to travel the route, for example, by reducing the distance or improving the vehicle dynamics [4,5]. ...
... with representing a parameter to define the range of power delivered. In this model, was set as 2 according to Roa and Muñoz [2]. ...
Pacing strategies are used in cycling to optimize the power delivered by the cyclist during a race. Gains in race time have been obtained when using these strategies compared to self-paced approaches. For this reason, this study is focused on revising the effect that the variation of the cyclist's parameters has on the pacing strategy and its results.
A numeric method was used to propose pacing strategies for a cyclist riding on an ascending 3.7 km route with a constant 6.26% road grade. The method was validated and then implemented to study the effect of aerobic and anaerobic power delivery capacity, mass, and drag area on the pacing strategies and their corresponding estimated race times.
The results showed that modifying 1% of the aerobic capacity or cyclist mass value led to a change of 1% on the race time. Modifying 1% the anaerobic capacity and the drag area led to changes of 0.03% and 0.02% on the race time, respectively. These results are strongly dependent on the route characteristics.
It was concluded that for the studied route (constantly ascending), the variation of the cyclist's aerobic capacity influences the pacing strategy (i.e., the power delivery over the distance). The anaerobic capacity and mass of the cyclist also influence the pacing strategy to a lesser extent.
... The intra-class distance within (a) of a dataset is the minimum average distance between each object in a cluster and all other objects in the same cluster. The intra-class distance of the entire sample data is the maximum value of the intra-class distance in all clusters [13], then: ...
With the rapid development of China’s social economy and the improvement of the level of urbanization, urban transportation has also been greatly developed. With the booming development of the internet and the sharing economy industry, shared bicycles have emerged as the times requirement. Shared bicycles are a new type of urban transportation without piles. As a green way of travel, shared bicycles have the advantages of convenience, fashion, green, and environmental protection. However, many problems have also arisen in the use of shared bicycles, such as man-made damage to the vehicle, the expiration of the service life of the vehicle, etc. These problems are unavoidable, and the occurrence of these failure problems will also cause serious harm to the use of shared bicycles. This article aims to study the path optimization of shared bicycles considering the recovery of faulty vehicles during dispatching. Based on the K-means spatial data clustering algorithm, a path optimization experiment of shared bicycle recycling scheduling considering the recycling of faulty vehicles is carried out. The experiment concluded that the shared bicycle recycling scheduling path based on K-means clustering planning significantly reduces the total time spent and the total cost of performing recycling scheduling tasks. Among them, the unit price of recycling and dispatching of each faulty shared bicycle has dropped by 4.1 yuan compared with the market unit price. The conclusion shows that the shared bicycle recycling scheduling path considering faulty vehicle recycling based on K-means clustering algorithm has been greatly optimized.
... First, the results obtained in this study for performance and comfort could be further refined by including other relevant variables. For example, considering requirements associated with the bicycle stability [50,51] and pacing strategies [52,53] could be explored. Second, the methodology for the selection of posture could be implemented for a group of cyclists with homogeneous characteristics for a statistically based study. ...
In individual time-trial cycling races (TT), the interest of the cyclists in improving aerodynamics increases because the rider has to overcome the wind drag effect without the advantages of drafting for riding behind another cyclist. For this reason, in some races, the riders use aerobars (Figure 1) to support the elbows closer to the bicycle with aerodynamic advantages [1]. The aerobars postures are associated with a drop in the power delivery capacity [2-4] and an increased difficulty to sustain the posture for long periods due to discomfort. It is possible to find some suggestions for the definition of posture when riding in aerobars [5-7]. Nevertheless, studies on the effect of postural parameters in aerobars postures are scarce.
In this context, a methodology was developed to study the influence that variations in the body posture when riding in aerobars have on the performance of cyclists and their interaction with the bicycle [8]. The methodology is based on an optimization problem that minimizes race time subject to constraints associated with the interaction between the bicycle and the cyclist. This interaction is represented through the pressures and the vibration levels in contact areas. The methodology was implemented in a numerical code for the posture optimization of cyclists.
Five cyclists were included in the study with their bicycles. The power delivery capacity and drag area, vibration transmission, and pressure in contact areas were measured. The postures were defined by the aerobars’ height fit limits of each bicycle (named ABhigh for upper bound and ABlow for lower bound). A 20-km race and various road inclinations and wind speeds were considered in the study.
It was concluded that postures with intermediate aerobars’ heights are identified as optimal solutions for conditions in which the interaction constraints modify the solution. For the other cases, the optimal solution lies on one of the boundary postures.
... First, the results obtained in this study for performance and comfort could be further refined by including other relevant variables. For example, considering requirements associated with the bicycle stability [50,51] and pacing strategies [52,53] could be explored. Second, the methodology for the selection of posture could be implemented for a group of cyclists with homogeneous characteristics for a statistically based study. ...
Featured Application: Optimization of performance in time-trial cycling events through the selection of posture while considering comfort. Abstract: 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.
This investigation sought to determine if cycling power could be accurately modeled. A mathematical model of cycling power was derived, and values for each model parameter were determined. A bicycle-mounted power measurement system was validated by comparison with a laboratory ergometer. Power was measured during road cycling, and the measured values were compared with the values predicted by the model. The measured values for power were highly correlated (R2 = .97) with, and were not different than, the modeled values. The standard error between the modeled and measured power (2.7 W) was very small. The model was also used to estimate the effects of changes in several model parameters on cycling velocity. Over the range of parameter values evaluated, velocity varied linearly (R2 > .99). The results demonstrated that cycling power can be accurately predicted by a mathematical model.
This review presents information that is useful to athletes, coaches and exercise scientists in the adoption of exercise protocols, prescription of training regimens and creation of research designs. Part 2 focuses on the factors that affect cycling performance. Among those factors, aerodynamic resistance is the major resistance force the racing cyclist must overcome. This challenge can be dealt with through equipment technological modifications and body position configuration adjustments. To successfully achieve efficient transfer of power from the body to the drive train of the bicycle the major concern is bicycle configuration and cycling body position. Peak power output appears to be highly correlated with cycling success. Likewise, gear ratio and pedalling cadence directly influence cycling economy/efficiency. Knowledge of muscle recruitment throughout the crank cycle has important implications for training and body position adjustments while climbing. A review of pacing models suggests that while there appears to be some evidence in favour of one technique over another, there remains the need for further field research to validate the findings. Nevertheless, performance modelling has important implications for the establishment of performance standards and consequent recommendations for training.
Computing the optimal pacing strategy for cycling time trials can be formulated as an optimal control problem, where a mechanical model and a physiological endurance model form the dynamical system and time to complete the track is to be minimized. We review approaches that use the 3-parameter critical power model to compute optimal pacing strategies and modify it to become a smooth 6-parameter endurance model. Due to its 3 additional parameters, it is more flexible to model the physiological dynamics appropriately. Besides, we demonstrate that this model has favourable numerical properties that allow to eliminate purely mathematical workarounds to compute an approximate optimal pacing for the original 3-parameter critical power model. An established simplification of the 3-parameter critical power model is considered for a comparison of numerically computed optimal pacing strategies on an artificial track with continuously varying slope subject to these variants of the 3-parameter critical power model. It is shown, that the optimal pedalling power subject to the original model exhibits unrealistically large variations, which are smoothed heavily by the simplified model. The 6-parameter endurance model turns out to be a flexible model, that exhibits intermediate variations in the optimal pedalling power, while being numerically well behaved. The methods used in this contribution are extensible and can be used for the computation of optimal pacing strategies in conjunction with more sophisticated physiological models.
In cycling at race speeds, 90% of total resistance opposing motion, R T(N) T depends on aerodynamic drag of air, which is directly proportional to the effective frontal area, AC d(m2). R T was measured on a cyclist, in an open velodrome, in order to evaluate AC d in four different positions on a traditional bicycle: upright d position (UP), dropped position (DP), aero position (AP) and Obree's position (OP : the hands in support under the chest, the forearms tucked on the arms, the trunk tilted forward). R T was determined at different constant speeds, Vc(m s−1) with a special device (Max One), which allows the measurement of the external mechanical power P ext(W) in real conditions of cycling locomotion ext (R T = P extVc−1). Experiments were carried out in order to test the validity and the reproducibility of P ext provided by the measurement device. P ext was measured twice in the same experimental conditions (exercise on a treadmill against slopes varying from 1 to 14%) and no significant difference was observed between the two measurement series. A systematic measurement error was observed allowing the use of a correcting factor. As expected, in the four rider positions, R T increased linearly (p
In elite cycling the resistive force is dominated by aerodynamics. Be it on the roads or in the velodrome, the sport has many
examples where aerodynamics has won and lost races. Since the invention of the bicycle, engineers have strived to improve
performance, often by reducing aerodynamic drag. Over the last 50 years a number of authors have presented their efforts in
journals, books and magazines. This review summarises the publications that show the continued development in the aerodynamics
of cycling. The review concludes by examining the shortcomings of the current understanding and making suggestions for future
research and development.
This paper documents a wind tunnel test program that measured the aerodynamic drag (Fd), lift (Fl) and side force (Fs) of 12 contemporary time trial (TT) helmets at yaw angles of 0 to 15∘. Fd measurements at yaw were subjected to a novel analysis technique adapted from the automotive fuel efficiency literature to provide a single wind averaged drag at a velocity (v) of 14.75 m sec−1 (53 km/h). Ranked wind averaged Fd measurements of TT helmets provide a simple performance index and it is recommended that this analytical procedure be adopted by the bike industry to permit uniform Fd comparisons of helmets, wheels, frames and other components that are subjected to yaw angle wind tunnel tests.
When cycling on level ground at a speed greater than 14 m/s, aerodynamic drag is the most important resistive force. About 90% of the total mechanical power output is necessary to overcome it. Aerodynamic drag is mainly affected by the effective frontal area which is the product of the projected frontal area and the coefficient of drag. The effective frontal area represents the position of the cyclist on the bicycle and the aerodynamics of the cyclist-bicycle system in this position. In order to optimise performance, estimation of these parameters is necessary. The aim of this study is to describe and comment on the methods used during the last 30 years for the evaluation of the effective frontal area and the projected frontal area in cycling, in both laboratory and actual conditions. Most of the field methods are not expensive and can be realised with few materials, providing valid results in comparison with the reference method in aerodynamics, the wind tunnel. Finally, knowledge of these parameters can be useful in practice or to create theoretical models of cycling performance.
Previous theoretical research found that varying power slightly to counter external conditions may result in improved performance during cycling time trialing, but it is not known whether such power variations result in added physiological stress. Thus, the purpose of this study was to determine whether variable power (VP) cycling produced greater physiological stress than constant power (CP) cycling of the same mean intensity.
Eight trained male cyclists (age 28 +/- 2 yr, mass 74.4 +/- 2.3 kg, VO2max 4.24 +/- 0.13 L x min(-1), weekly training 277 +/- 44 km) performed three 1-h ergometer trials. The first trial was performed at a self-paced maximal effort. The mean power from that trial was used to determine the power for the CP trial (constant effort at mean power) and the VP trial (alternating +/- 5% of mean power every 5 min).
No differences were found between the CP and VP trials in mean VO2 (CP 3.33 +/- 0.11 L x min(-1), VP 3.26 +/- 0.12 L x min(-1)), mean heart rate (CP 158 +/- 3 min(-1), VP 159 +/- 3 min(-1)), mean blood lactate concentration (CP 4.2 +/- 0.7 mM, VP 4.3 +/- 0.7 mM), or mean RPE (CP 13.9 +/- 0.4, VP 14.1 +/- 0.4).
Therefore, during a strenuous 1-h effort (78% of VO2max), subjects experienced no additional physiological stress by varying power +/- 5% compared with that during a constant power effort.
In this holistic review of cycling science, the objectives are: (1) to identify the various human and environmental factors that influence cycling power output and velocity; (2) to discuss, with the aid of a schematic model, the often complex interrelationships between these factors; and (3) to suggest future directions for research to help clarify how cycling performance can be optimized, given different race disciplines, environments and riders. Most successful cyclists, irrespective of the race discipline, have a high maximal aerobic power output measured from an incremental test, and an ability to work at relatively high power outputs for long periods. The relationship between these characteristics and inherent physiological factors such as muscle capilliarization and muscle fibre type is complicated by inter-individual differences in selecting cadence for different race conditions. More research is needed on high-class professional riders, since they probably represent the pinnacle of natural selection for, and physiological adaptation to, endurance exercise. Recent advances in mathematical modelling and bicycle-mounted strain gauges, which can measure power directly in races, are starting to help unravel the interrelationships between the various resistive forces on the bicycle (e.g. air and rolling resistance, gravity). Interventions on rider position to optimize aerodynamics should also consider the impact on power output of the rider. All-terrain bicycle (ATB) racing is a neglected discipline in terms of the characterization of power outputs in race conditions and the modelling of the effects of the different design of bicycle frame and components on the magnitude of resistive forces. A direct application of mathematical models of cycling velocity has been in identifying optimal pacing strategies for different race conditions. Such data should, nevertheless, be considered alongside physiological optimization of power output in a race. An even distribution of power output is both physiologically and biophysically optimal for longer ( > 4 km) time-trials held in conditions of unvarying wind and gradient. For shorter races (e.g. a 1 km time-trial), an 'all out' effort from the start is advised to 'save' time during the initial phase that contributes most to total race time and to optimize the contribution of kinetic energy to race velocity. From a biophysical standpoint, the optimum pacing strategy for road time-trials may involve increasing power in headwinds and uphill sections and decreasing power in tailwinds and when travelling downhill. More research, using models and direct power measurement, is needed to elucidate fully how much such a pacing strategy might save time in a real race and how much a variable power output can be tolerated by a rider. The cyclist's diet is a multifactorial issue in itself and many researchers have tried to examine aspects of cycling nutrition (e.g. timing, amount, composition) in isolation. Only recently have researchers attempted to analyse interrelationships between dietary factors (e.g. the link between pre-race and in-race dietary effects on performance). The thermal environment is a mediating factor in choice of diet, since there may be competing interests of replacing lost fluid and depleted glycogen during and after a race. Given the prevalence of stage racing in professional cycling, more research into the influence of nutrition on repeated bouts of exercise performance and training is required.
This review presents information that is useful to athletes, coaches and exercise scientists in the adoption of exercise protocols, prescription of training regimens and creation of research designs. Part 2 focuses on the factors that affect cycling performance. Among those factors, aerodynamic resistance is the major resistance force the racing cyclist must overcome. This challenge can be dealt with through equipment technological modifications and body position configuration adjustments. To successfully achieve efficient transfer of power from the body to the drive train of the bicycle the major concern is bicycle configuration and cycling body position. Peak power output appears to be highly correlated with cycling success. Likewise, gear ratio and pedalling cadence directly influence cycling economy/efficiency. Knowledge of muscle recruitment throughout the crank cycle has important implications for training and body position adjustments while climbing. A review of pacing models suggests that while there appears to be some evidence in favour of one technique over another, there remains the need for further field research to validate the findings. Nevertheless, performance modelling has important implications for the establishment of performance standards and consequent recommendations for training.
The aims of this study were to measure the aerodynamic drag in professional cyclists, to obtain aerodynamic drag reference values in static and effort positions, to improve the cyclists' aerodynamic drag by modifying their position and cycle equipment, and to evaluate the advantages and disadvantages of these modifications. The study was performed in a wind tunnel with five professional cyclists. Four positions were assessed with a time-trial bike and one position with a standard racing bike. In all positions, aerodynamic drag and kinematic variables were recorded. The drag area for the time-trial bike was 31% higher in the effort than static position, and lower than for the standard racing bike. Changes in the cyclists' position decreased the aerodynamic drag by 14%. The aero-helmet was not favourable for all cyclists. The reliability of aerodynamic drag measures in the wind tunnel was high (r > 0.96, coefficient of variation < 2%). In conclusion, we measured and improved the aerodynamic drag in professional cyclists. Our results were better than those of other researchers who did not assess aerodynamic drag during effort at race pace and who employed different wheels. The efficiency of the aero-helmet, and the validity, reliability, and sensitivity of the wind tunnel and aerodynamic field testing were addressed.
During the individual time-trial competitions in cycling, the cyclist’s skills are essential, but it is also important the race strategy. The race strategy includes the manner in which the cyclist competes and the selection and set-up of the cycling equipment. For hilly time-trials, part of the race strategy consists of the right selection of the bike type. Depending on the characteristics of the road such as total distance and altitude profile, a time-trial bike or a traditional road bike could be used. Additionally, in some races it is possible to change bike type as a part of the strategy. This strategy seeks to take advantage of time-trial bikes during low gradient sections and to take advantage of road bikes during high gradient sections. The purpose of this work is to plan an optimal bike change strategy to determine if it is advantageous to change the bike type, and if so, to find the point of the route where the change minimizes race time. The optimal planning methodology is based on a bike model, a simplified altitude profile and an optimization problem. A model parameters identification process is performed based on experimental tests in a hilly route. This route is used as a case study for the optimal planning of the bike change strategy.
To reduce air resistance, time trial cyclists and triathletes lower their torso angle. The aim of this study was to investigate the effect of lowering time trial torso angle positions on muscle activation patterns and crank torque coordination. It was hypothesized that small torso angles yield a forward shift of the muscle activation timing and crank torque. Twenty-one trained cyclists performed three exercise bouts at 70% maximal aerobic power in a time trial position at three different torso angles (0°, 8°, and 16°) at a fixed cadence of 85 rpm. Measurements included surface electromyography, crank torques and gas exchange. A significant increase in crank torque range and forward shift in peak torque timing was found at smaller torso angles. This relates closely with the later onset and duration of the muscle activation found in the gluteus maximus muscle. Torso angle effects were only observed in proximal monoarticular muscles. Moreover, all measured physiological variables (oxygen consumption, breathing frequency, minute ventilation) were significantly increased with lowering torso angle and hence decreased the gross efficiency. The findings provide support for the notion that at a cycling intensity of 70% maximal aerobic power, the aerodynamic gains outweigh the physiological/biomechanical disadvantages in trained cyclists.
© 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Abstract To reduce aerodynamic resistance cyclists lower their torso angle, concurrently reducing Peak Power Output (PPO). However, realistic torso angle changes in the range used by time trial cyclists have not yet been examined. Therefore the aim of this study was to investigate the effect of torso angle on physiological parameters and frontal area in different commonly used time trial positions. Nineteen well-trained male cyclists performed incremental tests on a cycle ergometer at five different torso angles: their preferred torso angle and at 0, 8, 16 and 24°. Oxygen uptake, carbon dioxide expiration, minute ventilation, gross efficiency, PPO, heart rate, cadence and frontal area were recorded. The frontal area provides an estimate of the aerodynamic drag. Overall, results showed that lower torso angles attenuated performance. Maximal values of all variables, attained in the incremental test, decreased with lower torso angles (P < 0.001). The 0° torso angle position significantly affected the metabolic and physiological variables compared to all other investigated positions. At constant submaximal intensities of 60, 70 and 80% PPO, all variables significantly increased with increasing intensity (P < 0.0001) and decreasing torso angle (P < 0.005). This study shows that for trained cyclists there should be a trade-off between the aerodynamic drag and physiological functioning.
Cycling performance is strongly dependent on aerodynamic drag, of which the majority is attributable to the rider.
Previous studies have shown the importance of optimising athlete posture on the bicycle for individual time-trial events.
This article identifies that performance in road cycling and draft-legal triathlon can be improved through aerodynamic
optimisation of the athlete’s posture. Nine relevant cycling postures have been studied, and it was found that for road
cycling, gripping the hoods with horizontal forearms can reduce the required cyclist power by 13.4%, and for draft-legal
triathlon applications, the use of short bar extensions reduced the required power by up to 16.7%. It was also found that
lowering the eyes and head increased drag in both drops and triathlon postures. Measurements of the velocity profiles
of the wake of a cyclist in four different postures are presented, and it is shown that differences in drag coefficients
between postures can be correlated with changes in the wake velocity defect and turbulence intensity distribution.
Abstract The wide-spread use of power-meters in today's competitive road cycling has been an incentive for optimizing the distribution of power output i.e. the pacing strategy. Therefore, the aim of this study was to examine the effects of course profile on the optimal pacing strategy in road cycling. For that reason, three course profiles, built up by cubical splines, were simulated with a numerical program for a fictional cyclist. The numerical program solves the equations of motion of the athlete and bicycle while an optimal design algorithm is connected to the simulation, aiming to minimize the time between start and finish. The optimization is constrained by a power-endurance concept named the critical power model for intermittent exercise. Three course profiles with the same total elevation but different number of hills were studied. The time gains of an optimized pacing strategy were 3.0%, 5.0%, and 2.3% and the speed variances at the optimized pacing strategy were 6.54%, 1.18%, and 0.84% for the single plateau, double hill, and quadruple hill courses respectively. Hence, the course profile has great effect on the optimal pacing strategy. In addition, the results show that the potential improvement of adopting an optimized pacing strategy is substantial at the highest level of competition.
The aerodynamic drag of a cyclist in time trial (TT) position is strongly influenced by the torso angle. While decreasing the torso angle reduces the drag, it limits the physiological functioning of the cyclist. Therefore the aims of this study were to predict the optimal TT cycling position as function of the cycling speed and to determine at which speed the aerodynamic power losses start to dominate. Two models were developed to determine the optimal torso angle: a ‘Metabolic Energy Model' and a ‘Power Output Model'. The Metabolic Energy Model minimized the required cycling energy expenditure, while the Power Output Model maximized the cyclists' power output. The input parameters were experimentally collected from 19 TT cyclists at different torso angle positions (0–24°). The results showed that for both models, the optimal torso angle depends strongly on the cycling speed, with decreasing torso angles at increasing speeds. The aerodynamic losses outweigh the power losses at cycling speeds above 46 km/h. However, a fully horizontal torso is not optimal. For speeds below 30 km/h, it is beneficial to ride in a more upright TT position. The two model outputs were not completely similar, due to the different model approaches. The Metabolic Energy Model could be applied for endurance events, while the Power Output Model is more suitable in sprinting or in variable conditions (wind, undulating course, etc.). It is suggested that despite some limitations, the models give valuable information about improving the cycling performance by optimizing the TT cycling position.
A bicycle and its rider are strongly impeded by their resistance to the flow of air. Aerodynamic stratagems have brought vehicles that can go 60 miles per hour on a level road without assistance. This article discusses techniques for drag reduction and reviews aerodynamic data for various human powered vehicles.
Another way of improving time trial performance is by reducing the power demand of riding at a certain velocity. Riding with hands on the brake hoods would improve aerodynamics and increase performance time by ≈5 to 7 minutes and riding with hands on the handlebar drops would increase performance time by 2 to 3 minutes compared with a baseline position (elbows on time trail handle bars). Conversely, riding with a carefully optimised position could decrease performance time by 2 to 2.5 minutes. An aerodynamic frame saved the modelled riders 1:17 to 1:44 min:sec. Furthermore, compared with a conventional wheel set, an aerodynamic wheel set may improve time trial performance time by 60 to 82 seconds. From the analysis in this article it becomes clear that novice cyclists can benefit more from the suggested alterations in position, equipment, nutrition and training compared with elite cyclists. Training seems to be the most important factor, but sometimes large improvements can be made by relatively small changes in body position. More expensive options of performance improvement include altitude training and modifications of equipment (light and aerodynamic bicycle and wheels). Depending on the availability of time and financial resources cyclists have to make decisions about how to achieve their performance improvements. The data presented here may provide a guideline to help make such decisions.
The basis of the critical power concept is that there is a hyperbolic relationship between power output and the time that the power output can be sustained. The relationship can be described based on the results of a series of 3 to 7 or more timed all-out predicting trials. Theoretically, the power asymptote of the relationship, CP (critical power), can be sustained without fatigue; in fact, exhaustion occurs after about 30 to 60 minutes of exercise at CP. Nevertheless, CP is related to the fatigue threshold, the ventilatory and lactate thresholds, and maximum oxygen uptake (V̇O2max), and it provides a measure of aerobic fitness. The second parameter of the relationship, AWC (anaerobic work capacity), is related to work performed in a 30-second Wingate test, work in intermittent high-intensity exercise, and oxygen deficit, and it provides a measure of anaerobic capacity. The accuracy of the parameter estimates may be enhanced by careful selection of the power outputs for the predicting trials and by performing a greater number of trials. These parameters provide fitness measures which are mode-specific, combine energy production and mechanical efficiency in 1 variable, and do not require the use of expensive equipment or invasive procedures. However, the attractiveness of the critical power concept diminishes if too many predicting trials are required for generation of parameter estimates with a reasonable degree of accuracy.
Aerodynamically efficient sports equipment/accessories and athlete body postures are considered to be the fundamental aspect to achieve superior performance. Like other speed sports, the aerodynamic optimisation is more crucial in cycling. A standard full-scale testing methodology for the aerodynamic optimisation of a cyclist along with all accessories (e.g., bicycle, helmet, cycling suit, shoes and goggle) is not well developed, documented, and standardised. This paper describes a design and development of a full-scale testing methodology for the measurement of aerodynamic properties as a function of cyclist body positions along with various accessories over a range of wind speeds. The experimental findings indicate that the methodology can be used for aerodynamic optimisation of all cycling sports.
When studying events involving locomotive exercise, such as cross-country skiing, one generally assumes that pacing strategies (i.e. power distributions) have a significant impact on performance. In order to better understand the importance of pacing strategies, a program is developed for numerical simulation and optimization of the pacing strategy in cross-country ski racing. This program computes the optimal pacing strategy for an arbitrary athlete skiing on a delineated course. The locomotion of the skier is described by introducing the equations of motion for cross-country skiing. A transformation of the motion equations is carried out in order to improve the simulation. Furthermore, a nonlinear optimization routine is connected to the simulation program. Simulation and optimization are performed on a fictional male skier. Results show that it is possible to attain an optimal pacing strategy by simulating cross-country skiing while connecting nonlinear optimization routines to the simulation. It is also shown that an optimal pacing strategy is characterized by minor variations in speed. In our opinion, this kind of optimization could serve as essential preparations before important competitions.
Many time-trial and triathlon bicycle races take place on relatively flat,
closed-circuit courses. In the absence of hills, riding-speed is limited almost
solely by aerodynamic drag; consequently, winds can have a big effect on
elapsed times. I analyze the special case of a straight out-and-back race in a
steady wind, assuming the rider has a given total amount of energy to expend
and can choose only two speeds - the aided speed with tailwind and the hindered
speed into headwind. In this ideal circumstance the problem of choosing optimal
riding speeds reduces to a constrained nonlinear optimization that can be
solved with elementary calculus. My analysis reveals a practical rule of thumb
that can be used more generally to choose optimal riding speeds for time-trial
racing on closed-circuit courses in the presence of headwinds and tailwinds.
Recreational cycling and professional cycle tours have prompted cycle components and accessories to be designed with drag reduction as a first priority. This is especially so in the case of bicycle wheels. This paper describes wind tunnel tests carried out on a number of designs of racing bicycle wheels ranging from a standard 32 spoke wheel, through wheels with aerodynamic rims and spokes, to a solid disc wheel to determine the axial drag and side force coefficients on the wheels and to make comparisons. The tests were performed at relative wind velocities (30–60km/h) and yaw angles (0–30°) corresponding to those encountered by the racing cyclist. Each wheel was found to exhibit its own particular characteristic curve which was only weakly influenced by the wheel rotational speed. The aerodynamically designed wheels showed reductions in axial drag of up to 50% when compared with the spoked wheel. The corresponding side force however increased. Cognizance should be taken of local atmospheric conditions when deciding on the design of wheel to use in a particular event.
The pioneering efforts to reduce drag of an aeroplane wheel with spokes is reviewed first. This compilation of early data shows the importance of the shape factor, D/d, i.e. ratio of wheel-to-tyre diameter.Two bicycle wheels having different shape factors are tested. Splitter plates of 2d and 4d length are fitted. Some reduction of drag coefficient is found only for 2d splitter plate. The small effectiveness of splitter plates is attributed to weak vortex shedding from the wheel. The full length splitter plate acting as a disc increases the side-force eleven times in comparison with that of the bare wheel.Similar tests are carried out on a bicycle frame fitted with splitter plates. The drag reduction is found to be marginal. Again it may be argued that vortex shedding from all members of the frame is weak.
The aerodynamic efficiency is an important design criterion for bicycle helmets. The characteristics of venting geometry,
venting orientation and venting location play a vital role in aerodynamic drag. In order to design an aerodynamically efficient
bicycle helmets, a comprehensive study is required. Therefore, the primary objectives of this work were to study the aerodynamic
efficiency as a function of venting geometry, venting location and orientation for a series of recreational production helmets
currently available in Australian market.
In time trial cycling stage, aerodynamic properties of cyclists are one of the main factors that determine performances. Such
aerodynamic properties are strongly dependent on the cyclist ability to get into the most suitable posture to have minimal
projected frontal area facing the air. The accurate knowledge of the projected frontal area (A) is thus of interest to understand the performance better. This study aims for the first time at a model estimating accurately
A as a function of anthropometric properties, postural variations of the cyclist and the helmet characteristics. From experiments
carried out in a wind tunnel test-section, drag force measurements, 3D motion analysis and frontal view of the cyclists are
performed. Computerized planimetry measurements of A are then matched with factors related to the cyclist posture and the helmet inclination and length. Data show that A can be fully represented by a rate of the cyclist body height, his body mass, inclination and length of his helmet. All the
above-mentioned factors are thus taken into account in the present modelling and the prediction accuracy is then determined
by comparisons between planimetry measurements and A values estimated using the model.
KeywordsAerodynamic-Drag coefficient-Performance-Planimetry measurement
In cycling time trials, competitors aim to ride a course in the fastest possible time and the implementation of a pacing strategy is therefore essential. In this study, a differential equation model of a cyclist incorporating continuous changes in velocity is formulated and applied to a selection of theoretical courses and athletes. The model is augmented with a constraint corresponding to a mean work rate and various pacing strategies are considered. The inclusion of continuous accelerations experienced by the cyclist forms an essential component in a model for courses comprising many changes of gradient, and a steady-state approximation, which has previously been used to assess pacing strategies, is not suitable. In addition to formulating a result on the mathematically optimal solution of the model equations subject to the mean power constraint, it is also shown that substantial time savings can be realized by cyclists increasing their work rates on uphill sections and suitably reducing their work rates elsewhere. However, the amount of time saved is highly course- and athlete-dependent with the greatest gains arising on courses with the longest continuous ascents by cyclists of greatest mass.
The critical power (CP) is mathematically defined as the power-asymptote of the hyperbolic relationship between power output and time-to-exhaustion. Physiologically, the CP represents the boundary between the steady-state and nonsteady state exercise intensity domains and therefore may provide a more meaningful index of performance than other well-known landmarks of aerobic fitness such as the lactate threshold and the maximal O2 uptake. Despite the potential importance to sports performance, the CP is often misinterpreted as a purely mathematical construct which lacks physiological meaning and only in recent years has this concept begun to emerge as valid and useful technique for monitoring endurance fitness. This commentary defines the basic principles of the CP concept, outlines its importance to high-intensity exercise performance, and provides an overview of the current methods available for its assessment. Interventions including training, pacing and prior exercise can be used to alter the parameters of the power-time relationship. A future challenge lies in optimizing such interventions in order to positively affect the parameters of the power-time relationship and thereby enhance sports performance in specific events.
It has been reported that performance in cycling time-trials is enhanced when power is varied in response to gradient although such a mechanical pacing strategy has never been confirmed experimentally in the field. The aim of this study was, therefore, to assess the efficacy of mechanical pacing by comparing a constant power strategy of 255 W with a variable power strategy that averaged to 255 W over an undulating time-trial course. 20 experienced cyclists completed 4 trials over a 4 km course with 2 trials at an average constant power of 253 W and 2 trials where power was varied in response to gradient and averaged 260 W. Time normalised to 255 W was 411±31.1 s for the constant power output trials and 399±29.5 s for the variable power output trials. The variable power output strategy therefore reduced completion time by 12±8 s (2.9%) which was significant ( P<0.001). Participants experienced difficulty in applying a constant power strategy over an undulating course which acted to reduce their time gain. It is concluded that a variable power strategy can improve cycling performance in a field time-trial where the gradient is not constant.
To develop a protocol for isolating changes in aerodynamic and rolling resistances from field-based measures of power and velocity during level bicycling.
We assessed the effect of body position (hands on brake hoods vs drops) and tire pressure changes (414 vs 828 kPa) on aerodynamic and rolling resistances by measuring the power (Pext)-versus-speed (V) relationship using commercially available bicycle-mounted power meters. Measurements were obtained using standard road bicycles in calm wind (<1.0 m·s) conditions at constant velocities (acceleration <0.5 m·s) on a flat 200-m section of a smooth asphalt road. For each experimental condition, experienced road cyclists rode in 50-W increments from 100 to 300 W for women (n=2) or 100 to 400 W for men (n=6). Aerodynamic resistance per velocity squared (k) was calculated as the slope of a linear plot of tractive resistance (RT=power/velocity) versus velocity squared. Rolling resistance (Rr) was calculated as the intercept of this relationship.
Aerodynamic resistance per velocity squared (k) was significantly greater (P<0.05) while riding on the brake hoods compared with the drops (mean ± SD: 0.175 ± 0.025 vs 0.155 ± 0.03 N·V). Rolling resistance was significantly greater at 60 psi compared with 120 psi (5.575 ± 0.695 vs 4.215 ± 0.815 N).
These results demonstrate that commercially available power meters are sensitive enough to independently detect the changes in aerodynamic and rolling resistances associated with modest changes in body position and substantial changes in tire pressure.
Three different cyclist positions were evaluated with Computational Fluid Dynamics (CFD) and wind-tunnel experiments were used to provide reliable data to evaluate the accuracy of the CFD simulations. Specific features of this study are: (1) both steady Reynolds-averaged Navier-Stokes (RANS) and unsteady flow modelling, with more advanced turbulence modelling techniques (Large-Eddy Simulation - LES), were evaluated; (2) the boundary layer on the cyclist's surface was resolved entirely with low-Reynolds number modelling, instead of modelling it with wall functions; (3) apart from drag measurements, also surface pressure measurements on the cyclist's body were performed in the wind-tunnel experiment, which provided the basis for a more detailed evaluation of the predicted flow field by CFD. The results show that the simulated and measured drag areas differed about 11% (RANS) and 7% (LES), which is considered to be a close agreement in CFD studies. A fair agreement with wind-tunnel data was obtained for the predicted surface pressures, especially with LES. Despite the higher accuracy of LES, its much higher computational cost could make RANS more attractive for practical use in some situations. CFD is found to be a valuable tool to evaluate the drag of different cyclist positions and to investigate the influence of small adjustments in the cyclist's position. A strong advantage of CFD is that detailed flow field information is obtained, which cannot easily be obtained from wind-tunnel tests. This detailed information allows more insight in the causes of the drag force and provides better guidance for position improvements.
To assess the effect of technology on sport, the performance statistics for four disciplines were analysed: the 100-m sprint, pole vault, javelin, and cycling. The concept of a performance improvement index was developed to allow comparison between athletes and between sports with a higher index indicating a greater improvement in the sport. The following performance improvement indices were found: 100-m sprint, 24% over 108 years; pole vault, 86% over 94 years; javelin, 95% over 76 years; 4-km individual pursuit, 35% over 32 years; one-hour cycling record, 221% over 111 years. Around 4% of the index for the sprint was attributed to tighter, aerodynamic clothing, suggesting that general athletic improvement in sprint-type events has been around 20%. Technological developments in simple equipment such as the pole vault or javelin were seen to affect the index by around 30%, while the index associated with aerodynamic improvements in the one-hour record was around 100%. It is concluded that the performance improvement index could be extended to amateur as well as elite sport where distance or time is used as a measure of performance.
The effect of varying power, while holding mean power constant, would have on cycling performance in hilly or windy conditions was analyzed. Performance for a 70-kg cyclist on a 10-km time trial with alternating 1-km segments of uphill and downhill was modeled, with mean VO2 (3, 4, 5 L.min-1), variation in VO2 (5, 10, 15%), and grade (0, 5, 10, 15%) used as independent variables. For the conditions of 4 L.min-1, 10% variation, and 10% grade, results were as follows: finishing time of 22:47.2 with varied power, versus 24:20.3 at constant power, for a time savings of 1 min 33.1 s. Separately, a 40-km time trial with alternating 5-km segments of headwind and tailwind (0, 8, 16, 24 km.h-1) was modeled, with the following results for the conditions of 4 L.min-1, 10% variation, and wind speed of 16 km.h-1: finishing time of 60:21.2 with power variation vs 60:50.2 at constant power, for a time savings of 29 s. Time saved was directly proportional to variation in VO2, grade, and wind speed and was indirectly proportional to mean VO2. In conclusion, the model predicts that significantly time savings could be realized on hilly and windy courses by slightly increasing power on uphill or headwind segments while compensating with reduced power on downhill or tailwind segments.
The aims of this study were to examine the effects of one self-selected and two enforced pacing strategies (constant and variable power output) on cycling performance during a time trial in which variable wind conditions were simulated. Seven male cyclists rode their own bicycles on a Computrainer cycle ergometer, which was programmed to simulate a 16.1 km time trial on a flat course with a 8.05 km h(-1) headwind in the first half of the race and a 8.05 km h(-1) tailwind in the second half of the race. Subjects rode an initial time trial (ITT) at a self-selected pace to the best of their ability. The mean power output from this trial was then used to calculate the pacing strategies in the subsequent two trials: Constant (C)--riders rode the whole time trial at this mean power output; and Variable (V)--riders rode the first headwind section at a power output 5% higher than the mean and then reduced the power output in the last 8.05 km so that the mean power output was the same as in the initial time trial and in trial C. Power output, heart rate and ratings of perceived exertion (RPE) were recorded every 1.61 km. Finish times, 8.05 km split times and blood lactate levels, pre- and post-exercise (to calculate delta lactate), were also recorded in each trial. In the ITT, riders chose a mean +/- SD power output of 267 +/- 56 W in the first 1.61 km which was 14% higher than the overall race mean +/- SD of 235 +/- 41 W. Power outputs then dropped to below the race mean after the first few kilometres. Mean +/- SD finish times in the C and V time trials were 1661 +/- 130 and 1659 +/- 135 s, respectively. These were significantly faster than the 1671 +/- 131 s recorded in the initial time trial (p = 0.009), even though overall mean power outputs were similar (234 - 235 W) between all trials (p = 0.26). Overall mean RPE and delta lactate were lowest in trial V (p < 0.05). Perceived exertion showed a pacing strategy by race split interaction (p < 0.0001), but it was not increased significantly during the first 8.05 km of the V condition when power outputs were 5% higher than in condition C. Heart rate showed no main effect of pacing strategy (p = 0.80) and the interaction between strategy and race split did not reach statistical significance (p = 0.07). These results suggest that in a 16.1 km time trial with equal 8.05 km headwind and tailwind sections, riders habitually set off too fast in the first few kilometres and will benefit (10 s improvement) from a constant pacing strategy and, to a slightly greater degree (12 s improvement), from a variable (5% +/- mean) pacing strategy in line with the variations in wind direction during the race. Riders should choose a constant power when external conditions are constant, but when there are hilly or variable wind sections in the race, a variable power strategy should be planned. This strategy would be best monitored with 'power-measuring devices' rather than heart rate or subjective feelings as the sensitivity of these variables to small but meaningful changes in power during a race is low.
Cycling performance is dependent on physiological factors which influence mechanical power production and mechanical and environmental factors that affect power demand. The purpose of this review was to summarize these factors and to rank them in order of importance. We used a model by Martin et al. to express all performance changes as changes in 40 km time trial performance. We modelled the performance of riders with different ability ranging from novice to elite cyclists. Training is a first and most obvious way to improve power production and was predicted to have the potential to improve 40 km time trial performance by 1 to 10% (1 to 7 minutes). The model also predicts that altitude training per se can cause a further improvement of 23 to 34 seconds. Carbohydrate-electrolyte drinks may decrease 40 km time by 32 to 42 seconds. Relatively low doses of caffeine may improve 40 km time trial performance by 55 to 84 seconds. Another way of improving time trial performance is by reducing the power demand of riding at a certain velocity. Riding with hands on the brake hoods would improve aerodynamics and increase performance time by approximately 5 to 7 minutes and riding with hands on the handlebar drops would increase performance time by 2 to 3 minutes compared with a baseline position (elbows on time trail handle bars). Conversely, riding with a carefully optimised position could decrease performance time by 2 to 2.5 minutes. An aerodynamic frame saved the modelled riders 1:17 to 1:44 min:sec. Furthermore, compared with a conventional wheel set, an aerodynamic wheel set may improve time trial performance time by 60 to 82 seconds. From the analysis in this article it becomes clear that novice cyclists can benefit more from the suggested alterations in position, equipment, nutrition and training compared with elite cyclists. Training seems to be the most important factor, but sometimes large improvements can be made by relatively small changes in body position. More expensive options of performance improvement include altitude training and modifications of equipment (light and aerodynamic bicycle and wheels). Depending on the availability of time and financial resources cyclists have to make decisions about how to achieve their performance improvements. The data presented here may provide a guideline to help make such decisions.
The primary purpose of this study was to evaluate the scaling relationship between body mass (mb) and projected frontal area (AP) of competitive male cyclists whilst allowing statistically for the influence of bicycle geometry. A group of 21 cyclists [mean mb 74.4 (SD 7.2) kg, mean height 1.82 (SD 0.06) m, mean age 23.6 (SD 5.1) years] volunteered to have AP determined from photographs at three trunk angles (TA: 5 degrees, 15 degrees, 25 degrees) for each of three seat-tube angles (STA: 70 degrees, 75 degrees, 80 degrees) using a modified cycle ergometer. Using multiple log-linear regression analysis procedures, the following equation was developed: Body AP (meters squared) = 0.00433 x (STA0.172) x (TA0.0965) x (mb0.762) (r2 = 0.73, SEE = 0.017 m2) (n = 183 images total). This equation indicates that after allowing for the independent influence of STA and TA on AP, AP was proportional to mb raised to the +0.762 power (i.e. Ap is directly proportional to 0.762). The 95% confidence interval for this exponent (0.670-0.854) barely included the theoretical two-thirds value but not the +0.55 value for AP or the +0.32 value for submaximal metabolic power (Ws) of outdoor cycling reported in the literature. Further analysis of wind tunnel data reported in the literature suggests that the coefficient of drag (CD) is proportional to mb raised to the -0.45 power. When combined with the present study findings, it is suggested that the drag area (CD x AP), which should be proportional to Ws at submaximal cycling velocities, is proportional to mb to the +0.312 power (i.e. CD x AP is directly proportional to mb-0.45) x (mb+0.762) = mb+0.312), which is consistent with the +0.32 exponent for Ws in the literature.
Wind speed, wind yaw and the aerodynamic drag acting on a bicycle and rider
- O Isvan