A classic scenario for time trial pacing strategies is to consider how to ride a race course that has a headwind for the first half followed by an equal tailwind for the second half of the course. This is a useful scenario to analyze to become better at pacing cycling time trials because it often occurs for out and back race courses. By using Optimal Cycling, we can systematically analyze the difference between riding such scenarios using a steady pacing strategy compared to the optimized strategy that the program solves for.

In this analysis, we are going to consider a flat 40 km TT course that has a headwind for the first 20 km followed by an equal tailwind for the last 20 km. We are going to solve for the optimal power pacing strategy using a critical power of 250, 300, and 350 watts to see how different power output levels affect the time savings obtained. We are going to look at scenarios with wind speeds of 0, 3, 5, and 8 m/s (0, 10.8, 18, and 28.8 km/h respectively).

Plot #1 - Race Course for the Pacing Optimization

The flat 40 km race course will be modeled with 428 points. Other notable parameters from the optimization model include:

• Rider Mass: 70 kg
• Bike Mass + Other Equipment: 8.5 kg
• Power Metric: CCAP
• Air Density: 1.18 kg/m^3
• CdA: 0.28 m^2
• Coefficient of Rolling Resistance: 0.004

Note that you can download the all the simulations done for this discussion here: Simulation Files for 40 km Flat TT with Headwind & Tailwind. You will need Optimal Cycling v0.9.1 or greater is required to run the simulation files. Depending on the speed of your computer, it can take several hours to run through all the simulation files.

The summary of the time savings that can be obtained using an optimized pacing strategy versus a start & steady strategy is shown below:

Table #1 - Summary of Time Savings Using an Optimized Pacing Strategy

For the output of 250 watts, the “Start & Steady” strategies are shown below. This strategy consists of quickly going up to race power and holding it steady for the entire course. Plots 3-5 show how the racer travels much more slowly in the first half of the course compared to the second half.

Plot #2 - 250 Watts, 0 m/s Wind, Start & Steady

Plot #3 - 250 Watts, 3 m/s Wind, Start & Steady

Plot #4 - 250 Watts, 5 m/s Wind, Start & Steady

Plot #5 - 250 Watts, 8 m/s Wind, Start & Steady

Below are plots of the optimized power pacing strategies for the output of 250 watts, plotted by course position. In Plots 7-9, we see the optimized power pacing strategies generated by Optimal Cycling. The strategy can be described as going harder into the headwind and ease up in the tailwind.

Plot #6 - 250 Watts, 0 m/s Wind, Optimized Pacing

Plot #7 - 250 Watts, 3 m/s Wind, Optimized Pacing

Plot #8 - 250 Watts, 5 m/s Wind, Optimized Pacing

Plot #9 - 250 Watts, 8 m/s Wind, Optimized Pacing

Now, the same plots for the optimized power pacing strategies but plotted by time. In Plots 11-13, we can see that the portion of time spent fighting the headwind in the first half of the course becomes increasingly greater as the wind speed goes up.

Plot #10 - 250 Watts, 0 m/s Wind, Optimized Pacing, Plotted By Time

Plot #11 - 250 Watts, 3 m/s Wind, Optimized Pacing, Plotted By Time

Plot #12 - 250 Watts, 5 m/s Wind, Optimized Pacing, Plotted By Time

Plot #13 - 250 Watts, 8 m/s Wind, Optimized Pacing, Plotted By Time

What can we learn from these plots and the summary table? The most important thing to note is that it is important to vary your power on a course that has a headwind and tailwind portion. From Table #1, we see that varying power becomes important at headwind/tailwind speeds of 3 m/s and above (10.8 km/h).

The exact numbers vary for riders with differing power outputs but the overall idea to push harder as the headwind increases remains the same. In Table #1, we see that there is less time savings for riders that push high power outputs. This is caused by the fact that a rider with a higher power output will cover the course in less time and thus the time savings will be proportionately smaller. However, Table #1 shows that the time savings are still significant if an optimized pacing strategy is used over a steady power approach.

For an overall power output of 250 watts, a rider that varies his power can save 10 seconds over a rider that just rides steady on a course with 3 m/s wind. A savings of 10 seconds could easily mean the difference between several finishing positions. In Plot #7, we see that Optimal Cycling suggests a power output of about 268 watts going into the 3 m/s headwind and a power output of 225 watts coming back with the 3 m/s tailwind.

Varying power becomes increasingly more important as the wind speed goes up as shown by a possible time savings of 60 seconds for an overall power output of 250 watts when there is an 8 m/s wind (28.8 km/h). In Plot #9, we can see the optimized power pacing strategy for this specific scenario and Optimal Cycling suggests a power output of 278 watts going into the 8 m/s headwind and a power output of just 172 watts coming back with the 8 m/s tailwind. This shows that on courses with high winds, the race is largely decided by how hard you race going into the headwind. The ride back with the tailwind should be a relatively relaxing affair since you have a tailwind pushing you that allows you to sustain a high speed without much effort.

To view the optimized power output plots for a cyclist at 300 watts and at 350 watts, visit http://optimalcycling.com/2011/05/30/additional-plots-pacing-strategy-headwind/.

I hope you have enjoyed this article and increased your knowledge of effective pacing strategies.