The Bike Position Optimization Quest

For the past 11 years working with Jana Richtrova, we have approached each year as an opportunity to optimize what, at the time, has been her bike position and equipment.

Along the way, my bike fitting & aerodynamics knowledge has evolved as I've learned more about mechanics and bike-fit protocols. Also learning new approaches & new technologies to "estimate" the drag coefficient.

In the early days, we used a picture of a rider, a known-size object, and Photoshop software to determine the rider's area to estimate the frontal projected area.

Later, we started doing more field testing using a power meter, speedometer, a known course, and tools like Golden Cheetah Aerolab. And a 3D capture device plus Computational Fluid Dynamics software to analyze a position to estimate the drag coefficient for different setups.

Early days CdA estimates

Five years ago, I opened the FreeSpeed Lab in The Woodlands, TX, offering metabolic testing, gait analysis, bike-fitting & aero testing. For the latter, I added the Velogicfit 3D aero simulator to determine the rider's frontal area during a fitting session and estimate the drag coefficient. And early this year, I got the necessary equipment and gained access to a velodrome to incorporate velodrome aero testing.

Regarding bike fitting, I've incorporated different tools like motion sensors placed on the rider, 3D capture to measure body movement, angles, rotation, etc., and a full functional assessment pre-fit to determine a rider's mobility & stability limitations (among other tools).

Bike positions over the last 11 years

For 2023, having access to various tools, our goal was simple: How could we optimize Jana's position in terms of 4 points:

1. Sustainable - a position she could sustain for 112 miles while producing target race power.

2. Efficient - a position that yielded a lower energy expenditure 

3. Aerodynamics - a position with the lowest CdA possible *without* compromising points 1 & 2. 

4. After achieving all the above points, the final piece was to optimize gear selection around it to reduce CdA further

The first step was to measure energy expenditure, heart rate & muscle oxygenation at a set power for four different positions :

• Position A - Lowest Stack/Mid reach - This was the position she rode for the 2022 Ironman World Championship

• Position B - Highest Stack/Short Reach - This was the position she rode for the 2023 Challenge Roth

• Position C - Highest Stack/Long Short Reach

• Position D - Mid Stack/Longest reach 

For simplicity purposes, I'm referring to stack as the height difference between the saddle and aero cups/armrest (point #4 on the image below) and reach as the distance between the front of the nose and the edge of the cup/armrest (point # 3 image below).

To determine energy expenditure, we did two intervals of 5 minutes each at a specific power, measuring watts, heart rate, volume of oxygen, and SmO2%. The order for each position test completed was A, B, C, D, D, C, B, A, with a rest between each 5-minute interval to change the position. I took the last 60-second average for each interval.

As you can see from the results above, positions B and D yielded the lowest energy expenditure & heart rate at the same power. Subjectively, Jana graded each position in terms of comfort and ability to generate power. While all positions felt sustainable, position D felt the most comfortable and natural to sustain, while power generation felt easier to produce. In contrast, position C was the least comfortable and felt power was more challenging to produce

In the following weeks, we headed to the velodrome to test the three positions we felt were best: A, B, and D. On these sessions, we used the same gear/equipment for all runs (same wheels, tires, PSI, helmet, outfit, shoes) and only changed the stack/reach for each position. We did a total of 12 runs, testing each position three times in the following order: A, A, B, B, B, D, D, A, A, B, B, D, D.

As you can see from the results, Position D came on top, producing the lowest drag coefficient. This result was pretty lucky and very exciting because this position also yielded a low energy cost, and it was the position that felt most comfortable/powerful for her.

With all that data, we achieved our first three points from our original goal and settled on Position D to be the one to optimize gear around. So, we returned to the velodrome one last time to optimize gear choices. We used her basic race setup for this session, including Zipp Wheelset 454/858 hookless, Continental 5000 TR 28mm, 60 psi, and Surpass Insane LTD suit.

We did various runs testing, bottle positions, aero socks, aero calf sleeves, bottle tucked-in jersey, etc. We didn't try other helmets as she only has the Giro Aerohead, which we used, but we expected she would wear another helmet as part of the sponsorship commitment for the Zwift Tri Team. (In the end, she rode the Giro.) 

Velodrome Aero Testing

With the final configuration, we could optimize her drag coefficient further. We achieved consistent runs in the mid 0.21s, averaging a 0.216 CdA, offering an extra 5 watts savings or around 10 min savings compared to her Kona 2022 setup. We knew for race day, she would use Continental 5000 TT TR for racing tires, which have a slightly lower rolling resistance, gaining a bit more free speed. Later, we did field testing to validate the results and consistently got a CdA in the 0.215 - 0.22 range occasionally.

Once we arrived in Kona, she did her race simulation, riding the entire bike course at target race watts, and on that day, her final split was already quicker than back in 2022 despite riding 1 mile longer, traffic & refueling stops. I then ran a BestBikeSplit model using the simulation weather conditions, power, etc. and estimated a 0.221 CdA.

In the end, Jana rode her highest power at 3.5 w/kg & fastest split in Kona. Her 4:40:40h split yielded a 0.22 CdA on BestBikeSplit once adjusted for the day weather conditions, Crr, and final power. It resulted in the fastest amateur bike split, 11th in the pro field, and a new amateur course record.

I'm looking forward to further developing this approach and offering a practical version to the public. This process was a fantastic learning experience.