Bicinetica is a new website and smartphone application to track your cycling training. Whether or not you have a power meter, Bicinetica can help you train better. These are some of its features.

- Accurate power estimator
- Detect failures in power meters
- Measure leg strengh imbalance for left sided power meters
- Can I beat that Strava segment? Measure how parameters such as your weight, your equipement and your fitness affect your PR time on a segment
- Make any indoor bike trainer into a power meter
- Estimate air drag coefficient area CdA (Needs a power meter)

Furthermore, Bicinetica allows you to track your critical power (CP), training load,fatigue, and much more.

#### Accurate power estimator

If you are considering buying a power meter, why not try Bicinetica first? Our power estimator is based in an advanced physics model. On climbs, using a sound road bicycle, our model accuracy goes hand in hand with strain gauge power meters. And unlike those, gravity doesn’t need calibration! On flat terrain the air drag plays an important role, and we are working hard to provide 95% accuracy even for very windy rides.

Here is a comparison of the power given by a strain gauge power meter (a 4iiii precision) and our model.

#### Detect failures in power meters and leg imbalance

This is a real case of an early adopter of Bicinetica, Jose.

Last year Jose bought a pedal based power meter that requires a precise installation. After a few weeks he noticed that his power figures were kind of odd… After communicating with the manufacter, following their instructions and performing different tests to calibrate the unit, the problem still persisted.

To make sure of the problem he rides using his power meter on a local climb and uses Bicinetica’s analysis to detect the possible failure.

Bicinetica detects a short climb in the ride of about 1.3km, averaging a 5.5% grade.

Jose completed that climb in 4:36 minutes, averaging 341W according to his power meter. Bicinetica runs a simulation for that segment, being fed by the track’s power, and considering the given parameters for him and his bike. The simulation returns an expected 3:41 duration for the climb, much shorter than the real, showing that the power meter is overestimating power. It can also show a comparison of the real speed and the expected speed:

Bicinetica also calculates the overestimation of the power meter. A 25% of power reduction makes the simulation time to match with the real 4:36 minutes for the climb.

In this case, the power meter was clearly off and needed to be replaced, but Bicinetica can be used to detect subtle differences. For instance, it can be used by cyclists who use a single (left) sided power meter to measure their average Left/Right balance. On repeated tests, the cyclist gets an accurate approximation of their power balance, and some left power meter units, like the 4iiii precision, allow to introduce a factor for cyclists to compensate their leg strength imbalance.

#### Effect of parameters (Can I beat that Strava segment?)

Alberto went for a group ride last week. During one of the climbs he was dropped by the group. He didn’t want to go ‘full gas’, but he wonders if he could have follow up the group. The climb is about 2.2km long and there’s a gain altitude of 176 meters. Since the segment was registered on Strava he could compare his time (9 minutes 23 seconds) with the fastest guy of the group (8 minutes 6 seconds). During the climb Alberto averaged 254W, how much more power would have he needed to follow the first man?

Bicinetica, using Alberto’s parameters, determines first the estimated duration of the climb, performing a second by second simulation based on the data and the power readings, given by a power meter, for every point of the climb. It delivers a graph showing the speed by second and the expected duration of the climb: 9 minutes and 28 seconds, a difference of only 5 seconds compared with the real time.

Here we can see a comparison of the speed readings of the track and the simulation.

Alberto could estimate how much faster he would have climbed if he dropped a few kilograms, but at 65 kilograms, he’s more interested in just seeing how much power he would have needed. Bicinetica performs simulations by raising the power readings a certain percentage until it finds that a 19% higher would have been enough. The average power in that case is 302W.

Now the question translates to: Can Alberto sustain 302W for eight minutes? Since he has been using Bicinetica for his rides he can see his critical power (CP) chart. For eight minutes his best effort is 282W, so unfortunately for Alberto the answer is that he couldn’t possibly have followed the group.

This tool allows you to see the effect of using other tyres, using lighter equipment or losing weight or as in this case, the effect of performing better. And it is especially useful to check your potential for a particular Strava segment, even if you could be a KOM contender for it, with just a click.

#### Make any indoor bike trainer into a power meter

With Bicinetica you can make any indoor bike trainer into a power meter. You will only need a speed sensor and to calibrate your particular trainer once, using a bike provided with a power meter. In this example we used an old, but completely functional, Tacx trainer. The user only needs to save a short ride, registering power and speed data, doing a couple of 10-15 seconds sprints.

After that, Bicinetica automatically adapts the model to that particular trainer. The results are shown in the following graph:

Applying a 15 seconds rolling average we can reduce the noise and see how similar both graphs are:

Here there is a zoom in for the first part:

Unlike some smart trainers that provide a power estimation based only on a power curve, Bicinetica takes into account velocity changes. For example, while coasting on the trainer, Bicinetica’s model will show 0W, while other smart trainers will incorrectly show a power output based on the velocity that the trainer still carries. Also, for short sprints from about 5 to 15 seconds, the change in velocity accounts for about 15% to 30% of the total power output. Bicinetica shows the real power output, considering that acceleration.