A friend is currently testing intensively the CdaCrr app with the Weather Meter anemometer mounted on the bike. The air speed is now recorded every second, so the rider average CdA is more accurately computed.
On the smartphone screen, two figures now appear on the top left, with first the real CdA (wind is used in the model), and the apparent CdA (model with no wind). The two are of interest, with the first one you can see the influence of your position changes during the ride, even with unsteady wind. By the second value, we can learn how drafting is important during a group ride, or how tail or headwind affects quantitatively the air resistance measured by the apparent CdA figure.
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| 2 hours ride. Segments where CdA is averaged are indicated by the red marks. |
During his last ride (between 11am and 1pm), the nearest airport station has reported a wind speed of 14.8 km/h and an east direction (so between ~80 and 100 degrees from the north). Meteorological station are at a standard height of 10 meters, so wind speed should be translated to a value near the ground (there is a velocity profile created by shear) with the Hellman estimation. A rule of thumb is to divide the value by two (or even three, according to this post). So, we guess a wind speed near the ground of 5-8 km/h.
CdaCrr app has recorded the following data: axial wind speed (subtracted bike sensor speed from anemometer air speed) and direction of travel (given by the phone GPS):
We can notice the sinusoidal tendency of axial wind speed with direction. Indeed, the axial wind speed seen by the rider is given by:
AxialWindSpeed = WindSpeed * cos(BikeDirection-WindDirection)
By fitting the data with a sinusoidal function (red curve below), we find out the prevailing wind direction 84°, east as indicated by the weather station.
The fit also gives us the sinusoidal amplitude, WindSpeed in the previous formula, as 3.9 km/h with a wind in the previous graph between -10 and 10 km/h. Compared to the 5-8 km/h of the meteorological station, there is no surprise here.
The idea of using GPS data to check wind direction was read in this great article.
The idea of using GPS data to check wind direction was read in this great article.
