At the third round of the Mopar Canadian Superbike Championship held at Atlantic Motorsport Park, I continued working with Jodi Christie and John Sharrard with data acquisition on their Accelerated Technologies Honda CBR1000RR. At the second round held at https://www.insidemotorcycles.com/component/k2/item/1299-trevitts-blog-data-from-autodrome-st-eustache.html“>Autodrome St-Eustache, we started using the AiM EVO4 system and spent a fair bit of time looking at the GPS data and sector times. At AMP, however, the focus ended up being on the Honda’s suspension and a chassis setup to suit the track’s unique (read: bumpy) character.
The CBR is equipped with an AiM suspension potentiometer on the front fork and another on the swingarm to measure front and rear wheel travel. The EVO4 system is capable of recording this data 500 times per second, giving a staggering 70,000 data points for the suspension alone for every lap of AMP.
There are numerous ways to collate this mountain of data and derive some useful information. The raw position data is useful for seeing if the suspension is bottoming or topping out excessively, and to see the attitude of the bike at any given time. We can see how much the fork dives under braking or squats on acceleration, for example, and how quickly those transitions are happening. The image above shows position data for the CBR’s fork and rear suspension over the course of a lap at AMP.
Because suspension action is so dependent on shaft velocity (as opposed to the speed of the motorcycle), we use a math channel to take the derivative of fork and shock position to find velocity. This data in turn is used to generate a histogram, which shows how much time the fork or shock spends at each speed. AiM’s Race Studio 2 analysis software has this feature built-in, making suspension velocity analysis an easier task than it would be otherwise.
Inset into the image above are histograms for the CBR’s suspension over a lap of AMP. The histogram charts have shaft velocity across the bottom axis, and show how much time the fork and shock spend at each velocity. At the far left are high negative velocities, which reflect high-speed rebound action. At the far right are high positive velocities, which reflect high-speed compression action. The center portion of the histogram shows low-speed velocities for compression and rebound. Note that the fork spends much more time in the low-speed region than high-speed, giving it the characteristic hill shape. Statistical analysis of the histograms can be used to help determine how the suspension is working and what changes to make.
After the round at St-Eustache, I spent quite a bit of time studying the suspension data and the derived histograms. Previously I didn’t have that much experience in this area; most of the knowledge I had came from theory and books related to car suspension and data acquisition. And Sharrard, as you may know, is a suspension expert – his company Accelerated Technologies is a suspension specialist shop – but is new to the data side. To put theory and practice together, I contacted Pete Snell (of Snell Technical Services), who tuned for me in my racing days and has plenty of experience with suspension and data from his time working with Steve Crevier. By the time practice began at AMP, I had a pretty good understanding of the suspension data and how to use it.
As it turned out, that time was wisely spent; from the very first lap of practice the suspension data was key and pretty much all we looked at for the entire weekend. Sharrard was making suspension changes right up until the race on Sunday, and the setup helped Jodi to edge Jordan Szoke at the finish for his first Superbike victory.
The next round of the series is at Canadian Tire Motorsport Park on August 10-11. I have definitely been learning as I go, but for this round I will be at the track with the team for the first time. I’ve been busy studying the AMP data since the race weekend, and am anxious to put this newfound knowledge to good use.
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