Using Data Acquisition Part 2 - RPM Analysis

In last issue's Art & Science we discussed the basics of data acquisition and different ways to interpret speed data. Speed-whether recorded by a GPS-based system or a unit that measures wheel speed-is generally the base channel and offers plenty of information on its own. Adding more channels, however, allows a more in-depth analysis of the motorcycle's and rider's behavior on the track. That higher level of analysis can in turn result in quicker development and improved overall performance from both the bike and rider.

Most data acquisition systems offer a dedicated rpm channel, which records engine revs a set number of times every second. Just as with the speed channel, the rpm data can be plotted against distance from a beacon or start/finish line, showing engine speed at any point on the track. An rpm trace reveals plenty with just a quick glance: maximum rpm used on each straight, minimum rpm in each corner and where the rider is upshifting and downshifting. This information can be used to make a gearing change-whether it is a swap in sprockets to alter the final drive ratio or an internal ratio change-and optimize engine rpm over the course of a lap. As well, improvement may be found as easily as by pointing out to the rider that rpm is low or high in a certain corner and he could benefit by using a different gear.

Now that we are dealing with two channels-speed and rpm-the data can be further manipulated using math channels to yield even more information. Most systems' software allows the user to create an additional channel that is based on a mathematical function working on one or more existing channels. For example, knowing engine rpm and wheel speed, it's possible to use a math channel to find what gear the bike is in at any given time and display the gear position graphically or numerically. Some analysis software packages such as AiM Sports' Race Studio 2 include a gear-position channel that makes assumptions for internal and final gearing, meaning there's no need to input each gear ratio or sprocket size.

We'll come back to math channels in future installments, but for now consider some more possibilities: Wheelspin can be displayed in graphical form by subtracting front-wheel speed from rear-wheel speed, or acceleration and braking forces can be calculated from speed. As more channels are added, math channels can combine and manipulate two (or even more) channels to more easily show a certain characteristic.

Another useful tool for evaluating rpm data is the histogram. Instead of graphing rpm (or any channel, for that matter) over time, a histogram plots data as the percentage of time that it occurs within a specified category or range. For example, an rpm histogram could show that rpm is between 10,000 and 11,000 rpm for 10 percent of the lap; between 11,000 and 12,000 rpm for 15 percent of the lap; between 12,000 and 13,000 rpm for 12 percent of the lap; and so on. This can indicate at a glance how the rider is managing rpm. If the engine makes most of its power between 10,000 and 11,000 rpm, for example, and the rider is not maximizing that band as shown on the histogram, an overall gearing change may be prudent.

The case studies presented in the accompanying screen captures show more detail about rpm traces and histograms. In our next installment we'll discuss adding and evaluating even more channels.