Using a math channel allows data to be manipulated into an easier-to-read form. It may be something as simple as inverting a channel (so that positive values are negative and negative values are positive) to make it more represent what we consider “more” or “less”. And it may be something incorporating several channels and a multitude of functions. It’s easy to get carried away and create multiple channels simply because they are available, but the downside is that you’ve got even more channels to clutter up a graph and your computer’s memory. For a math channel to be considered useful, it should display data in such a way that you can quickly and easily see an important characteristic. For example, we look at longitudinal acceleration in braking zones to see how hard the rider is braking, rather than trying to judge how steep the speed graph declines.
There are many ways to combine lateral and longitudinal acceleration channels to gather information. The most common view – one that shows an overall picture of both channels – is an X-Y plot. This graph displays at a glance several important characteristics that are very difficult to see using a standard graph format.
While the internal accelerometer of a data acquisition unit can record longitudinal acceleration accurately, the same cannot be said of lateral acceleration. Figure 1 shows the same lap information as the previous examples, with GPS speed and GPS lateral acceleration displayed. To this, lateral acceleration as recorded by the unit’s internal accelerometer has been added. This data remains close to zero for the entire lap, and is practically useless, especially when compared to the GPS-derived data. Why is this?
Just as longitudinal acceleration is recorded by an accelerometer inside the data unit as well as through the GPS signal, lateral acceleration is likewise represented by two channels. In this case, however, the internal accelerometer cannot cope with a motorcycle application and is rendered useless. A full explanation is detailed in the next section. As mentioned previously, this is why GPS-based systems are so valuable, and any reference here to lateral acceleration will by necessity mean the GPS channel and data.
Figure 1 shows a typical graph of speed and longitudinal acceleration for a middleweight machine at Willow Springs. The scale of the chart measures in units of g, with positive g corresponding to acceleration and negative g indicating braking. With GPS-based systems, you will have the option of displaying either acceleration as measured by an accelerometer inside the unit or based on the GPS signal. Different software packages name the two channels in a variety of ways, and it’s important to distinguish between the two; we will always deal with GPS acceleration if possible, as it’s a much more accurate data stream. Look for a channel called GPS longitudinal acceleration, GPS G or some combination of those terms.