Tires are a critical data...
Tires are a critical data point, as age, number of heat cycles, air pressure (both cold and hot), tire temperature, rubber hardness, and spring rate are all important tire data that needs to be collected and managed.
Racers tend to take a very narrow view of the data they collect. The number-one data point collected on a regular basis is the lap time. The problem is that the lap time is a dependent measurement. We need to measure the things that are driving the lap times. Some other feature or adjustment drives the variation in the lap times. Tires, springs, shocks, and/or gear ratios all have an impact on lap times. If we discover the most important adjustment on the car that affects the lap times, then we can most likely predict lap times.
The data you record on race days may be as simple as the time of every lap at speed. Unfortunately, this data alone is not that valuable. Unless the data sets are accompanied by copious notes that define the tuning action you were making for the times recorded, the data is almost meaningless. The notes are your linkage to understanding how your changes to the car affect the lap times.
For example, let's compare the lap times from two different race days on the same track (a half-mile dirt oval). The lap times were dropping every time the car went onto the track. The majority of the speed can be attributed to the track drying out and becoming faster. The last 20 laps were the main event, and the lap times were the fastest of each day. But something else was happening on the laps that were faster, although there was still a good bit of variation. Was the track changing? Was the driver getting more breaks on the track? Was the car performing better? Did the grip on the track change? Did you install new tires on the car for the main? The multiplicity of different causes for the speed should be documented in your notes. What did you do differently from one week to the next? The answer is in the notes.
If we view the raw data as just a stream of numbers, [See Graph 1, page 66] we can see there were some differences between the two number streams. The view in a graphical form lets us see where the differences were. The first pass is shown to help us visualize the differences between the two race days. The rates at which the car picked up speed are different. In one set of data the car got much faster in the last five laps. In the other set the car also got faster on the last five laps, but the amount of change was much less.
The next step involves taking a close look at only the main event data. [See Graph 2]
What can we learn? It depends! It depends on the notes you had taken that went along with the lap times. It might be something as simple as getting out front with a clear track or old tires that take longer to heat up. Without the notes to go along with the data, it will be very difficult to really pinpoint the factors that were driving the delta (change) in performance.
We also need to look closely at notes from a test day. You may be working with camber on your car. Let's say you change the camber and then go to the track to test the change. The lap time is used to measure the success or failure of the adjustment. You may test three different camber settings, "A," "B," and "C," to develop the best setting for your car on a particular track. The test may be as simple as a two-lap confirmation run followed by another change. In reality, you should probably run a larger lap count to lend a bit more credence to the test and develop a greater level of significance to the change. But sometimes we have to do what we can given the value and scarcity of track time. The data may look like this:
Setting | Lap 1 | Lap 2 |
A | 21.073 | 21.071 |
B | 21.065 | 21.077 |
C | 21.066 | 21.072 |
The data set in this form may not tell you what you want to know. We may select the "C" setting because it yielded the fastest lap. But did it answer the question we were asking? It sometimes makes sense to look at the data from a more visual perspective than to just look at the numbers.
When the data is viewed in a graphical form, [See Graph 3] we can clearly see that setting "A" has the least variation or range in the data. In settings "B" and "C," the first lap was faster, but then the car slowed significantly. This may be a good data point if we are interested in qualifying, but for a longer session setting "A" may be better. This data set is telling us that something else is going on and we may need to test further. The differences are more readily observable in a graphical form than in a textual form. The data did not change; it just was a bit easier to see the differences between the individual camber settings.
The missing components to this data set are the physical conditions on the day this test was accomplished, which include the following: the track, date, type of day, who was driving, and the other settings for the other adjustments on the car. These data points are critical information. Once again, we need to keep copious notes in an effort to document each change and fully understand the whole of the test.
When we take notes, we need to be as specific and as detailed as possible. Just recording lap times is a start, but it is not enough. You can be sure that your competition is taking notes and documenting activity. Professional racers keep very detailed notes and measure everything they can. They know that the difference between winning and participating is a well-documented racing process. Keeping good notes and documenting the process is often the difference between guessing and making data-based decisions.