The mere mention of “data acquisition” at a dirt track will illicit a variety of responses by the racers. Many of them might think that developing a data acquisition (DA) system will cost multiple thousands of dollars. Nothing could be further from the truth. In fact, I would suggest that you could build a basic system that can help you improve your team’s performance for less than it costs to buy the team dinner at the track concession stand. Yes, you will spend some money, it’s not going to be free, but that doesn’t mean DA is out of the realm of the weekly racer.

In the least complex terms, DA is a method of gathering information or data. It can be a computer-based system or a system based in pencils, pens, paper, and some stopwatches. The real trick is to just start gathering the data. Once you have the data you can start to ask and answer questions about your performance as a racer. Just like any other endeavor there are some vocabulary we need to talk about prior to going any further. For our conversation we need to define data. Data comes in two basic forms:

Continuous Data
Continuous data is expressed as a number, it’s the number that your DA system is going to record and you’ll use this data or these numbers later as a basis for your analysis of your performance. A simple example would be lap times, spring rate of any given spring, crossweight, wedge, and so on. They are good examples of continuous data as they are expressed in numbers.

Attribute Data
Attribute data is just that, an attribute: good, bad, better, or best. We use words to describe an attribute. Attribute data isn’t what we should be using to tune our race cars alone, it’s a supporting role for continuous data. Taking notes about on-track performance that we express in words is attribute data, loose off, tight center, and so on. Those are attributes of what the car is doing on the track.

How It Was and Is
In the past, DA had to be done manually with a stopwatch, pen, and paper. But while many of us were hiding or content in the past, the future crept in and changed our world. These changes didn’t change the data, it was always there, and it just gave us more options to collect and analyze it. We now have the ability to ask many more questions of the same data set thanks to the advent of low-cost computers and software. This mountain of data allows teams to learn things about the car, its performance, and how changes they make effect both. We can not only discover if the car is simply faster after a given set of changes but where on the track this performance increase is occurring. We can use the answers a specific data set may give us to formulate more questions, to dig further into the performance envelope.

We can now look at g-forces through corners, down the straight, and under braking; we can look at suspension travel, driver input to various controls, brakes, steering, and shift points. As far as engine parameters, we can look at rpm, a variety of temperatures from oil, water, exhaust, and intake. We can even look at air pressures at a variety of body locations to verify wind tunnel data and get a better understanding of how pitch and yaw affect the car’s performance. How important this type of feature measurement is for the Saturday night racer may be a point of debate.

We can even look at the driver and monitor heartbeat and breathing; all it takes is money and an inquisitive mind. Granted, we weren’t able to track as many parameters using manual methods or look at as many dynamic variables. But the world has changed and we’re being offered a better way to gather the data we need to answer the questions we have about our race cars.

The reality is that many of these systems, while they offer mind boggling features and measurement opportunities, one has to ask the question: Does the local guy racing at the local track on Saturday nights need a high-buck DA system? In my mind the answer is yes. It would be very helpful, but I also think that it would be really cool to have an F40 Ferrari in my garage to run errands with on the weekends.