I remember reading a recent article comparing 200 treadwear tires and one of the initial concerns was setting tire pressure. Shockingly, they found that varying tire pressures had little affect on lap time. Whoa there! I did not spend good money on a needle pyrometer for no reason! Did I? Did I?
Clearly this is something YSAR needs to investigate. In theory, raising tire pressures does several things.
- Decreases rolling resistance
- Decreases grip
- Improves steering feel
I can imagine that these forces offset each other to some degree. Straight speed vs. corner speed: it’s 6 of one, half-dozen of the other. It makes some sense that tire pressures might not change lap time by much. But making sense isn’t the goal here. I’m a scientist by profession and passion, so I just have to conduct some experiments. Since I don’t have immediate plans for a semi-private test day, I’m testing this in simulation first. Later in the year I hope to revisit this study on a real track. Let’s begin with the usual sim testing environment: Assetto Corsa, Brands Hatch Indy, NA Miata.
Experiment #1: Ideal tire pressure
In order to remove any human sources of variability, I’m going to let the AI drive first. Assetto Corsa sets the Miata pressures at 28 psi by default and allows a range from 15-40. I chose to change pressures in 4 psi increments. As you can see in the table below, 28 psi seems optimal. Interestingly, all laps are within 0.25 seconds using pressures from 24-40. If I had seen these numbers in real life, I would probably conclude that all lap times were roughly equivalent. But the AI drives each lap within hundredths of a second, so the differences are real, though small. Overall, I have to agree with the initial premise: tire pressures don’t affect lap time very much.
Experiment #2: Asymmetrical tire pressure
One of the things I like doing at the track is running non-square setups. I’ll mount completely different tires on the front and the rear. The two ends of a car are doing very different things, so there’s really no reason to run square setups. One of my favorite ways of goofing around on a skid pad is to mount sport tires on the front and all seasons on the rear. That’s a good way to train your oversteer recovery skills! Note that I said skid pad not HPDE session. I don’t think it’s a good idea to mess around too much in the presence of other drivers on a fast track.
So what happens when the AI drives a non-square setup? As it turns out, Assetto Corsa doesn’t allow you to have different compounds for the front and rear. But you can change individual tire pressures.
My first thought was to change the psi by 4 lbs on either side of 28. So 24F 32R and 32F 24R. The faster combination was to have more pressure in the rear. It wasn’t much of a difference, so I decided to go extreme and set one pair of tires to the ideal 28 psi and the other to 40. The result is sort of shocking. 28F 40R (64.04) is not only faster than 40F 28R (64.41), it’s also slightly faster than 28 square (64.09).
A stopwatch doesn’t give many details, so let’s load up the telemetry and take a closer look at what’s happening in Experiment #2. Green is 28-28 (because green is in the middle of the rainbow). Red is 28-40 (because oversteer feels red). Blue is 40-28 (because understeer feels blue).
For some reason, the AI chooses a different line on the square setup. The green line shows that the AI attempts to hold too much speed which results in being later to throttle. While initially faster, this ultimately causes the square setup to lose nearly 2 tenths by 1800 feet. It maintains that loss for a little while but then recovers most of it by the end. Apart from one bad decision in one corner, the square setup is actually faster everywhere else. This is why we don’t rely solely on the stopwatch.
What’s happening with the understeer and oversteer setups? The reason the oversteer is faster is that it’s able to use more mid-corner throttle, and it gets to full throttle sooner. It also has more yaw early and requires less steering effort in a few places. You have to zoom way in to see this. These are very subtle differences, but they add up to 4 tenths of a second by the end.
Experiment #3: Human driver
OK, time for me to drive. The first thing I did was run some square setups at a couple different pressures. There’s a little difference in the way they feel but not that much. I’d rather focus on what happens when you run different pressures in the front and rear.
|Front||Rear||Fast||Median||M – F||Cuts|
The fastest was the square setup. That’s not really surprising. What is surprising was that the understeer setup was very close. The median lap was only 0.09 seconds off. If you look at the difference between the median and fast laps (M – F) you can see that the understeer laps have the most consistent pace. That was my impression while driving too: “oh well, another uneventful lap”.
The big shock is how bad the oversteer setup was. Its fast lap was 0.55 seconds slower than understeer and the median is even worse: 0.90 (some of the laps were not pretty). I was having to make steering corrections in nearly every corner as the back stepped out under braking and also under throttle. I also had one lap where I went a little too much off course and got a cutting violation.
In the graph below, the panels are speed, steering angle, throttle, and time. I have plotted the top 5 laps of each run. As you can see from the red steering angle trace, the position and magnitude of the steering corrections are quite variable. This indicates that an oversteering car is hard to drive consistently (and possibly also that I suck at racing).
Let’s take a closer look at the fast laps to dissect how understeer and oversteer affect driving style. I’ve zoomed in on the first corner (a fast, descending right-hander) below. Again, the panels are speed, steering angle, and throttle from top to bottom. The area under the blue steering angle trace is relatively large. I’m having to crank the steering wheel quite a bit because the front of the car is sliding (understeer). On the green trace, there is very little steering because the rear is stepping out just a little. This is what Paul Gerrard calls zero steer. On the red trace, the back has stepped out so much (oversteer) that I have to make a steering correction in the opposite direction to prevent myself from spinning. Note that the green trace also has a steering correction (it’s bowed down in the middle), but it is very mild.
Looking at the throttle trace (bottom panel) you can see the disadvantage of the understeer setup: it’s late getting to full throttle. So in addition to the loss of speed from scrubbing the front tires, it has an additional opportunity cost in throttle time. The oversteer setup should get to full throttle first because it’s pointed straight first, but I’m fighting the wheel so much I don’t manage it. A better driver could make this work better than me.
Here’s the whole graph. Note that the understeer setup isn’t always the last to full throttle. Sometimes the initial application is delayed. But once applied, the throttle can be used as an on/off switch. You don’t really have to balance the back end when the back end isn’t sliding. In contrast, the oversteer setup requires a soft foot and live hands to keep it on track.
Tire pressures do matter
The AI was relatively unfazed by non-square changes in tire pressure, but I was not. Having a loss of grip specifically on one end of the car or the other completely changed how I drove. I can sum up the driving experience as follows:
- An understeering car
- feels boring
- requires a lot of steering effort
- requires trail-braking to rotate
- requires patience before throttle
- may see you running off track at the exit
- An oversteering car
- feels exciting
- practically turns itself
- requires steering corrections to prevent over-rotation
- requires throttle modulation
- may see you spinning at the entry, middle, or exit
- feels exciting
Why is the AI behavior (oversteer fast) so different from mine (understeer fast)? I’m not sure exactly what to take away from the AI driver. It’s several seconds slower than me and doesn’t even know how to trail-brake (data not shown). The AI sucks at racing. However, it is very good at controlling oversteer. Its steering corrections are always exactly the right amount. I don’t think we should read too much into the AI performance.
Although I set out to determine if tire pressures affected lap times, what I ended up focusing on was how tire pressures affected grip balance. Why? Because the handling of the car is what will ultimately dictate lap times. Too much oversteer not only results in a car that is difficult to control, it’s also slow. But what of too much understeer? It’s a little annoying but can be mitigated by trail-braking. Ultimately, it’s easier to deal with a little extra understeer than a little extra oversteer. For many inexperienced racers, the natural reaction to stuff going wrong is to lift off the throttle. If the car naturally understeers, the stuff is mostly understeer and lifting is the appropriate response. In an oversteering car, lifting is going to make matters worse.
All of the experiments here depended on the Assetto Corsa tire model. How accurate is that? No idea. I don’t think of these experiments as the end of anything, but rather the seeds for the real-world tests I’ll do later in the year. Stayed tuned (pun intended).