Your Rebound is Too Slow

Before we start, this is the second article in a likely series about suspension data as collected with the Motion Instruments data acquisition system. See here for the first article, and here for a detailed read on how it works, what we’re measuring and how Motion Instruments suggest that we tune things.

Okay. That’s a little bit of clickbait. I don’t actually know that your rebound is too slow. You might have this all figured out already. I thought I had it all figured out! A few times. Then I looked at the data again. And then I looked at different data. And then I wasn’t so sure. One thing I have concluded though, there’s a lot more to this rebound damping thing than we’ve been told by manufacturers! It’s almost like there’s no one setup for everybody and everything. I mean, who knew, right?

Packing

You’re a waist high whippersnapper. The training wheels just came off. You’ve got a piece of grass stickin’ out your mouth and you’re whittlin’ a stick. You’re getting ready to jam that stick in the end of a hotdog, and then you’re going to cook it over a fire. Granddad is sitting there beside you, driftin’ in and out of sleep. Is he snoring? How does he do that? Then he springs to life! “Boy! Did I ever tell you about packin’?” You get pretty excited! Is this the talk? It starts off pretty well. “There’s a man and a woman and they’re driving down a road together.” I’m listening, granddad! “And then you hit some bumps! Washboard they call it. And you hit the first bump, and that’s okay. But the second bump…well! Your suspension doesn’t have the oomph to get ‘er back up to full extension! And with each bump, the suspension is gettin’ lower, and lower, and lower. Pretty soon, you’re just bangin’ metal on metal, like a hippie hittin’ a tin a’ beans against the door of a train as he clicky clacks down the rails to nowhere!” Granddad is obsessed with hippies, for some reason.

This is how we learn about packing. We’re told some legend about driving on washboard. It’s a horrendous thing that happens to morons! That doesn’t happen to us! We’ve never ridden across a row of braking bumps and come out the backside with our suspension fork bouncin’ off the stops! Of course our suspension isn’t packing! And if our suspension isn’t packing, well, our rebound can’t be too slow then, can it?

This is the problem with extreme examples. Sometimes, when we simplify things to gain an understanding, we squash the nuance out of it. I think how we explain rebound damping has lead to many of us running too much rebound damping. Myself included.

The Packing Continuum

What I’ve come to learn is that packing isn’t a binary on/off thing. It’s not either happening or not happening. It’s more of a continuum.

To understand what that means, we have to talk a bit about a sort of idealized shock stroke. Imagine you’re cruising into a bump, perfectly weighted, so you’re at your target sag front and back. You hit that bump, your suspension compresses until it hits equilibrium between the force from the bump and the force from your spring. It then pauses for a teensy little moment, and then your spring starts pushing back, extending your suspension. What you’d like to have happen at this point is for your suspension to extend back to your sag point as quickly as possible without overshooting too far, or oscillating too much. So, when we talk about rebound damping, all we’re really talking about is how quickly and controlled your fork is settling back to equilibrium (i.e. sag point), and ready for the next bump.

The thing is, there’s always going to be a bump that comes at you more quickly than your suspension will be ready for! If the trail is really smooth and the bumps are spaced far apart, your suspension doesn’t have to react very quickly in order to be ready of that next bump. As the time between bumps decreases, your suspension has to react faster and faster to be ready. Take that out to its conclusion, and what that says is that at some point all suspension will pack, in that there is a theoretical series of bumps that come too quickly for it to recover in time. All suspension will eventually be dealing with multiple hits that cause it to compress from a point deeper than sag. This starts to get into some “could god microwave a burrito that would get so hot that even he would burn his mouth?” type of weed philosophy. But the faster you go, and the bumpier things get, the quicker your suspension needs to recover to be ready for the next bump.

And that’s an important adjustment that I needed to make when it came to my rebound damping. I moved from a mentality of “not so slow that it is packing” to one of “fast enough to recover quickly for the next bump”. Leaving the extreme examples behind allowed me to accept that I may never be able to fully avoid packing, but the faster I run my rebound, the less likely it is to happen. For all those doubters, how fast do you think Richie Rude is running his rebound here?

Taking Things to the Real World

Now that we’ve decried using extreme examples to prove a point, let’s use an extreme example to prove a point! I was sitting at the bottom of Seymour one day, waiting for a ride partner to show up. I had all of my data acquisition gear installed on the bike and I was just about to take it off. I looked over, saw a nice little staircase, and wondered if I could use it to demonstrate some things with my suspension. I took a few runs at the staircase, starting with everything quite open, gradually closing off my rebound damping with each successive run. This proved to be a really great way to demonstrate differences in rebound damping.

Before we get to that, we need to talk a little bit about what we’re looking at. While the Motion Instruments app is very useful, and can point you in the right direction very quickly, it doesn’t show you the details of how your suspension is moving. I wanted to get right in there and see if I was able to visualize packing, so I had to take things a little bit further. I spent a bunch of time playing around in excel, trying to match the results that I was getting from the Motion Instruments app. Once I had that, I pushed everything into PowerBI so that I could play around with it more easily. This allowed me to plot my suspension position vs. time and then filter in to look at specific sections of trail. Once that was working, I started to compare sections of trail side-by-side that had been ridden with different settings, and to calculate various attributes (i.e. max suspension speeds, travel, dynamic sag, etc.) for those sections.

Each graph:

• Represents the percentage of travel. So, that’s the percentage of 150mm of travel in the rear, and the percentage of 160mm travel for the Fox 36 and 170mm of travel for the Formula Selva.
• Holds time as a constant, comparing the same number of samples, not the same distance travelled on the trail. I did this so it would make suspension speeds more obvious. A steeper line equals a faster speed. The challenge though, is that the distance isn’t fixed so each comparison isn’t over the exact same section of trail. Close, but not exact.
• I’ve included calculations for max travel, dynamic sag and max compression and rebound (shown as a negative) velocities
• The first set of graphs we will analyze is composed of 600 sample points (which is just under 3 seconds of activity). I’m traveling at ~13 km/hour, so the graph covers a distance of roughly 11 meters

The top graph (Fast Rebound) represents the settings I was running that day (7 clicks from closed up front, 11 clicks from closed in the rear). The bottom graph (Slow Rebound) has closed things off a lot (1 click from closed up front, 5 clicks from closed in the rear). Showing these two runs side by side gives us a good read on the data.

The other really beautiful thing about this data set is it gives us the response under a few different conditions. First, we enter the graph from the left with our suspension settling after hitting a small curb. Then, we get a bunch of quick repetitive hits in the form of the stairs, followed by a big bottom out hit. After that, we have one large hump as I load up the bike, followed by a full unweighting as the wheels come off the ground after the curb, and then, finally, a second bump that signifies the impact from landing after the curb. This gives us a view on a lot of different responses, over a very short window.

We can clearly see the impacts of running faster rebound when we compare the stair sections of each run. On the first run, the fork is recovering quickly, and so is hovering around sag as we roll down the stairs. For the final compression at the bottom, the fork has very nearly recovered to sag point (the impact starts at 19% travel) and then maxes out at 57%.

When we jump to the slow rebound example, we can see a much slower recovery and some pretty significant impacts as a result. Clearly, the fork doesn’t have enough time to recover from each stair hit and by the time we get to the bottom of the stairs, we’re much deeper into travel, such that the bottom compression starts with the fork at 31% of travel, and we end up using a whopping 73% of travel. This looks like a pretty great example of packing to me!

Beyond the fork just riding lower and lower, there are some secondary impacts. We see much more force of the impacts flowing through the front of the bike, and less on the rear, suggesting a substantial shifting of weight forward. For the fast rebound example we’ve actually used 68% of rear travel, while with slower rebound we’ve only used 61%. This isn’t that great of a difference in terms of percentage points, but remember that the rear is also rebounding slower as well! It should be slowly burrowing packing down, just like the fork, but the fairly substantial shift in weight negates this from happening.

There is also some insight to be gained by looking at the two large humps in the data that follow the stairs. First, it’s almost impressive how identical the preload input is that I put into the bike before rolling off the curb. This makes it really easy to compare the response as the bike unweights coming off the curb.

We can go a lot deeper here, as well, and parse the data points to calculate velocities and response times. Up front, the 6 clicks difference in rebound damping the slow and fast examples have more or less halved the rebound velocities, doubled the response times and doubled the distance the bike covers before the suspension recovers when the bike is unweighted. With fast rebound, the fork quickly tops out, and with slow rebound the fork meanders towards top out and barely gets there before impact. Weighted, the difference in response is less with much smaller differences in average speed. However, we should keep in mind that with slower rebound the fork compresses much deeper in travel and therefore there’s more force trying to extend the fork. The damper is slowing things down more than just the speeds indicate.

The rear is showing less of an impact from the changes in settings. Average rebound speeds are closer no matter the settings, but clearly faster on the fast rebound example. With the bike unweighted, the bike is responding over the same time (as it should be as this represents the time/distance from curb to landing and in neither case does the suspension fully topping out), but it doesn’t move as far.

Now let’s see what this looks like on the trail.

On the Trail

You would have a hard time understanding how much time I have spent looking at suspension graphs over the last few months. First, it takes a bit of time to pick out the same spot on different graphs. You have to pick through a lot of graphs and match up a lot of points to do so.

Then, you quickly learn that it can be a whole lot of noise that doesn’t tell you much.

And that was my big struggle here. The Motion Instruments app was telling me that my rebound speeds were too low, but when I zoomed in on the data I was having a hard time seeing anything other than really subtle differences. Worse, riding a slightly different line or weighting the bike a little bit different would cause more response in the data than the suspension settings!

But I eventually figured it out after looking at piles and piles of comparables. Below, we’re going to focus in on one. We’ll start a little bit zoomed out before honing in on a pretty small range of data to demonstrate how this all plays out in the real world.

We’re going to look at a section of John Deer, taken on two different days. We’re going to gradually zoom in with three sets of graphs. The first is 4.9 seconds of trail (1000 samples) starting at approximately 1:12 from the top of John Deer. The next set of graphs is 2.5 seconds of trail (500 samples). The final look is 1 second of trail (200 samples). Settings/components over those two runs are as follows below:

The first graph teaches us a few things.

• Run #1 – Fox 36 – I’m running 1 more click of both LSR and HSR than is recommended by Fox. On top outs where the wheel is fully un-weighted, there’s a clear 2-stage rebound where the fork is quick to rebound until around the 5% mark, where is slows considerably before hitting top out. This looks similar to what the fork was doing on our slow rebound stairs example. I’m going to speculate that this is an interaction between slow and high speed rebound settings, where we move from oil flowing through shims to oil flowing through the low speed circuit.
• Run #2 – Formula Selva – Settings here are close to what we ran on our fast stair sample, and the response looks similar. Formula doesn’t provide recommended damper settings that I could find, so this was winging it based on max rebound speed from the Motion Instruments app. Max speeds are in the ballpark of what is suggested, but the histogram (not shown) shows a bit of a spike in the 0-5% travel bracket, suggesting maybe it’s riding too high in travel? But this could also be suggesting too much spring pressure. I will be experimenting with less air pressure and more compression damping in the future
• The data coming off the rear is much more consistent from run to run than coming off the front. This feels obvious as they’re the same shock with only slightly different settings. Certain sections look very close to identical. Max speed is actually faster on Run #1, despite the rebound being 2 clicks slower. I think that at this point on the shock, there is no discernible difference in rebound from 8 clicks and further out. The rebound adjustment on this shock is just a rod closing off an orifice, so while it does have an impact on high speed rebound, it seems to have more impact on slow.

Our mid zoom example doesn’t really give me much more insight over the first. We do start to see a few more differences between the two data samples, but I’d have a hard time drawing any conclusions here. Certain things are just too similar, while others are too different.

Where things get really interesting is when we zoom even further in, and focus on 200 sample points. This close in, our response starts to look pretty similar to our stair example. On Run #1, we see the fork looks like it is slowly wiggling down into itself, without much rebound response between bumps. On Run #2, we start and end at the same place, but the suspension is responding faster, recovering closer to sag, and starting each successive bump higher in travel. The fork has more travel at its disposal and it’s moving more with each impact, with the front and the rear of the bike tracking one another better. Looking specifically at the rear though, the difference in the response between Run #1 and Run #2 are much smaller, with subtler differences compared to the fork.

With all of that information, I would consider a few changes to my settings. I would for sure continue opening up the rebound on the Fox 36, and probably experiment with separate adjustments to LSR and HSR. The rear shock is looking like it needs a lighter rebound tune, or perhaps even a different shock, with more response to setting changes. On the Formula fork, I think I’ve hit my limit for what I’m comfortable with rebound speed and I might even try one click more (slower) rebound. Overall, I’m governed by the coil spring that I have for this bike, which is forcing me into a spring forward tuning philosophy in the rear, which I’m balancing out on the front. I’d like to experiment on both ends of the bike with less spring and more compression damping, but that’s neither here nor there in our discussion about rebound.

What Does this All Mean?

Before we get to that, I wanted to share a couple of outside resources that I found that helped me to clarify my thoughts on rebound damping. These two visuals were handy for demonstrating a theory, but they’re also imaginary things made up by humans, so grain of salt and all that.

The first is this website called Shim Restackor. The pitch here is that a bit of under-damping is a good thing. Anything less than critical damping is going to cause your suspension to oscillate (i.e. overshoot sag) but we can handle a bit of this and, more importantly, this allows your suspension to respond faster, and therefore ride higher in its travel.

The graph above explains this, by showing the difference a system that is near critical damped (green/zeta = 0.9), underdamped (red/zeta = 0.7) and severely under-damped (blue/zeta = 0.5). The severely under-damped fork is going to overshoot sag by a fair amount and then oscillate around your sag point. This will not feel all that controlled. The near critical damped fork is not going to oscillate around sag to any noticeable degree, but it’s slow to get there! The under-damped fork is going to overshoot sag by a bit, but it’s allowing the fork to both return and settle fairly quickly. Using the “seat bounce test”, they suggest you can achieve this by bouncing on your suspension and setting your rebound to allow for a single oscillation of a few mm before settling. Is this correct? Perfect? I’m not sure, but it explains why a faster rebounding fork feels like it is riding higher in its travel.

The other really great resource that I found is the Race Tech Suspension Bible. This deals with motorcycles, but there’s some fascinating stuff in here. There’s a diagram on page 32 that explains the conflicting things you feel when you’re adjusting your rebound damping.

What this is suggesting is that there’s a window that is generally acceptable for rebound damping. On one end of that spectrum, we dial in more rebound to create a feeling of control. That’s suspension that moves a bit slower and feels a bit less lively, more settled. On the other, we have lighter rebound that improves traction (but don’t go too light). So that’s suspension that is reacting to bumps more quickly, putting the wheel back on the ground faster, and creating traction by having your wheels touching the ground. But this also can feel less controlled, more active and a bit more bouncy. If left to my/our own devices, we (probably) gravitate towards the controlled end of that spectrum as it feels more natural, but when you see the data, you start to see the benefits of the faster end of the spectrum.

What Does this Mean for You?

“That’s great Dave. We’re happy that you have figured out that your rebound was too slow. What can we do with this information?”

This is a fair question. It doesn’t seem like you’re going to be able to buy your own Motion Instruments system any time soon, but I think there are some things you can take away from the work that I’ve put in here. I mean…I’m just some schmo with access to a data acquisition system, so you’re probably getting what you pay for with this advice. If you’re serious about this, there are experts that you can consult with that will be happy to help you tune your suspension to your individual needs.

But let’s get back to the opening premise of this article. Opening up your rebound is really noticeable, especially in the rear, and especially while climbing. The whole traction/control spectrum really comes into focus when your rear is bobbing more than you’re used to on a climb. It’s unsettling, quite frankly! The adjustments on the Marzocchi shock seem to have a much larger impact on slow speed rebound than on high, and I think I could stomach higher maximum rebound speeds if it the impact on pedaling wasn't so great, and it would be great to see if I could find a world where my max rebound settings were faster while my low speed rebound felt more controlled.

The bad feelings went away as soon as I turned my bike downhill. Honestly, I never felt anything bad coming down the trail with lighter rebound settings. My suspension felt softer (as it was riding higher in travel) and quicker to respond to hits (well…ya). Up front, it was all good, as I never felt any detriment while pedaling.

This was all in line with what Motion Instruments told me would happen. They suggested some target speeds and I wasn’t hitting them! I opened up my rebound damping and my rebound speeds got faster! And it felt better!

The thing is, would I have been able to get here without a fancy data acquisition system? With rebound settings, I actually think so! I think I knew that my rebound was probably a bit too slow, and I certainly wasn’t surprised when the system told me to speed up my rebound damping. I think the Shim Restackor “seat bounce test” is on to something. If you bounce on your suspension and it doesn’t oscillate around sag at all, your rebound damping is likely too slow. It’s going to feel safe and controlled, but it’s likely compromising your suspension performance. If it’s oscillating well past sag, it’s likely too fast, but that’s going to be a harder thing to gauge. Even a bit more oscillation is going to feel pretty weird when you’re pedalling your bike. You can tune this out a bit with more low speed compression, or just flick the climb switch if you're lucky enough to have been issued one.

I may have to write about this a bit more in the future, but what I’ve been unable to do is balance my rebound speeds front to rear. The thing is, I think this is okay! The rear of my bike is a bit slower getting back to sag, but this sort of defaults into a position of safety (slacker angles, higher hands) so I’m not convinced it’s all bad. You also don’t have to think too hard to imagine the downsides of the rear of your bike rebounding quicker than the front. But, as mentioned above, I wouldn't mind experimenting with this a bit more if I could better control pedaling performance.

Of all the tweaks I’ve made over the last several months, faster rebound created the most noticeable change. I’m not sure if that corresponds with “helped the most with performance,” but most of you are going to be able to feel a few clicks difference in rebound, and the data shows that faster rebound speeds will allow your suspension to ride higher in its travel and will allow it to react more quickly to bumps. So, play around a bit. Pick a 15 second section of trail that you know well, is pretty bumpy and that you can ride consistently. Do a seat bounce test. Do a run. Hike back up. Open up your rebound a click or two. Bounce on it again. Do another run. Hike back up again. Try something else. This might feel a bit weird at first, but if you’re adhering closely to your suspension manufacturers recommended settings I’ll bet that you have some space to speed up your rebound damping. I’ve certainly seen the benefits of getting a bit more aggressive with my rebound speeds and I think you can too.