fbpx Skip to main content

Should you be able to “feel” clicker changes?

When we turn a clicker in, we stiffen the damping, and when we turn a clicker out, we soften the damping. This has an equal effect throughout all stroke speeds, right?

Yes, in an ideal world, there is usually a constant increase or decrease in force needed to move the suspension across the speed range that the suspension moves at.

Take a look at the example below. The blue dotted lines either side of the solid blue line show the force measured across varying speeds with the clickers closed (top dotted line) and clickers open (bottom dotted line). We can see from the graph that the change in the damping force across the speeds is pretty much the same, around 0.5kgf (except for at very low speeds where the force starts from 0).

(The image below is from a Thumper Talk post, but the graph appears to be from Shim Restackor.)

I believe most average riders think that by turning the clickers, they will be able to solve any of the issues they are having on the track, regardless of how fast the suspension is moving, because the clickers have the same impact all the way through the different speeds.

This isn’t true.

I often see it being said that riders should be able to “feel” everything that happens on track and relay that back to their suspension technician or team, but here’s the issue; the faster the suspension moves, the more difficult it is to feel the clicker changes.

The graph below uses the data from above, and shows the percent change in force as the suspension moves faster. This is represented by the gray line. At low speeds (less than 1m/s), the change is quite substantial at nearly 10% for speeds of 0.5m/s. Thereafter though, the percent change drops off quite quickly, and by the time it get’s to 3m/s, there is only a 3% change in force. What does this mean in terms of feeling?

I want you to imagine we fill a bucket with water, and it’s left out on a bench in front of you. In the bucket, there is a flat plate with a handle attached sticking straight up from the bucket. There is space left all around the plate, so that the water can flow past the edge of the plate and the walls of the bucket. Move the plate up and down with the handle, and you will get a feel for the force of the water acting against it. Now, replace the water with maple syrup. It’s a lot tougher to move right?

The viscosity of water is 0.01 poise, and the viscosity of maple syrup is around 0.05 poise, so it takes 400% more force to move the plate in the bucket with maple syrup. That’s why we can easily feel the difference.  If the water were 3% more viscous, it would be 0.0103 poise. How could we possibly feel that?

OK, so what, I can see a 10% difference there in the graph as well and surely that’s what the rider is feeling?

Let’s take a look at some real world data.

The graph above shows the percent time the forks spent at different compression speeds for two different riders. One rider had an average speed of 37km/h (blue line), and the other rider had an average speed of 50km/h (orange line). (No, they weren’t on a Yamaha and a KTM, that’s just a happy occurrence from Microsoft Excel’s colour choice 😅)

Ah ha! The peaks of the graphs line up!

What this means is that most of the time the suspension is moving at around 0.5m/s, which matches up quite nicely with the peak change in force from the clickers. This is probably no coincidence, as the decades spent developing suspension from orifice style damping to closed cartridge would have been driven mostly by rider feel, and thus, the biggest effect from clickers happens at the speed the suspension spends most of its time at. You might have also noticed that the faster riders suspension spends less time at the lower speeds, and more time at the higher speeds, meaning that faster riders will need to be more sensitive to feel the clicker changes.

That’s a delightful way to end our story then right? We can just cure all riders problems with clickers?

Eh…. no.

There are two things that we need to account for.

1. The suspension can still move at really high speeds up to 9m/s where the rider will find it incredibly difficult to feel the clicker changes. (We usually see this when landing from a jump, or hitting a really square edge hole) .

2. The damping force may just be way off, and you’ll never get to where you need to be with the clickers alone.

We’re on to the final stretch, bear with me!

Let’s take one last look at the first graph, and something we haven’t spoken about yet, the brown line. You might have noticed it is labeled as “baseline”, and the blue line is labelled as “setting”. What this means is that the technician has made a change to the shim stack layout of the valve in order to reduce the force from the original setting. E.g with the baseline at 5m/s, there was a force of 26.5kgf, but with the new setting the force is reduced to 23.7kgf, meaning the fork would feel softer.

With this configuration of clicker, you were never, ever, ever going to get that much of a change, so if the rider had an issue with a harsh feeling on square edge bumps, or bottoming of the fork, it was going to need a valve adjustment.

I have to caveat all of these articles with the fact that in the real world, things rarely behave in an ideal manner, and you will see differences in behaviour from clickers and valving configurations. Like maybe the clickers stop having an effect at higher speeds, or they have more of an effect at lower speeds, and all this can be seen through dyno testing.

Hopefully though, you will see how using the Motoklik system, and the AiSetup can benefit your riding. There is a lot to be had from the clickers (up to 10% performance improvement based on this example!), and the beauty of it is, that Motoklik will identify if your suspension can be improved even further by either running you out of clicks, or by showing that the overall characteristic is too soft or too hard, in which case you will need to call on your local friendly suspension technician.

I hope you enjoyed this read, and you will find all our articles on the News section of our website!

If you’d like to work with us and the Motoklik system, feel free to email [email protected]

Kind Regards,

Jens

Ahhhh the robots are coming! AI for Suspension Setup

When the Jacquard loom of 1801 was introduced to factories in France, it was met with public outcries of opposition where “People smashed the machines” and even “killed textile mill owners”.  While the measures the protestors went to were extreme, their thought process had some basis: “this bloody machine is putting me out of work!”. This loom, alongside the steam engine and carbon steel formed the building blocks of the industrial revolution and the world had access to more items at a lower cost than ever before.

In todays world with all of the advances we have in technology, we have more people working better jobs, and with better health, than ever before.  So, what should we do when a new technology comes along that challenges the status quo?

Artificial Intelligence (AI) is making us look at the Jacquard loom all over again. When the words “Chat GPT” first appeared in the news, there was a lot of speculation on how many people would lose their jobs as a result, and how terminator was now real and our civilisation is doomed to extinction when the robots take over. But, what is AI?

The best definition I have come across is from IBM’s, Jeff Crume. Jeff states that “AI is basically exceeding or matching the capabilities of a human”.  That’s it. No robot takeover, no subjugation of humans, just the ability of a machine or software to match the capability of a human.

A practical example of this is determining the price of a car. When we see a 4 door saloon (sedan) car with an Audi or Ford badge of a certain year, we can have a rough guess as to what the price of the car is. If we work as a car sales man, we can give an even more accurate guess, but if we were either of these people we would still have to do more research to come up with as accurate a price as possible. This becomes more and more difficult as you start to take more factors into account; is it petrol or diesel, what colour is it, how many miles are on the clock, what’s the service history, has it been crashed, how many previous owners are there, does it have a leather or cloth interior, aircon etc. etc. The human mind can find it very difficult to take all these factors into account. But not AI. With enough data, an AI model can be trained to give immediate, accurate answers no matter what car you ask it about. Don’t believe me, try to beat Microsoft Azures Automobile Price demonstration model.

So what does this mean for the the world of suspension setup?

We first need to specify how suspension is currently set-up. There are three options available:

1. “Feel” what’s happening and use your experience to make spring and damper adjustments.

2. Have an experienced suspension technician watch you, and combine it with your feel feedback to make adjustments.

3. Manually interpret suspension data, work with an experienced suspension technician, and combine it with your feel feedback to make adjustments.

These three options are similar to guessing the price of a car. Using your “feel” is guessing on your own, working with a technician is a sales man guessing, and using data is the sales man doing research. We’re limited on the number of factors we can take into account because the human mind is limited in how much data it can retain.

Before we go any further, don’t @me with comments like, “he said suspension technicians are just car sales men.” I am ABSOLUTELY NOT saying that. Suspension technicians and data analysts spend years of their life gaining experience and working with riders to build up unbelievable skills, in the same way a weaver could weave magnificent patterns before the loom.

When faced with the immense power of AI however, it’s difficult to see how a single mind, or a small group of human minds can compete, in the same way the weaver had to compete with the loom.

Motoklik’s AiSetup is built with the objective of recommending clicker adjustments, and highlighting if there is an issue with the springs or valving. It’s specifically designed to work with suspension that use shim stacks to control the flow of oil in the damper. It does this by using a database that we have built up with years of testing across numerous types of tracks, riders, makes and models of motorcycles and suspension, to make accurate predictions. Our database is like all of the car details that feed into the car pricing model explained earlier.

Does this threaten the job of the suspension technician?

Yes, and more importantly no.

Some suspension technicians pride themselves on track side support, and attend tracks every weekend. Others want to spend time with friends or family and don’t need the phone hopping all weekend with “Trevor” asking what way he should go with his clickers because his bike feels kicky on the way into the back left turn at xyz track.

Regardless of which type of suspension technician it is, the most benefit for riders comes from suspension service work, and required re-valves or kit suspension. This is the bread and butter of the suspension technician, and is complemented by Motoklik and AiSetup. Clicker recommendations can help riders on the weekends, and any issue with valving or springs can be corrected by technicians during the week. Add in Motoklik’s built in hour meter, and riders can know when it’s time for a suspension service (we estimate 20-25 hours on the forks, and 40-50 hours on the shock.)

Does AI still sound so scary? I hope not. Humans have always been advancing technology, from stone axes to quantum computers. As long as technology has improved, so too has the life quality of humans.

If you are interested in working with the Motoklik system, feel free to email [email protected] 🙂

Kind Regards,

Jens

Professionelle Datenanalyse- und Fahrwerks-Einstellung via App!

Motocross Suspension Data Logger for 85cc Motorcycles

Gestern noch unvorstellbar – heute für Jedermann in Echtzeit verfügbar! /// MADE IN IRELAND!

Motocross Suspension Data Logger for 85cc Motorcycles

Kaputte Strecke, dicke Arme, unkonstante Rundenzeiten, unvorhersehbare kleine Stürze, fragende Blicke. Hier ein Klick, da eine Drehung an der Federvorspannung und eine Stimme aus dem off die irgendetwas von „Highspeed“ faselt. Nach einer Stunde muss Dr. Google mit dem Standard-Setting behilflich sein weil irgend jemand „erstmal alles auf Standard“ kommentiert hatte.

Verzweifelte Anrufe beim „Fahrwerks-Guru“ des Vertrauens der zwar fasziniert deiner wirren Beschreibung des Problems lauscht aber per Ferndiagnose auch nur einige Standard-Vorschläge machen kann. Der „Kriegsrat“ aus Freunden und Familie tagt erneut und diskutiert, wild gestikulierend wie man es aus diversen MX-Videos kennt, wann und wo du schnell oder zu langsam warst. Welche Entscheidung deine Spurenwahl vermeintlich optimieren könnte und vor allem: Wie hat das Fahrwerk „gelegen“ und welchen Impakt hatte es auf die die vorherigen Diskussionspunkte! Dir brummt der Kopf, du hattest eine Frage und hast nun 5 Meinungen.

Du denkst an die bekannten MXGP-Fahrer. Ein Fahrwerks-Experte vor Ort, der kilometerlange Wanderungen um die Strecke unternimmt um die perfekte Fahrwerksabstimmung bereithalten zu können. Mechaniker, die Rundenzeiten und Fahrtechnik im Blick haben. Die Vergleiche hinsichtlich der Spurenwahl und Abschnittsgeschwindigkeiten der Vorrunden beobachten- und vergleichen um zusammen mit dem Trainer oder Teamchef die perfekte Empfehlung abgeben zu können.

Eine perfekte Umgebung um schnell Motorrad zu fahren die dir, als „ambitionierten Hobbyfahrer“ wie es heute so schön heißt, wohl nie zur Verfügung stehen wird. Mit dieser Annahme liegt man stand heute aber komplett falsch. Jens Köpke von Motoklik Suspension aus Kilkenny in Irland behauptet all das in ein paar kleinen Boxen für Jedermann bereitstellen zu können und MOTOCROSS-MAGAZIN DEUTSCHLAND meint„Er hat auch schon geliefert“!

AiSetup™ von Motoklik Suspension analysiert automatisch eure Fahrwerksdaten und vergleicht sie mit Hunderten von Stunden guter Setups, um euch auf jeder Strecke das beste Setup zu bieten. Wie genau funktioniert dieses System und was bietet es alles? – DAS erfährst Du in diesem Artikel. MOTOCROSS-MAGAZIN Technik!

Motoklik AiSetup Logo

Motoklik ist ein benutzerfreundliches, einfach zu montierendes, robustes Federungs- und Rundenzeitmesssystem für den Einsatz im Motocross-Sport.

Die vom Motoklik-Gerät aufgezeichneten Daten werden über Bluetooth auf die mobile Motoklik-App heruntergeladen. Die App verfügt über 6 Grundfunktionen:

• Lap-Timing-Analyse, berechnet aus den Satellitenpositionsdaten
• Aus Satellitenpositionsdaten berechnete Abschnitts-Timing-Analysen
• Daten zur Position von Gabel und Dämpfer
• Durchschlagserkennung, um festzustellen, wo auf der Strecke das Fahrwerk den größten Teil des verfügbaren Federweges nutzen muss
 Durchschlagsanalyse, um festzustellen, ob ein Problem mit der Gabel oder dem Dämpfer vorliegt und mit welcher Geschwindigkeit sich die Federung bewegt
 Live Durchhang-Messung mit welcher der Benutzer das Arbeiten von Gabel und Dämpfer in Echtzeit überprüfen kann

Motoklik umfasst außerdem ein cloudfähiges Online-Dashboard für die erweiterte Analyse von Fahrwerksdaten.

Motocross data logger app suspension bottoming analysis view
Motocross data logger app lap time view
Motocross data logger app live sage value readout

AiSetup™ empfiehlt dir nach der Analyse, wie viel Klicks für Druck- und Zugstufe sowie für High- und Lowspeed der Druckstufe des Dämpfers eingestellt werden sollten. Damit Ihr Euer Bike mit maximalem Vertrauen bewegen könnt!

GateDrop.com Tested: Motoklik – the ultimate suspension set-up tool!

Motoklik ist einfach zu bedienen, einfach zu montieren und robust. Es verfügt über eine zentrale Steuereinheit (CCU), die sich zwischen den Gabelbrücken hinter der Startnummerntafel befindet, eine Satellitenpositionsantenne am Lenker mit einer Start-/Stopp-Aufzeichnungstaste und einer LED-Farbanzeige sowie einem Messstab für die Gabel, welcher sich am linken Gabelholm befindet und eine Messeinheit für den Dämpfer, welche sich zwischen Rahmen und Hauptbremszylinder befindet. Alles lädt sich über die Stromversorgung des Motorrades selbst auf, sodass man sich keine Gedanken über einen Batteriewechsel oder einen Aufladevorgang machen muss.

Die Installation ist für jeden machbar!

Sobald die Sensoren eingeschaltet sind, kann alles auf dem Smartphone erledigt werden und man erhält bis zum letzten Klick Informationen, wie genau das Fahrwerk eingestellt werden sollte – von hartem Untergrund bis hin zu Sand. Die Sensoren am Bike verfolgen alle Werte über die Rundenzeiten und liefern so detaillierte Informationen wie die relative Geschwindigkeit basierend auf der Beschaffenheit der Strecke. Dabei werden Vergleichswerte zu vorherigen Runden ermittelt. Eine beeindruckende Innovation.

AiSetup ist eine intelligente Funktion, die deine Daten analysiert und dir sagt, wie viele Klicks für die Druck- und Zugstufe gedreht werden müssen und ob du den Low- bzw. Highspeed der Druckstufe am Dämpfer anpassen musst, damit du dein Bike stabil in einem schnellem Tempo fahren kannst. AiSetup benachrichtigt dich auch, wenn eine Abstimmung der Dämpfungskennlinie durch Neubelegung der Shims notwendig wird oder die Federn für dein Gewicht und deine Fähigkeiten zu weich oder zu hart sind, sodass du weißt, ob du zu dein Fahrwerk von deinem Fahrwerksspezialisten anpassen lassen musst.

Mit Motoklik kannst du außerdem die Durchhanganzeige in Echtzeit, die Durchschlagsanalyse, die Positions- und Geschwindigkeitsanalyse von Gabel und Dämpfer, die Abschnittsanalyse, die Durchschnittsgeschwindigkeit, die Rundenvariation, den Geschwindigkeits- vs. Streckenbeschaffenheits-Score und vieles mehr sehen.

Motoklik ist nicht nur ein Datenlogger oder Datenerfassungssystem. Es handelt sich um ein Fahrwerks-Setup- und Rundenzeit-System, das dir helfen kann, deine Fahrkünste und Leistung auf deinem Dirtbike zu verbessern. Es ist ein unverzichtbares Werkzeug für jeden Dirtbike-Fahrer, der das Beste aus seinem Fahrwerk herausholen möchte.

Motoklik Product Information Video

Du kannst verschiedene Motos und Strecken vergleichen, sehen, welche Linie schneller ist und ob deine Fahrwerkseinstellungen dich schneller machen. Du kannst deine Daten auch in das Online-Dashboard von Motoklik hochladen und mit deinem Fahrwerkstuner teilen.

Was befindet sich im Lieferumfang, was genau bekomme ich alles?

• Zentrale Motoklik-Steuereinheit. Diese Einheit wird verwendet, um die einzelnen Sensoren mit Strom zu versorgen und die gemessenen Daten der Sensoren aufzuzeichnen sowie die Daten über Bluetooth an die mobile App zu übertragen. Das Gerät enthält außerdem eine 1000-mAh-Lithiumbatterie mit 3,7 V.

• Satellitenpositionsantenne. Die Antenne wird zur Identifizierung und Fixierung von Satelliten verwendet, um die aktuelle Position in Breitengrad, Längengrad und Höhe zu berechnen und die Geschwindigkeit zu berechnen, mit der sich die Antenne bewegt. Das Gerät verfügt außerdem über eine durchsichtige Tastenkappe, die in Grün und Rot beleuchtet werden kann. Blinkendes Rot zeigt an, dass die Antenne versucht, eine Satellitenortung zu erhalten, blinkendes Grün zeigt an, dass der Satellit fixiert ist, und durchgehendes Grün zeigt an, dass Motoklik Daten aufzeichnet.

• Gabel-Messstab. Der Stab beherbergt eine Reihe von Sensoren, die die jew. Position der Gabel anhand der relativen Position eines Magneten bestimmen.

• Hinterradfederungssensor. Der hintere Sensor beherbergt eine Reihe von Sensoren, die die Position des Dämpfers anhand der relativen Position eines Magneten bestimmen.

• Vorderer Magnethalter. Der Halter enthält einen 15 mm x 5 mm großen Neodym-Scheibenmagneten und wird am Vorderradgabelschutz des Motorrads befestigt. Dieses Teil ersetzt den Klemmhalter für die vordere Bremsleitung.

• Hinterer Magnethalter. Der Halter umschließt einen 15 mm x 5 mm großen Neodym-Scheibenmagneten und wird an der Schwinge am Heck des Motorrads befestigt. Die Befestigung erfolgt durch Schrauben, mit denen die hintere Bremsleitungsführung in Position gehalten wird, und/oder durch Kabelbinder.

• Stromkabel. Die Kabelbaugruppe besteht aus drei Komponenten: dem Motoklik-Stecker, dem OBD-Stecker und der Sicherung.

• OBD-Anschluss. Dieser Stecker wird direkt an den Kabelbaum des Motorrads angeschlossen und dient dazu, eine 12-V-Stromversorgung vom Motorrad zu beziehen, die zur Stromversorgung des Motoklik verwendet wird. Die Stromversorgung vom Motorrad erfolgt über ein Relais, das nach einer bestimmten Zeit abschaltet, wenn der Motor nicht läuft, z. B. 30 Sekunden. Wenn die Stromversorgung entfernt wird, wird das Motoklik-Gerät 10 Minuten lang von der internen Batterie mit Strom versorgt und schaltet sich dann ebenfalls aus. Motoklik entlädt die Motorradbatterie nicht.

• Sicherung. Das Stromversorgungskabel enthält außerdem eine 1-A-Flachsicherung, um den Stromverbrauch unter 15 W zu halten.

Mehr Infos bekommt ihr unter www.motoklik.com
Folgt Motoklik Suspension auf INSTAGRAM
Folgt Motoklik Suspension auf FACEBOOK
Folgt Motoklik Suspension auf YOUTUBE
Motoklik Suspension Linktree: linktr.ee/motoklik
©Bildmaterial: @visual.mx.photography @j_112_kinsella and @162ey

Eine Story vom MOTOCORSS-MAGAZIN DEUTSCHLAND – Ihr habt Fragen oder möchtet uns etwas persönlich fragen? Schreibt uns eine Nachricht an [email protected] – Folgt uns auf unserem offiziellen WhatsApp Kanal HIER oder werdet Follower auf FACEBOOK oder INSTAGRAM

Why was suspension setup so difficult in SMX?

“The motocross section was very difficult on supercross suspension, with the braking bump getting bigger, it was tough to manage, I mean for me”. (Credit – How was your weekend, www.swapmotolive.com) Dylan Ferrandis didn’t mince his words after the first round of the Supermotocross playoff at ZMAX Dragway last September when it came to his setup. The new format threw the biggest curveball since the move to four strokes for suspension, because the tracks were actually a real hybrid.

I know what you’re thinking, these teams and riders are the best in the world, how can they not get it figured out? Why were they even using supercross suspension on motocross?

The technology in dirt bike suspension is probably often overlooked when compared with Moto GP, or Formula 1, but the truth is that the mechanism used inside a set of forks and shock to control damping is on par, or even a step above what we see used in the pinnacle of tarmac motorsports. This is because the speeds that the suspension move at are so varied compared to the smooth surface of the asphalt. Yes, when an F1 car hits the curbs, the suspension must move quickly, but this is maybe more of a blow off pressure release valve than the requirement for controlled movement like we see in the transitions of a supercross rhythm. And herein lies our answer to the woe’s of Ferrandis, as well as the other riders.

The following images show the lap outline of a Californian supercross track on the left, and Fox Raceway on the right. Underneath the track outlines is a plot of the front and rear suspension speed for one full lap, and underneath this is the suspension position for one full lap. What stands out?

You can see that the speed of the suspension in the corners in supercross is about half the speed of what you see in the corner sections of the motocross track. (The coloured rectangles on the track outline are sequenced with the coloured rectangles on the suspension speed data). This means that braking and accelerating bumps are much smaller in supercross. With smaller bumps, the riders and teams can run much stiffer suspension without losing comfort. Those are words in the world of dirt bikes that go together like peanut butter and jello; supercross suspension and stiff. Do you remember when Fabio Quarteraro tried to push down on Tomac’s Yamaha this year? Yep, supercross stuff is pretty stiff!

So, why do they need stiff suspension in supercross? The answer lies in the second graphs under the track outline, the suspension position data. At the top of the graph the suspension is fully compressed, and at the bottom it’s fully extended. You can see how even with the much stiffer settings, the suspension is still using the full stroke on a supercross track, especially the rear through the transitions in jumps (shown by the large purple rectangle). Imagine now trying to go through that section with the softer motocross settings, you wouldn’t have an ankle left!

Let’s take a look at the three SMX tracks which opened in ZMAX Dragway, Concord, North Carolina, moved on to Chicagoland Speedway in Joliet, Illinois, and finished up at the Los Angeles Memorial Coliseum in California. In the following images, each track outline has been marked out with purple to show the supercross sections, and green to show the motocross sections.

The opener at ZMAX Dragway was really tough. With nearly a 50/50 split between supercross and motocross sections. At this track, there was no choice but to run supercross settings, because it would have been too dangerous for the rider to ride through the supercross transitions without the hold up of the stiffer suspension. The challenge was to ride on the faster sections outside the stadium area where the braking and accelerating bumps were building up.

Chicagoland offered some more clarity, with the majority of the circuit being a more motocross style. Even the double jumps and over-under are manageable on motocross settings, but the riders would have to be sure to be precise with their track position, especially on landing, or else they could easily end up in a situation like Tomac found himself in back in May.

Finally, there was the LA Coliseum. This was easily the most “supercrossy” of the three venues, albeit a little bit toned down with the absence of whoops. Nevertheless, the riders were still challenged, especially in the sand section where we saw big crashes from Aaron Plessinger, Dean Wilson and most notably Chase Sexton. How much of the blame for these accidents can be laid at the feet of setup though is up for debate, as the malleable surface of sand can often throw a curveball.

What can be done in future to help the riders and teams navigate setup in these venues. If we take the example of Formula 1 again, each time they go to a new track, they are going in blind right? Well not really. Every time these teams go to a track, they gather as much data as they can, including suspension position and speed. Before ever rolling a lap around a new circuit, they can already model up how they think the car will perform in those conditions, and once they gather some on track data, they can fine tune the settings. Maybe the track is a little bumpier, or the corner speeds are slightly different to what they modelled. Well, the same can be done for motocross, supercross and supermotocross.

The current method of suspension testing and development on dirt bikes is heavily based on trial and error, and rider feedback. Rider feedback is always necessary as it is the requirement of the suspension to keep the rider as comfortable as possible, not to satisfy a math’s equation. The down side is that over 90% of riders can find it difficult to communicate what the bike is doing on the circuit. If teams had gathered suspension data from the supermotocross tracks this year, it may have been possible to identify areas for improvement in the design of the damping curve, or more position sensitive damping, as well as be able to better judge the settings needed for tracks in the future. It looks like SMX is here to stay, and so too will be the handling issues felt by Dylan Ferrandis and other’s this year.

If you would like to work with us, or the Motoklik system, please feel free to email me on [email protected]

Kind Regards,

Jens

How to decide which shim to adjust in a shim stack.

Shims, shims they’re good for your bike, the more you change them, the more the handling goes to…..

Introducing shims to dampen oil flow was an absolute triumph in suspension technology. There’s no doubt that the switch from squishy and harsh orifice damping to using these round little slices of glory improved performance massively, and brought in a whole new world of tuning options. Sounds like great news right?

Of course it is, but the new challenge of figuring out how to adjust the shim diameters, thickness’s and arrangements created the dark art of suspension tuning that we know of today.

As a quick recap, shims will bend out of the way of the oil flow, making a more linear or digressive damping curve. This gives the suspension good hold up over low speed impacts, but allows the suspension to move on high speed impacts. Compared with orifice damping which was just a hole drilled in a tube, so it offered little to no resistance under low speed, and increased damping exponentially at high speed, causing it to feel harsh.

The graph below is from the Racetech Suspension Bible  and shows how increasing the orifice diameter affects the damping curve on the left, and how using a shimstack compares with an orifice on the right.

I have to preface this article with the fact that I have never worked as a suspension technician. However, I do have a masters in engineering, but my time working as a car mechanic with my older brother taught me that the piece of paper they give you at the end of college isn’t much use when you’re wrestling a diesel four wheel drive gearbox onto a spigot shaft.

What I will try to do here then is marry together the literary research I have carried out over the years, with the practical knowledge I have garnered from hanging around suspension technicians.

The question we will try to answer today is, which part of the shim stack should I target to make a rider feel more comfortable?

There are probably technicians who could answer this question just from raw experience, and trial and error. By using an analytical approach though, we can reduce testing time, and document a lot of that information gathered through experience. Every technician has to retire some time, and it’s an awful pity to lose all that knowledge.

Let’s start with what we know already.

From our previous articles, we know the average speed of the suspension movement on different sections of the track, and that we can use dyno’s to measure the suspension damping force effectively for the speed’s we see on the circuit.

What we don’t know, is which part of the shim stack is affected by how much force. If we know the answer here, it becomes straightforward to know which part of the stack to adjust. So how can we calculate the stiffness of each part of a shim stack?

Fortunately, there are lots of very clever people in the world, and one website I came across www.shimrestackor.com, has developed a piece of software that you can input all the shim dimensions from your stack, and it will print out a stiffness graph. You do have to pay a license fee for the software, and for the purpose of this article, I cam across a formula on the site that I could use as a rough substitute to demonstrate my point. The following formula basically calculates the stiffness of each shim, and by adding all the stiffnesses together, you can see how stiff the stack is at each point.

Woah!! What the heck is that?

Don’t get too put off now, let’s just look at this in plain English.

There are a few different symbols in there that mean the following:

K Stack: How stiff the whole shim stack is.

n: The number of shims in the shim stack.

Ki: The stiffness of the i-th shim.

Ei: How stiff a material is.

ti: The thickness of the i-th shim.

vi: How much the shim will squish out when it’s squeezed together.

Ri: What the radius is for the curve of the shim when it’s being pushed out of the way by the oil.

So what we do is calculate out K for each shim, and then add each K value together.

There are many assumptions built in here, and this equation also doesn’t account for crossover shims, or other variations, but as I said, this is a rough estimate.

The shim values I am using are the standard settings from a WP XACT fork for the base valve and the mid valve. I just plug in the values from this sheet into the formula above, and it results in the following two graphs:

These graphs show the force created by each shim in the base valve and the mid valve using the formula. There were 27 compression shims in each stack, excluding the clamp shim. What’s strange to me is how the mid-valve maxes out at 600N, while the base valve goes up to 1200N.

And if you remember from our last article on dyno’s the above graph is from Kreft suspension, and shows the damping force in Newton’s created at speeds from 0m/s up to 4m/s. Our last piece of the puzzle is to know how fast the suspension is moving on the part of the track the rider doesn’t feel comfortable on. There are two ways we can do this, one is to take the average speed of the suspension in compression on that part of the track, or two is to view the actual speed in the Motoklik app.

As an example, if the rider is having an issue on corner entry, the data from the speed of motocross suspension article showed that the average speed on corner entry was 0.506m/s. Working this back through the Kreft graph shows that the average force is around 120N, and working this back again into the shim stack graphs shows that this is around shim 6 on the base valve, and shim 8 on the mid valve.

Looking at example two, using the Motoklik app, I have picked a corner entry on the track. If the rider was complaining saying that they feel a harsh hit, we can easily see this in the speed the suspension moves on the graph. Taking this a step further, and assume we don’t want to affect the other parts of the turn, we can isolate the hard hits to between 2m/s and 3.6m/s. Converting this into a force shows that we are between shims 13 and 17 on the base valve, and 22 to 27 on the mid valve.

This whole article is just looking at one particular circumstance, and all of the values and forces can change depending on the type of rider, type of track, and configuration of the shim stack.

I do think it’s clear to see that by taking an analytical approach, we can be much more targeted in the changes we make to shims, and by gathering data continuously, we can build a detailed picture of suspension performance.

If you want to work with the Motoklik system, you can email [email protected] with any questions you have.

Kind Regards,

Jens

P.S.

Thankfully Craig Dixon was on hand to point something out which I missed in the article, please read below to see what else to be aware of:

“This is both correct and incorrect, identifying the shim area is fine but shims do not act as individuals, nor is there an identifiable high speed or low speed area of a shim stack. changing any shim changes the forces across the entire velocity / damping range. For example if we are to make a change to a high velocity shim (#13 to pick a number) and make this part of the damping stiffer, the low speed area will also increase in damping in proportion to the change made, if only a high speed adjustment is needed then we must also change the low speed shim stack (softer) to keep this section at the original damping force.”

Are they worth it? Shock dynos in motocross.

In our last newsletter, I wrote about the average speeds of motocross suspension on a hardpack circuit. There were some surprising values in there, including max speeds of up to 7.1m/s on the forks, and 2.3m/s on the shock. This brings up the question then, is it worth it to use a shock dyno in motocross?

The reason being that most shock dynos on the market have a maximum speed of 2.5m/s to 3m/s, and many times suspension technicians will run their tests at 1m/s. That’s surely a problem, isn’t it? How can a technician be sure that what they change on the shim stack is having the desired effect on the track?

There are two things we need to find out:

Can a dyno be run at their maximum speed of 3m/s with motocross suspension?

And, how much time does the suspension spend above 3m/s on the track?

In the image above on the left are the specifications of the Andreani DB4 and DB4-Plus dynamometer’s, and on the right is a force vs speed graph for standard WP XACT fork suspension from the Kreft suspension website.

For the most part, the type of dynos you will find with a motocross suspension technician are Scotch-Yoke or Crank dyno’s, and you can read about the Pro’s and Con’s of each on Laba 7’s website.

What’s being shown in the Andreani graph is that with the DB4 dyno, the suspension can only produce a force of 2,000 Newtons at 2m/s.

On the Kreft moto graph, it shows the measured force of the fork vs the speed. The speed goes up to a max of 4m/s, and the force at that point is slightly less than 700N.

That all seems fine then, the fork can be ran at maximum speed on this dyno.

In the image above on the left are the specifications again of the Andreani DB4 and DB4-Plus dynamometer’s, and on the right is a force vs speed graph for a Showa shock on the TCD Racing website.

On the TCD Racing graph, it shows the measured force of the shock vs the speed for both compression and rebound. The upward trending lines are the compression values which are the focal point of this article. The max force measured is 7,500N with the standard shim settings, and only at a speed of 0.52m/s. With the shim stack adjustments made by TCD, this value is dropped to 4,500N

Even with the softer TCD settings, this means that by the time the DB4-Plus dyno gets to 0.7m/s or 0.8m/s, it could already be at its limit. Now, I’m not pointing a finger at the DB4-Plus, it could very well be the same issue with most dynos that are used, it is just that Andreani were open enough to provide this information on their website, and it’s all I have to work off.

What about the answer to our first questions, can dyno’s be ran at their maximum speed with motocross suspension?

For the forks, we can likely say yes. For the shock, it’s a maybe leaning towards a probably not. It really depends on the stiffness of the shim stack and valving setup in the shock.

But does that really matter if we compare it to real world data? Let’s have a go at answering our second question.

Throughout these articles, I have been using the same data set for each example. The data comes from a German hard pack track, with a young rider on a 2023 Husqvarna TC 250.

You will have seen the graph above before in our previous article on improving the accuracy of our predictions for suspension setup. It shows the speed of the forks throughout the entire session, which was around 3 laps long. We found out in our last article on average suspension speed that the suspension moves fastest on jump take off’s and particularly landings.

We can see a number of times where the suspension reaches speeds far higher than the max speed for most dyno’s of 3m/s, but how often does it move that fast really?

I have broken the data out for the front and rear and calculated what percent of time is spent above 3m/s for the forks and shock.

The total time the forks spend above 3m/s is 0.91%.

The total time the shock spends above 3m/s is 0.00%.

Yippee! This means that measuring the suspension at the max speed on the shock dyno doesn’t bring us an awful lot of value, and probably isn’t worth worrying about. Remember, on the rear shock, we extrapolated that the max speed would probably be around 0.8m/s.

However, from speaking with suspension technicians, I know that many of them run their dyno’s at 1m/s. So let’s carry out the same analysis again, and find out how much percent time the suspension spends above 1m/s.

The total time the forks spend above 1m/s is 12.76%.

The total time the shock spends above 1m/s is 1.45%.

13% is a pretty significant amount of time to ignore, but we also know now that the dyno should be able to run forks at max speed because the damping force is low enough.

What does all this mean then.

The bottom line is, the higher end dyno’s that are available on the market should be satisfactory to cover 99% of the time the suspension spends moving in the real world, but you have to be careful about the maximum force for the rear shock. If you’re a technician that is working with supercross suspension, there could be some real challenges if the dyno isn’t up to the specification you need.

Something else to watch out for here, is that this is only one example with some pretty big assumptions about the damping forces created by the suspension, and data from just one session on one track. There can be a lot of variables that skew the outcome of this study one way or the other.

There is no doubt that dyno’s are an excellent tool for performing quality assurance checks, as well as optimising the damping characteristic for different type’s of riders. Even if you want to see what the force curve is at the max fork speeds of 7m/s that we saw in the first graph, by running the dyno at max speed of 3m/s, you could probably have a good guesstimate at what the damping curve looks like.

If you want to work with the Motoklik system, you can email [email protected] with any questions you have.

Kind Regards,

Jens

Average speed of suspension in motocross.

In our last article, I wrote about how to improve accuracy when analysing suspension data.  When making changes to suspension shim stacks however, it can be extremely helpful to know how fast the suspension is actually moving, to know which part of the damping system to target i.e. the mid-valve or base valve stack on forks for example. In this article, we will look at sample data from one track. So let’s jump straight into it.

All speeds shown in each graph are metres per second, and the graphs show the lap overall average, as well averages for different sections of track.

The graph above shows the average compression speed of the front forks for the overall lap, as well as different sections of the track.

The graph above shows the average rebound speed of the front forks for the overall lap, as well as different sections of the track.

The graph above shows the average compression speed of the rear shock for the overall lap, as well as different sections of the track.

The graph above shows the average rebound speed of the rear shock for the overall lap, as well as different sections of the track.

One thing that might be jumping out at you is that the fork speeds are much higher than the shock speeds. This is because the front axle is connected directly to the fork, whereas the rear axle is connected to the swingarm, and then through the linkage. This connection reduces the speed from the rear axle to the shock by around 3:1.

There are also some observations which we knew already from the last article, like how the fastest speeds are measured at the jump take offs, and how the compression speeds are slightly higher when braking into a turn, than accelerating.

From my experience, it has to be said that the speed of the rider, the speed of the track and the roughness of the track can all have a significant impact on the average speed values measured, and just because an overall fork compression value of 0.476m/s works well on one track, it absolutely doesn’t mean that this is a target value to aim for at every other track.

When you match this data up with a force / speed graph from a suspension dyno, and with experience know which areas of the curve relate to which part of the shim stack, this data becomes incredibly useful in finding answers fast to suspension setup problems.

If you would like to work with the Motoklik system, or have any questions, e-mail [email protected]

Kind Regards,

Jens

Making accurate predictions on suspension setup in motocross.

In our last article, I wrote about the challenges of suspension data acquisition in motocross, and why we believe it hasn’t been widely used to date. As part of that discussion, I brought in some fairly abstract ideas to do with height of children versus adults, and how to accurately predict the temperature on a given day in Ireland. If you were brave enough to stick with that to the end, thank you, because today you will see where I was going with it!

Where we ended up was that by using a larger historic dataset based on averages, we can improve the standard deviation (σ; pronounced sigma) of our data, the ± bit. When σ is improved, we can make more accurate predictions about the value we should expect for height, temperature, or what we’re interested in, suspension speed. Let’s finally get to the good bit, looking at some actual suspension data measured by Motoklik.

The image above shows the speed of the front forks over the course of one lap on a motocross track in Germany. Anything greater than 0m/s is compression, and less is rebound. Looking at the data like this, it all looks like a bit of a mess. If we are to take the average σ for the full lap, we get:

Front Compression = ±0.611 m/s

Front Rebound = ±0.382 m/s

Rear Compression = ±0.526 m/s

Rear Rebound =   ±0.239 m/s

However, when we take a closer look, we can start to see some patterns…

Any guess for what the data above is?

Yes, you’re right it’s a jump! (Well maybe you read it from the graph title, but I’ll give you the benefit of the doubt 😉). It’s pretty easy to recognise how the forks are compressed on the upramp, how they stay fully extended in the air, and how they compress again on the landing.

Let’s look at another example.

No guessing this time, this is data from a turn on the track. It shows the speed of the front suspension. You can see on corner entry how the forks are compressing and rebounding at much higher speeds than they are exiting the corner. The apex of this turn is around sample number 151.

The point I am making is that as we start to look at the data more closely, we can see how some data is more related than others, so if we are to group all of the data from turns together, and all of the data from jumps together, and from braking and accelerating and so on, what do you think might happen to our σ?

The image above shows the front fork σ for the overall lap, as well as for the different sections of track we have grouped together. The blue line represents compression, and the yellow rebound. The green space between the flat line, and the data line shows how much we have improved the σ by grouping the data together.  We see a really good improvement for most things, except for maybe braking, and jump landings. Remember, a smaller σ allows us to make more accurate predictions!

The image above shows the rear axle σ for the overall lap, as well as for the different sections of track we have grouped together. The blue line represents compression, and the red rebound.

So overall we are showing a massive improvement in the accuracy of compression data, and some good improvements for rebound, but the rebound data was already more accurate than compression from the get go.

There is one Achilles heal though, and that’s the jump landing data. On both front forks and the rear, we got a significantly worse σ value 🥹 Does this mean all our hard work was for nothing? Surely we can find an answer that makes this all worth while.

Stop and have a think about what we could do next…

Well what do we know about jumps? From the “Front Suspension Position for 1 Jump” graph closer to the start of this article, we can see that when we are taking off and landing from a jump, that the suspension moves a big distance in a short amount of time. This must mean that the suspension on average is moving a lot faster on a jump than elsewhere on the track. Is this true?

We can check this easily by calculating the average speed of the suspension movement for each of our grouped sections. It gives the following results:

Front Compression Lap Average: 0.476 m/s

Front Compression Jump Landing Average: 0.907 m/s

Rear Compression Lap Average: 0.463 m/s

Rear Compression Jump Landing Average: 1.108 m/s

Hey! 😲That’s a pretty big difference in average speed!

Now we know that adjustments to higher speed movements of the suspension will have the biggest effect on jumps. Let’s try adding a group, within a group, and see what it does to our σ value for jumps.

When we filter out the low speed movement of the compression from the data, we dramatically improve the accuracy of predictions for jump take off’s and landings. We have to be a little bit careful here though for two reasons:

1: When we look at the jump take off speeds, there aren’t  that many that reach up into the higher threshold, which in most cases is going to give us a better σ value by default.

2: The jump landing σ still isn’t quite as good as the overall σ, but it is a whole lot better than where it was.

Right, let’s try and wrap this thing up.

It can be easy to dive into all these numbers and get very excited, but it’s more important to not lose sight of what we are actually trying to achieve.

We are trying to give riders the best suspension setup possible for the current track conditions and their riding style.

On most suspension we can control the low speed compression and rebound on the front and rear, and the high speed compression on the rear via the clickers. We know now that jump data is mainly comprised of high speed movement of the suspension.

If we redesign our graphs to those shown above, we can look at how much we have improved the accuracy of our predictions for the clicker adjustments by grouping the data together in related track sections. We can even take this a few steps further, and add in more sub-groups to group the data together even more.

As you can imagine, to break out the track like this manually for every lap and every section can be a terribly time consuming task, but the results are totally worth it for the improvement we get in suspension setup prediction accuracy.

I think that’s enough for today’s discussion, and if you’ve made it all the way to the end, thank you for your time.

If you would like to work with us, or use the Motoklik system yourself, and you have a few questions, feel free to send an email to [email protected] 🙂

Kind Regards,

Jens

The challenges of suspension data in motocross.

On Track Off Roads Adam Wheeler released an article this week on the OTOR website with the focus on data and how it is used in MXGP.

In the article, Adam writes about his interaction with the topic over the last 10 years, and what the current view in the paddock is on working with sensor technology on dirt bikes. Around the mid 2000’s to early 2010’s, we saw the move to data acquisition in motocross, most notably with Chad Reed’s TwoTwo Motorsports Honda, but little has changed in terms of the actual hardware or software since that time. There are a myriad of things that can be measured in motorsports all based around temperature, pressure, flow rate, strain and position, but of course our focus here at Motoklik is on suspension.

So what are the current views on suspension data acquisition in motcross? Thanks to Adam, we have some answers on hand:


Roger Shenton, Team Co-Ordinator, Team HRC: We’ve used sensors on suspension for a few years but we never race with it. It’s delicate. We have to use a harness and the bike carries more weight, so we put it on only for pre-season and mid-season testing to know what the suspension is doing and not just for rider feedback but to see what our technology is doing. We don’t incorporate it with racing at all.

 

Wim Van Hoof, Technical Manager, Standing Construct Honda MXGP: I know they use sensors on the suspension in the U.S. and in supercross I can understand it as the track changes little compared to motocross, and how many times a season do they have a mud race?! They don’t have braking bumps like we do or changing lines. If we put sensors on our suspension then after two-three laps the data will have changed, and from where can you make the comparison?

 

Harry Norton, Red Bull KTM Factory Racing Team Technical Co-Ordinator: Being able to understand the exact forces on the suspension is useful. If you could put suspension data over engine data on the track then you’ve got a really clear picture of what is happening. For sure there are already people looking into this and I think it will be a priority for teams in the future.

As per Roger, Wim and Harry, suspension data is used at MXGP and Supercross level, but there are two main challenges, reliability and changing track conditions.

In the picture above, you can see the types of sensors most commonly used today. This is a carry over technology from tarmac based motorsports and not built particularly with motocross in mind. While that sensor technology works brilliantly on-road, some of the issues faced by these sensors in off-road are:

  • Contact parts and electronics get exposed to sand, water and grit causing them to fail prematurely.
  • Shafts bend during high speed movements.
  • Return springs aren’t fast enough to measure high speed compression movements accurately.
  • Accuracy can be reduced from changes in pressure due to temperature and oil volume fluctuations.

What has Motoklik done to overcome these problems?

We knew from the outset, that a reliable system is key to making suspension data work in motocross. This is the reason why we developed our own brand new type of sensor (shown in pictures below) that solves all of the issues outlined above. How did we do that? Magnetism! Magnetic field strength is an amazing feat of physics. It’s ability to pass through materials eliminates the need for contact parts, however, until now the distance that could be measured was limited by how sensitive the sensor was. The new Motoklik sensors work over longer distances and adapt to changes in the position of the magnet in the x, y and z axis’s making them incredibly versatile, and who knows maybe we will see them used in other professional motorsport in the near future 😉

Our first problem of reliability is now solved, but what about the ever changing conditions? Surely a track that’s lines and roughness change from lap to lap can’t be interpreted through data…

If we put on our data scientist hat here for a minute, what’s really being said is that motocross suspension data has a really high standard deviation value. Standard deviation is a measure of how spread out the data is that has been recorded.

An example would be the heights of people. If we had a classroom full of 5 year old’s, and we measured their height, we would get an average of 109cm ± 4cm. If we measured a room full of adult men, it’s 1,778cm ± 8cm. The standard deviation is the ± bit, and just because adult men have a higher standard deviation, it doesn’t mean we can’t make relatively accurate predictions about their height, in the same way that just because motocross suspension data has a higher standard deviation than road race data, it doesn’t mean we can’t apply data analysis techniques to it.

The trap that you can easily fall into is focusing on one specific issue at one specific part of the track. Suspension setup in motorsport is a compromise. We need to have a wide view of all opinions (or in this case data) to make a fair decision. This gives a clue as to what one part of the solution is when analysing suspension data in motocross.

Let’s work through an example again, and this one is close to my heart, the temperature on a given day in Ireland. The graph above is the maximum temperature from everyday throughout 2022. We can see a bit of a trend there as we go from Winter into Summer, and back to Winter again, but a prediction as to what the temperature is going to be on a certain day is very difficult to make with any level of accuracy. This is what happens when we look at suspension data for one specific section of track, or one specific lap. We’re trying to make a prediction with a low amount of historical data.

When we add in data from the last 10 years, things become a lot more clear. We can see how most of the data lies inside the two curved red lines, so on any given day we can make a prediction within around ± 2.5°C. The accuracy of our prediction can be further improved if we add in more data such as humidity, atmospheric pressure and cloud cover. This is what’s possible when we have enough suspension data to work with also.

So why hasn’t that been done before?

I believe the answer lies in the reliability of the current sensors used, and the individuality of the data recording. With race teams and manufacturers having to work on their own, it’s very difficult to record enough data with such a small group of riders. There is a lot of time already spent on trying to test cams, gearing, ecu maps, triple clamps, linkages, tyres, handlebars and so on, it leaves very little time to dedicate to suspension data recording especially in Europe with bad weather and the sensors may not last more than a couple of laps.

This is where Motoklik has such an advantage. We can reliably and continuously monitor and record the data from 100’s and 1000’s of riders from all over the world in every type of condition to build a vast data base of suspension data to make predictions on setup, in the same way that Google uses internet browser data to predict what items you might be interested in buying, or where you’d like to go on holidays.

There is a lot more that can be done to improve the accuracy of our predictions for suspension setup, but as you might think, it starts getting tricky to do it on your own if you are separating out the data into multiple features and combining it with a huge historical data base. This is where Artificial Intelligence comes in, but I think that is a topic for another day 🙂

MOTOKLIK AiSetup in Gatedrop review!

Excellent suspension is one of the most vital components of speed around a motocross circuit whatever the level. A fast bike with bad suspension won’t help as much as a slower bike with great suspension.

Suspension is crucial for trust, speed and safety but setting it up is complicated for most riders. For many, it’s a bit of a guessing game but that guesswork is now redundant thanks to Motoklik, a revolutionary company making great suspension set-up available everyone.

Motoklik is an easy to use, easy to fit, robust suspension setup and lap-timing system for use in motocross.

In short, once the sensors are on, everything can be done on your smartphone and gives you, to the very last click, how your suspension should be set up from hard pack to sand, the sensors on the bike are tracking everything from lap times, and gives information as detailed as relative speed based on track roughness to earlier in the day as well as when and where the bike bottoms out. It’s impressive and could revolutionise how the weekend warrior is able to set up their bike.

So, does it really work? We tested with club rider Richard Greer to get feel of how the product really can benefit the average rider, and spoke to Stuart Edmonds , who currently uses the technology at the Pro level, we also caught up with MotoKlick CEO Jens Koepke to learn more about the product that’s available here.

From club rider to pro, the reflections were positive.

Stuart Edmonds: “I don’t think anyone who gets it shouldn’t get a benefit out of it. If they don’t they are doing something wrong. Straight away you stick ot on your bike and you get your laptimes and suspension combined. It gives you a massive input on increasing speed, increasing stability on the bike and being able to ride faster for longer and being comfortable.

“Sometimes in myself you get a bit caught up with is it too hard or soft. To be able to go and look at the date and be able to tell straight away, ‘yeah, it’s actually too hard.’ It’s an asset for me to have.”

Richard Greer: “It is going to help. It gives you the ideal set-up for you and that track. You would become a better rider and better test rider just by using the system and making the changes it recommends and go from there.”

“I could feel the improvement, I could feel the suspension moving more. We took five clicks off the front and a few clicks off the back. When I made the adjustments I could go through the bumps, there wasn’t as much fighting with the suspension.”

Get the full in-depth verdict below:

Read the full press release on the new AiSetup to learn more about their latest technology:

Motoklik, the industry leader in motocross AI technology, is proud to unveil AiSetup, an innovative artificial intelligence software that revolutionises suspension set-up and lap-timing. With AiSetup, riders can optimise their suspension settings without the tedious trial-and-error process, thanks to precise recommendations generated by advanced AI algorithms.

Motoklik Key Features:

  • Streamlined Suspension Tuning: Say goodbye to time-consuming trial and error. AiSetup provides clear, easy-to-understand recommendations for clicker adjustments, saving valuable track time and frustration.
  • Lap-Timing: Motoklik’s lap-timing technology enables riders to track and analyse their performance while correlating it with suspension settings for better insights.
  • Compatibility: AiSetup works with the main motocross models, ranging from 85cc up to 450cc, providing optimised suspension settings for a wide range of bikes.

Jens Köpke, CEO of Motoklik, shared his excitement about the launch of AiSetup, saying, “Motoklik has always been committed to pushing the boundaries of innovation in motocross technology. With AiSetup, we are redefining suspension tuning by leveraging the power of artificial intelligence. We believe this software will revolutionize the way riders approach suspension set-up and help them unleash their full potential on the track.”

Motoklik’s AiSetup is set to disrupt the motocross industry, offering riders of all levels an unprecedented level of precision and efficiency in suspension tuning. The system is available on Motoklik’s website, and is compatible with a wide range of motocross bikes.

For more information about Motoklik and AiSetup, please visit www.motoklik.com or contact [email protected]

Select your currency