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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 jens@motoklik.com 🙂

Kind Regards,

Jens

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 

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 info@motoklik.com

Motoklik: The Ultimate Suspension Setup and Lap-Timing System for 85cc Dirtbikes

If you are looking for a way to improve your suspension setup and lap times on your 85cc dirtbike, you need to check out the Motoklik system. Motoklik is an electronic device with unique suspension sensors, a mobile app, and a cloud database that allows you to measure and analyze your suspension performance and lap times on any track.

Motoklik is designed to work with motorcycles that have off-road capability, and it is now available for 85cc dirtbikes from GasGas, Husqvarna, and KTM. Whether you are racing motocross, supercross or enduro, Motoklik can help you achieve the best suspension setup for your riding style and track conditions.

Motoklik is easy to use, easy to fit, and robust. It comes with a central control unit (CCU) that is located between the triple clamps and behind the front number plate, a satellite position antenna that is located on the handlebar with a start/stop recording session button and LED indicator, a front suspension measurement wand that is located on the left fork leg, and a rear suspension measurement pack that is located between the frame and brake master cylinder. It self-charges from the bike’s power supply, so you don’t have to worry about replacing batteries or recharging.

Once you install Motoklik on your 85cc dirtbike, you can start recording your suspension data and lap times with a simple press of a button. After riding your first session, you can use the Motoklik app to see your data and get recommendations from AiSetup. AiSetup is a smart feature that analyzes your data and tells you how much to adjust each of the clickers for high and low speed compression and rebound, so you can ride with maximum confidence. AiSetup also notifies you if your valving or springs are too soft or stiff for your weight and ability, so you know if you need to have your suspension serviced by a technician.

With Motoklik, you can also see live sag readout, bottoming analysis, suspension position and speed analysis, section analysis, average speed, lap variation, speed vs. track roughness score, and more. You can compare different sessions and tracks, see which line is faster, and see if your suspension setup changes are making you faster. You can also upload your data to the Motoklik online dashboard and share it with your technician.

Motoklik is not just a data logger or data acquisition system. It is a suspension setup and lap-timing system that can help you improve your riding skills and performance on your 85cc dirtbike. It is a must-have tool for every dirtbike rider who wants to get the most out of their suspension.

Don’t miss this opportunity to get Motoklik for your 85cc dirtbike today. Click on Buy Now to order yours, and get ready to experience the difference that Motoklik can make.

During our trip to Southern California in March and April 2022, we were fortunate enough to meet with Trevor Hunter from Dirt Bike Test at Glen Helen, to try out the Motoklik system on his Yamaha YZ 250 FX. Check out the video below to hear Trevor’s initial thoughts on working with the Motoklik system.