MotoGP is packed with technology that many of us don’t understand.
For example, aerodynamics is a very complex and often counterintuitive science. We look at the new wing aero equipment and assume that this is what it does, but it actually does.
And then there’s artificial intelligence, machine learning, neural networks, geometric deep learning, and all the other computer science stuff that boggles our minds.
All of this science already plays an important role up and down the pit lane in MotoGP, whether we understand it or not.
However, there is one element of MotoGP technology racing that is extremely important and has been ignored.
Bike racers are mobile ballasts and constantly move positions
A racing MotoGP bike weighs about 160 kilograms, while a rider in combat gear probably weighs 75 kilograms. Thus, the rider accounts for one third of his entire career on the racetrack.
MotoGP bikes record data through around 500 channels, distributing information from the engine, chassis, ECU, and more. Additionally, there are hundreds of calc channels that perform mathematical calculations from multiple channels, so for example, we can analyze rear shock data to figure out what’s happening at the rear axle.
So that means engineers know 100% of what’s going on with their bikes, right?
No, it’s not. This is because motorcycle racers are not tied to a car like car racers. A bike racer is a moving ballast that constantly shifts position to improve the bike’s behavior during braking, acceleration, and cornering. In fact, riders rarely sit still.
And this is important information that engineers don’t know – where is the rider when loading the front or rear tire? Where is he when he’s hanging around trying to spin the bike faster? Or? How much force is he applying to the left handlebar as he flicks the bike into the right hairpin? And how much weight is he applying to the left footrest to reduce wheelspin on exiting the hairpin? Are you using it?
Jorge Martin’s Ducati is kissing the apex, but his head is probably two meters from the tire contact patch. Being able to accurately measure the rider’s position would be of great help to engineers.
Pramac Ducati
Recording this data allows engineers to better understand what is happening and why. This allows us to build better computer models and create more accurate computer simulations. It’s no surprise since similar sensors are already used in several road bike development programs.
“If you want to model everything in order to understand it all, you need to know all the key inputs for the bike’s behavior, and of course rider position is one of them,” said KTM’s MotoGP Technical Manager Sebastian Risse. say. “There are already many tools for video analysis, but the video feed is not always available.”