MotoGP’s next tech revolution? Sensors on riders!

MotoGP

The rider accounts for around a third of the combined mass of a MotoGP bike. Engineers have tons of bike data but they need to know where the rider is sat and what he’s doing

Brad Binder on KTM

Brad Binder leans right while his RC16 leans left between Phillip Island’s Lukey Heights and MG Hairpin. The RC16’s data recorder knows where the bike is but it doesn’t know where the rider is

Red Bull

Mat Oxley

MotoGP is filling up with technologies which many of us don’t understand.

For example, aerodynamics is a hugely complicated and often counterintuitive science. We see a new wing aero accoutrement and assume it does this, when in fact it does that.

And then there’s artificial intelligence, machine learning, neural networks, geometric deep learning and the other various computer sciences that make our minds boggle.

All of these sciences already play important roles up and down the MotoGP pitlane, whether you understand them or not.

However, there is one factor in the MotoGP tech race that has been ignored, even though it’s hugely important.

Bike racers are moveable ballast, who shift position constantly

A race-ready MotoGP bike weighs around 160 kilos while its rider, wearing full battle dress, weighs maybe 75 kilos. Therefore the rider accounts for a third of the mass careering around the racetrack.

MotoGP bikes record data via around 500 channels, delivering info from engine, chassis, ECU and so on, plus there are several hundred calc (calculation) channels, which make mathematical calculations from multiple channels, so, for example, you can use rear-shock data to work out what’s happening at the rear axle.

Which means engineers know 100% of what’s going on with their motorcycles, right?

No, they don’t, because bike racers aren’t strapped into their vehicle like car racers. Bike racers are moveable ballast, who shift position constantly, to make the motorcycle work better during braking, acceleration and cornering. In fact the rider hardly sits still.

And this is the vital information that engineers don’t know – where is the rider when he’s loading the front or rear tyre? Where is he when he’s hanging off, trying to turn the bike faster? How much force is he putting into the left handlebar when he flicks the bike into a right hairpin? And how much load is he putting into the left footrest to reduce wheelspin exiting that hairpin?

Jorge Martin cornering on Ducati

Jorge Martin’s Ducati is kissing the apex, but his head is maybe two metres from the tyre contact patch. Accurate measurements of rider position would be a big help to engineers

Pramac Ducati

Recording this data would give engineers a much, much better idea of what’s going on and why. It would allow them to build much better computer models, so they can create more accurate computer simulations. Similar sensors are already used in some road-bike development programs, so it’s a no-brainer.

“If you want to model everything to understand everything you need to know all the major inputs in how the bike behaves and, of course, rider position is one of them,” says KTM’s MotoGP technical manager Sebastian Risse. “Already with video analysis you have a lot of tools, you just don’t have the video feed all the time.”

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Manufacturers already spend a lot of time and money using video analysis. Some employ their own cameraman who stand trackside and shoot motorcycles in all phases – braking, cornering, acceleration – and then use special software to overlay different bikes and riders, always searching for new knowledge and tiny improvements.

“Sensors on riders could make a huge difference,” says Pecco Bagnaia’s crew chief Cristian Gabarrini. “To know how the rider moves on the bike would be very interesting.

“Also, the pressure the riders put into the handlebars and footpegs would be very interesting. Because maybe one rider is in the same position as another, but he puts different pressure into the footpeg at a certain corner.”

“In F1 you know where the driver is,” says Aprilia rider Aleix Espargaró‘s crew chief Antonio Jiminez. “In MotoGP the guys move everywhere, so for sure if we could see how the rider changes the bike’s dynamic centre of gravity it would be very important.”

Image of sprinter

Companies like OptiTrack provide body sensors for movement sciences, to improve the performance of athletes and so on

OptiTrack

In fact, Aprilia is already looking into this.

“We are planning to do this kind of thing, because the most difficult point in making computer simulations is to simulate the rider as a control system that guides the bike – that’s very difficult,” says Aprilia’s MotoGP tech chief Romano Albesiano. “On the data we have now we can see where the loads are, but we don’t know where the rider is and what kind of pressure he is putting into the bike. Absolutely this is an important point of investigation.”

And Ducati is onto it too.

“This is the edge of our research, so I cannot talk about it too much,” says Riccardo Savin, Ducati’s MotoGP chassis and vehicle dynamics engineer. “But for sure understanding where the rider is and what he’s doing is very important for vehicle dynamics, aerodynamics and also ergonomics. We know the lean angles, the loads, but we don’t know where rider is.”

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So how would it work?

Human movement sciences are already a big thing in many sports, from athletics onwards. Sensors are applied to athletes to measure every movement, which is analysed to help them improve their performance. The sensors are highly accurate, with only 0.2mm of measurement error.

Thus MotoGP engineers would know exactly where riders are on their machines and what movements and inputs they are using to make them faster around the race track.

Will this technology be allowed by MotoGP’s rule makers? In recent years MotoGP has been very open to some areas of development – like aerodynamics – while closing other avenues – like electronics.

There’s little doubt that this kind of technology would increase knowledge of motorcycling and help engineers design better road bikes, so it would be logical to allow it.

And if not?

“If we aren’t allowed to race with it, we could still use it in private tests,” adds Albesiano.