Now that Lewis Hamiltonand Mercedes can safely claim, yet again, Formula 1 Driver’s and Constructor’s championships, lets dig into how these F1 cars go so darn fast. Is it simply a matter of producing horsepower? Downforce? Spending a boatload of cash?
An F1 Grand Prix is a three-day weekend event that typically includes two days of practice and qualifying followed by a race on Sunday. On Friday, the racecar is loaded with sensors so the team can see what’s working and what’s not. By Saturday, the car is stripped of all but the most critical sensors, and the car racing on Sunday must be identical to the Saturday car.
Hundreds of sensors collect and transmit data on thousands of components (including the driver). The amount of data collected can be up to a 3TB per car just for race day (Sunday). Over the racing weekend (Thursday – Sunday), the total for both cars can reach 30TB or more (just 5 years ago it was ~50GB). The data is then used to make adjustments to downforce, tire pressure, suspension, and more. Tuning the car is very complex as each adjustment affects other areas of the car.
Chasing diminishing returns? Consider this: There are ways to execute a gear change faster, but at the expense of increased wear. You could gain tens of milliseconds per lap. To most of us, that’s nothing. Now consider that, for qualifying at the Austin Grand Prix this year, two people in qualifying had the same lap time to one-one thousandth of a second over a two-mile track, 50ms just got yourself one extra space in the grid.
As SAP is a partner of one of the longest standing F1 teams in McLaren. McLaren was one of SAP’s first HANA database customers. McLaren use data analytics to determine the speed of the car on various points and curves to analyze the performance. A car’s speed depends on the driver as well as the machinery used. The turning point is that the data analytics is going to be used not just to measure the speed of the car but the relative speed of the opponent as well. The analysts can predict the race before it finishes.
Going back to the current and 5-time Constructor’s Champion – Mercedes AMG – it turns out that we here at Hitachi Vantara have someone with keen experience in working the sport’s reigning top team. I’m going to hit up our own Ian Clatworthy for some insight into how a top F1 team uses analytics to go fast.
Dave Krenik: Ian, you’ve worked with one of the most successful Formula 1 teams of the decade – Mercedes AMG Petronas. Can you provide us some background on what you did with the team?
Ian Clatworthy: Hi Dave, thanks for having me. I joined the F1 grid in 2006 with the birth of the works Honda Racing F1 Team from BAR Honda. The team then because Brawn GP in 2009 before being purchased in 2010 by Mercedes AMG. When I joined the teams were very much at the beginning of automated analytics and using world wide data links to provide live telemetry and voice back at the factory.
DK: Ian, please give us glimpse as to how Mercedes integrates Analytics into their F1 program.
IC: At the time the business was running SAP for all business operations from ordering supplies, logistics to recording how many miles parts on the car had run. For example, to know what suspension parts you needed to send to the next race depends on what is happening at the track real-time. So alongside normal internal and external communications, data-links were key at the track, 12 years ago this was achieved by ISDN lines (showing my age here), we would use between 16 and 25 lines per race to get the bandwidth we needed. This changed to lease lines as the hertz rate of data channels increased and with it came the ability for us to have more engineering resource supporting the events back at base in Brackley, UK. All of a sudden, we had the ability to review a wider source of data, from track temperatures, live car GPS to tire temps and wear. All alongside providing the ability for an engineer to open his notebook anywhere and analyze data real-time when a race is happening on the other side of the world. This is the fastest IoT device in the world.
DK: What sort of resources does Mercedes devote to Analytics in F1? Data Scientists? Translators? Etc.?
IC: Well on an F1 car there are over 200 channels of data being recorded, there is only so much of this data an engineer can process. In this case at every race there is normally around 40 engineers sitting in the “War Room” helping the resources trackside. But this is just the car, we also have to take into account all other variables on track. This could be weather, competitive strategy, engine mapping and now battery regeneration. This data can now be fed into a Data Lake to enable engineering to receive proactive insights live during a race. This business runs 24x7 so having live data updates enables just in time logistics, faster part production and even the ability to simulate tire wear real-time.
Thanks Ian – much appreciated.
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