Enlarge / Red Bull Racing’s Daniel Ricciardo prepares for the 2017 Australian Grand Prix.
“Big Data” has been on everyone’s lips in recent years. But Formula 1 racing caught this mistake a long time ago, certainly in the days before this catchphrase. In the past, we’ve looked at how teams like Williams Martini Racing, Renault Sport Formula One, and Caterham F1 (RIP) have dealt with collecting and processing their terabytes. Today is Red Bull Racing’s turn.
“I’ve been with the team for 13 years now, and we’ve been doing that for ages. The complexity of our measurements and the sophistication of the analytics keep getting better, but we’ve been doing big data for a long time, ”said Matt Cadieux, Chief Information Officer of Red Bull Racing. The data in question is collected by innumerable sensors in the team’s racing cars and adds up to around one terabyte (500 GB for each of the two cars) every race weekend.
“But if you look at all the other data we use – video, audio, number crunching to go through various simulations – that’s a huge multiplication factor,” he told Ars. Cadieux wouldn’t give us an exact number for that volume of data Call a race weekend so that this information doesn’t prove too useful to the team’s rivals in the paddock, but the team manages 8 PB of data company-wide. Cadieux estimated that 95 percent of this was related to vehicle design and vehicle performance – think Computer Aided Design (CAD) and Computational Fluid Dynamics (CFD), but also strategy simulations and historical telemetry data from previous seasons. “We have a very data-hungry business,” he said.
This data is fed back to the garage and used to determine the team’s strategy during the races. But it is also reported back to the engineering department in Milton Keynes, England, where it refines the cars throughout the season and influences the development of next year’s machines.
In recent years, the FIA - the group that writes the rules of Formula 1 – has been on a cost-saving kick. (It’s well-intentioned, but the FIA ignores the fact that every team spends every penny of its annual budget looking for better performance on the track.) That has put restrictions on the use of wind tunnels (which are limited to 60- Percentage scale), but also CFD modeling – with a maximum of 30 hours of wind tunnel time or 30 teraflops of CFD processing in one week (or a combination of both, as long as the combined mixture of hours and teraflops results in only 30). But the number of teams you can bring along on each race weekend is now also limited.
Keep HQ up to date
Enlarge / The Red Bull Racing simulator building at the team factory in Milton Keynes, England.
Getty Images for Red Bull
Like other teams we’ve spoken to, Red Bull adds data connections and enterprise software to its staff to put engineers into the headquarters. “Sixty people have operational roles on the circuit and we add a large number here in the UK. We have an operating room – branded by AT&T – that can hold more than 40 people at full capacity, ”Cadieux told us.
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For each race weekend and test session, the team sets up an MPLS (Multi-Protocol Label Switching) connection between the track and Milton Keynes, providing the operations room with real-time feeds for video, audio and voice chat. So when the team is testing a new part from the design office – for example a revised front wing – that part can be debugged with the design team’s expert in the operating room. “He can see how the car is going in real time and participate in technical debriefings that take place after every practice or qualifying session during a race weekend,” he said.
This connection back to home base also means that if the team has a specific problem with a car during the race, they can keep the system’s experts informed. “The real-time connectivity allows them to behave as if they were on the racetrack themselves,” said Cadieux. Other members of the team play a more proactive role, monitoring competitors to identify weaknesses or strengths that could affect Red Bull’s strategy. The platform the team uses for this is likely to be familiar to those of you who spend your workdays in remote meetings: Citrix.
“With Citrix we can look at applications that are very graphics-intensive or contain large amounts of data that you would not normally be able to interact with in a remote location,” said Cadieux. This includes the telemetry of the cars as well as the post-processing and analysis of this vehicle data, a server service that the team brings to every race, but which is then also sent back to the home base.
And data also flows in the other direction. With real-world testing now severely restricted by the rules, Red Bull uses the Friday training sessions of an F1 racing weekend to validate all the simulations it runs during the week. “Guys can upload large CAD assemblies, rotate them, cut large sections, and suggest changes for the future. With CFD you can open the animations and stream videos with more or less the same performance as if you were back at the headquarters. “he told us.
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Must keep it safe
Enlarge / The Red Bull Racing simulator from 2010.
Getty Images for Red Bull
Of course, all of this data needs to be well protected. Cadieux pointed out that Formula One is an incestuous industry, with most of the network operating from bases within 50 miles of each other in the UK’s so-called “carbon-fiber triangle”. Teams have relatively flat organizational structures, and Cadieux pointed out that an easy way to get promoted is to switch to another team and have the data in hand. (It is best known that a Ferrari engineer was caught handing documents to McLaren in 2007, but it has happened before – in 2004 Toyota was accused of using stolen Ferrari design plans.)
However, Cadieux said the need for data access controls needs to be balanced with the need not to slow down the pace of the team or make the work environment too uncomfortable. There are also external threats, both from other teams and third parties, looking for a ransomware payout. “Because we’re high profile, we tend to be a target,” he said.
But perhaps the most fascinating aspect of Red Bull’s IT work is one that Cadieux couldn’t tell us much about: machine learning and AI. “We are studying them to make better simulations and better racing decisions,” he said. “It’s just getting started; we’re working with multiple partners right now, but it’s the beginning of a journey. But I’ve been in IT for almost 30 years and there are more changes than ever before. It’s both scary.” and a huge opportunity. “
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