F1 championships are increasingly determined by technology | Wilnesh News

Motorsport isn’t always a showcase for precision engineering.

“Twenty years ago, when you were building a car, the wishbone was going to go through part of the body; you drilled it out,” Williams CEO James Vowles told CNBC’s “Inside Track.” , you will find that the axle is in the wrong position.

However, with 24 races in the modern Formula 1 season and limits on race spending, even small mistakes can cost the title. To avoid them, teams rely more on digital tools. Car designs are actually rethought before being uploaded to a program that simulates surrounding airflow. Meanwhile, other software systems pressure-test every nut and bolt in varying weather conditions to ensure the design will remain stable throughout the season.

“Once we think we’ve found a high-performance design, we build a 60-percent version and put it into the wind tunnel,” McLaren business technical director Dan Keyworth told CNBC, adding that the prototypes are equipped with hundreds of Each sensor allows software engineers to simulate the car’s performance in different scenarios.

Unlike full cars that can’t be tested around the world, these “digital twins” allow teams to model the conditions a real car will need to perform. “There are a lot of things you need to analyze or process before you get to the track, including spending time in the simulator,” Red Bull driver Max Verstappen said. “Once the car is on the ground, you really try and optimize it.”

By doing this through digital twins, teams can develop strategies for different circuits. A car designed for a fast circuit like Silverstone in the UK will lack the grip and downforce required in a place like Monaco, where drivers need to use the full width of the track. With 24 races on the schedule and only a few days between races, forecasting track performance is crucial to ensuring engineers are prepared to make any necessary changes.

It also allows them to adjust their strategies on the fly. Although teams can have up to 60 operational staff on the track on race day, each team is communicating with analysts at headquarters. “We have a direct data link from the track back to our mission control room in real time,” said Ben Waterhouse, head of performance engineering at Red Bull. “Everyone there will be looking at their computers and providing feedback to the track engineers and providing Recommendations that can be implemented in racing.”

As the team moved from stopwatches and handheld engine temperature gauges to onboard sensors, those recommendations became more accurate. Generate 1.1 million pieces of data Points per second. “That’s where artificial intelligence and machine learning are very powerful because it can react much faster than humans can,” Walls said. “However, there are areas where human enlightenment is needed, for example if there is an accident, humans can very quickly look at and determine if there are red flags.”

With cost caps limiting the budget to $135 million per year, automating repetitive tasks was critical to ensuring the team was utilizing resources efficiently. Engineers have left the job of predicting inventory costs and organizing shipping to machines, while analysts use pattern recognition algorithms to determine when other teams are likely to pit during a race.

If worked well, governance can push teams to find new ways to use these technologies.
“In the past, we were able to take quite a bit of risk – are we going to get a performance advantage out of it?” Waterhouse said. “But the latest regulations are forcing us to change the way we look at innovation; to be very conscious of costs and to be more focused on efficiency.”

As artificial intelligence and other technologies advance, finding ways to deploy them will increasingly determine whether the F1 championship is won or lost. Tech companies have rushed in to help the team, with a slew of new sponsorship deals signed in the past two years alone. Unlike tobacco companies, which sponsored previous generations of F1 teams, technology companies are involved. Cloud computing giant Oracle not only paid Reportedly $300 million Becoming a title sponsor of Red Bull also gives them access to cloud infrastructure and artificial intelligence expertise. Google’s partnership with McLaren is built on similar principles, providing technology and expertise in exchange for a global platform where they can test it against commercial rivals.

This is not only a new era for F1, but also a new era for the sport. The greatest competitors are no longer the best athletes or brilliant strategists, but the most innovative ones.