TIBCO Behind the Scenes: Andrew Shovlin, Mercedes-AMG Petronas F1 Team Trackside Engineering Director

Reading Time: 9 minutes

While every Formula One season brings various challenges, regulations, and changes, this season has played out as a unique battle for the entire grid. FIA—the sport’s governing body—launched the most significant technical regulation change in a generation, leading to unintended consequences for teams across the sport. Normally, the Mercedes-AMG Petronas F1 Team would focus on fine-tuning incremental car improvements across a season. But this year, the immediate focus had to be on gaining stability and consistency due to aerodynamic issues. 

David Rosen, vice president of customer and technology leadership at TIBCO, sat down with Andrew Shovlin, the Mercedes-AMG Petronas F1 Team’s trackside engineering director, to discuss how the team uses analytics to overcome major obstacles while setting itself up for success in the long term.

New Regulations and Challenges

David Rosen (DR): Thanks for joining me today, Andrew; let’s jump right in! The new car this year obviously represents the sport’s most significant technical regulation change in a generation. Can you describe the new regulation changes and the biggest challenges that were presented by them?

Andrew Shovlin (AS): The new regulation changes for 2022 completely changed how the car’s aerodynamics work. The intention was to try and make the cars better at following, very much impacting how much of a turbulent wake they generated. But the impact on us was that it completely changed how you needed to run the cars, how you needed to develop the cars, and the whole aerodynamic structures are changed. So we’ve worked hard trying to understand where the performance in these regulations was going to come from and how we optimize the car itself.

DR: Were there certain aspects of the regulations that were harder to deal with than others?

AS: One of the biggest challenges of the new regulations was that the cars want to run really close to the road, right on the road, in fact, because that’s where these ground-effect aerodynamics generate the most performance. So a lot of the challenge in how you actually run the car is about getting it to work that close to the track—but without the downsides of it hitting the ground. Then on top of that, there’s the phenomenon of porpoising that we’ve had to deal with that was largely unforeseen. We expected that there might be issues where the car will be essentially sucking itself to the road surface, and we knew that might throw up some challenges in how we had to run it, but the actual dynamic effect of porpoising wasn’t one that we had anticipated. It was quite a new problem when we started running the car. One of the big challenges was to understand the mechanisms at play. We were very focused on getting to grips with those because understanding the mechanisms would be the key to developing within these regulations.

2022 Mexico City Grand Prix, Saturday

Analytics and Bold Design Choices

DR: How instrumental were your analytics capabilities in diagnosing the challenge, finding its root cause, and then solutioning going forward?

AS: When we launched the car, and in particular when we were doing the pre-season testing, we realized the scale of the problem. We had a car that you couldn’t really race sensibly. It was unstable on the track. It was very difficult for the drivers in braking zones. We couldn’t actually get our hands on the performance that we designed into it. It then became a race against time, not the normal development challenge, but this was how quickly we could understand this problem, get to grips with the mechanisms, and develop it out of the car. 

That’s where the TIBCO Spotfire analytics became very valuable because we’re generating hundreds of gigabytes of data over that testing period. We’re trying to understand and drill down into the mechanisms to look for the trends from run to run, in effect, the trends that are taking place when we’re making changes. On the aerodynamic side, it was a case of trying to spot the trends and the mechanisms that are giving us clues as to what is actually happening here and how we can change the car aerodynamically to try and stop it.

DR: We’ve heard and read about some of the design gambles that went into the car design for this year. What would you say were the bold chances that you took in designing the car or the boldest thing that you changed?

AS: One of the boldest steps we took was a design where we were trying to create the maximum volume for the aerodynamicist to work with, but to do that, we had to create the tightest packaging of any car on the grid. And creating that creates a great deal of design challenges. It’s very difficult to get stiffness in certain areas of the car. Everything also wants to run hot because you’ve put everything together in the same space. But the reason we were confident to take those bold design choices, to take those risks, is that we’re able to look at all the simulation data, trying to explore where the potential is within the new regulations, looking at hundreds and thousands of simulations to realize that this was the route for us that was going to give us the best long-term prospects and the best long-term scope for development on the car.

2022 Mexico City Grand Prix, Saturday

Simulations and the Total Car Redesign

DR: You mentioned simulations, which I think is one of the most fascinating ways the team prepares for races. Can you expand upon the role that TIBCO plays in that simulation process?

AS: A new set of regulations presents an awful lot of opportunity. One of the challenges within the organization is for the different groups to work out how they can use that opportunity and how we can all work together. So to understand that, we’re running millions of simulations across aerodynamics, vehicle dynamics, across the system side, looking at the car cooling, trying to work out what is the best overall compromise. What is the fastest overall race car? To do that, we can share the data of all of those simulations using the TIBCO Spotfire analytics across the whole site. It makes it very quick, very efficient for the different groups to discuss these, to look at those trades and those compromises, and home in on the optimum solution overall.

DR: This year, I read that you kept just the steering wheel and the gas pedals, but everything else has changed. When you think about a redesign, do you think about that holistically, or is it extracting the most from individual components? How much of this is about finding harmony when everything’s working together, versus getting every ounce out of every individual component?

AS: The new regulations did mean that practically only the steering wheel and the pedals carried over. Almost everything else was new. This created an extreme challenge for us on the design side. The traditional way of developing a Formula One car was often just to make each individual component as good as you could, the best engine, the best suspension system, and the best brake system. The modern way of looking at it is that the whole car has to function holistically. You’re not just looking for the best in one area. You’re looking for the best overall compromise. As you expand that design challenge, looking at the influence of one area on another, it becomes almost impossible to develop it in the old sense of trying to improve each component, and you end up moving to a completely simulation-based world where the driver can actually drive the car around the track without ever having made a part. It allows you to make those right decisions and get things correct the first time, but the only way of doing this is if you can collate huge amounts of data, you can start to analyze those efficiently, and it allows you to ultimately make the right decisions at the end of the day.

DR: From a design standpoint, how do you balance decision-making across short, medium, and long-term gains?

AS: When we started to run the car, we realized that there were huge challenges to try and get on top of the porpoising and the bouncing, and they weren’t really foreseen in the design phase. We knew there might be issues running the car close to the ground, but we hadn’t realized the issues would be as complicated and as involved as they were. We took the view, looking at a medium- to long-term future, these regulations are in place for four years, and the way that we were going to be successful over that period was to try and understand exactly what is going on, what mechanisms were causing this issue. Because if we could understand the mechanisms, and importantly, if we could simulate them and model them, we would then be able to develop within that landscape. 

Now that process was quite costly. It perhaps didn’t give us the best start to the season that we could have had, and maybe a more experimental approach on the track, just trying things on the car would’ve given more instantaneous results, but the investment in that learning, in developing our capability, and in developing the simulation capacity to really understand the mechanisms is the thing that will put us on a route to long-term success. The early part of the season was very much about damage limitation, and the car wasn’t behaving in the way we wanted. It was a very difficult car to drive and to engineer, but we used all our simulation tools to try and find the best possible scenario there. And very much on the track, it was about just trying to score every point we possibly can. If any of our competitors make a mistake, we were there to pick up the pieces. And that approach was buying us the time to understand the issues that we were facing and to conduct the experiments at the track because by changing things, we learn every single time. The more experiments we did, the more we were learning. And ultimately, those experiments were breeding the understanding and the development of our tools that allowed us to bring parts to the track that could actually start to fix the problem.

2022 Sao Paolo Grand Prix, Sunday

Long-term Development and Collaboration

DR: How would you say TIBCO is helping you stay focused on big-picture success?

AS: TIBCO allows us to focus very much on long-term development. During a season, each race is different. Each race presents different challenges, and you need to run the car differently. But when you start to look at it over a range of seasons, you can start to understand the trends and what car will give you the best performance over 24 races. Because that’s the car that ultimately is going to win the championship. And these tools are allowing us to optimize for the small scale of a single race weekend but also the much broader scale over a whole range of tracks, from Monaco all the way to Miami, which are very different challenges. And that allows us to ultimately put the best car on the track that we can. 

We’re leveraging TIBCO’s tools to support the storage and visualization of large amounts of data. Not just the data that we get off the car but the data from all the simulation tools. And we can actually take the car data and augment it with model data that you can then expand far more than you could ever think to measure on the car itself. That then gives you the challenge of how do you actually visualize this and how can you efficiently make decisions based on it? And that’s where TIBCO’s tools give our team an advantage because the speed that you can analyze and visualize means the faster that you can actually learn, the faster that you can hone in on that optimum setup. And ultimately, that’s the challenge that we’re trying to achieve at the race track.

DR: Let’s double-click on this notion of collaboration. An endeavor such as this broad redesign requires a lot of hard work and collaboration across the entire organization. Can you explain the shared responsibility across teams to make this new car design—and the subsequent changes since preseason testing—successful?

AS: A Formula One team is made up of many different groups. We’ve got a very substantial aerodynamics department and a vehicle performance department. You have systems and power unit integration, and the challenge is getting all those groups to work together as well as possible. And every single group has its own simulation tools. They’ve been developing them all to try and optimize their own individual areas, but where TIBCO Spotfire helps the team in particular, is you can bring together all of those different groups, all of those simulations, and very efficiently work across the organization to try and find the best solutions for the car. 

DR: The Mercedes-AMG Petronas F1 team is clearly committed to data and analytics to guide decision making. How critical is TIBCO to your success on that path?

AS: Formula One has become a data-driven and hugely technological sport, and ultimately how well you can handle data, store data, and visualize data is becoming one of the key elements to competitiveness in Formula One. And that’s why at the Mercedes-AMG Petronas F1 team, we want to harness that analytical power that we can get through TIBCO to try and help us make better decisions using that data more efficiently every day. The challenge at the start of the season was, very much, trying to get the porpoising under control. Running the car the way we actually designed it to run—close to the ground without any of the bouncing and disruption. 

The progress on that goal has been good. We’re now getting to a stage where there isn’t much more to find, and the challenge shifts to one of incremental development. How can we understand these regulations, which carry on through to the next season and the season beyond? Where is going to be the performance that we can develop onto the car? Where are the opportunities, and how can we optimize what we’ve got to get that incremental development? Because success in Formula One is very much about development rate and having a development rate faster than your competitors. And if we can achieve that, then we’ll be in a position to win races and win championships in the future.

Racing to Success with TIBCO

Enjoyed the 2022 Formula One season? Learn how the Mercedes-AMG Petronas Formula One team has used the TIBCO platform to operationalize data into insights—informing car design, race strategy, and driver performance. And to hear Andrew Shovlin tell more about the 2022 Formula One racing season, check out this video.