May
Racing is the combination of a team of people, the creativity and skill of the driver, and the technology behind the car. It’s not just the driver. It’s an engineering race. The Renault F1 Team knows this as well as anyone. As a technologically innovative powerhouse, they understand the role technology plays in completing their mission. They understand even better that it’s not the technology alone that leads to championship-winning teams: it’s technology under the power of people.
It takes a dedicated team to produce a winning Formula One car, from Renault’s Enstone and Viry-Châtillon Technical Centres to the track. The thousand-strong team is constantly exploring how to push the limits of engineering, making cars faster and more reliable than ever. Each piece of information is imperative to understand the dynamics of the car and transform these forces into performance.
Last year I was assigned by Microsoft to photograph how they are working with Renault F1 in the technology race of data for pole position.
Every time Renault F1 Team drivers Daniel Ricciardo and Esteban Ocon get behind the wheel, more than 200 sensors collect over 50 billion data points that help the technical staff improve aerodynamics, performance, and handling. But one of the most vital sources of data isn't a sensor or computer. It's the human behind the wheel, whose point of view provides valuable information on how the car is performing and behaving; something that a sensor can’t communicate to the engineers.
The team must be able to trust the data they receive, analyse it, and visually interpret it in the most efficient way. Microsoft technology such as Azure Batch, artificial intelligence tools, and HoloLens, can help filter through each valuable piece of information—whether it’s human feedback or data generated by sensors—to create that competitive edge and help Renault F1 Team continue to vie as a credible championship contender.
The team is running thousands of digital scenarios with Azure Batch in order to improve modifications, pit stop tactics and more. The scalability of the cloud enables the team to these scenarios in minutes, reducing costs where previously it would have taken hours on-premise.
Renault is also using artificial intelligence (AI) to find insights from the billions of data points it generates every race. Azure Machine Learning can search the data for anomalies, allowing engineers to spend more time on innovation.
Renault is also using artificial intelligence (AI) to find insights from the billions of data points it generates every race. Azure Machine Learning can search the data for anomalies, allowing engineers to spend more time on innovation.
The team has already gone from placing ninth in 2016 to sixth in 2017, and after this year’s seasons, ranked fourth. Pierre d’Imbleval, Renault Sport Racing chief information officer, is confident that the use of technology will help the team improve further.
“We are at the top of the midfield. What will change the game is how we embrace technology that makes us even more efficient. It’s about being smarter in the way we work.”
