In the world of Formula 1, the difference between the quickest driver or the fastest car and a team finishing last comes down to mere fractions of a second per lap. Those crucial few tenths of a second that make all the difference are the result of many factors, including aerodynamics, weight, race strategy, driver, tyres, and fuel composition.
These factors are optimised in real time by F1 teams: sensor-captured data is sent to the cloud, while teams run Monte Carlo simulations at their headquarters as the race happens. Decisions are made based on what sensors on the car are reading, as well as driver and engineer feedback, and audio and video feeds from the track.
"To optimise the performance of racing cars, F1 teams are very interested in big data processing, game theories, statistics and machine learning to inform race operations as well as future car design," says Randeep Singh, Head of Race Strategy at McLaren Racing.
A five-year research technology partnership between McLaren Racing and King Abdullah University of Science and Technology – KAUST – focuses on R&D and extreme performance technology. The partnership's main objective is to push science and engineering to new limits and improve the performance of the F1 racecars.
Through the partnership, KAUST researchers are working with McLaren Formula 1 to tackle sensor challenges in several application areas: strain sensors, flow sensors, inertial sensors and various wireless sensors.
"By exploiting the latest fabrication technologies, in the KAUST laboratories, we are able to create specifically tailored sensor solutions. The goals are to make the sensors lighter and less intrusive, as well as to realise sensors that can provide measurement data which is not accessible with current methods," explains Professor Jürgen Kosel, Head of Sensing Magnetism and Microsystems Group at KAUST.
As a long-term goal, the team aims to develop wireless sensors to obtain temperature, load and pressure data from locations on the car that are hard to reach.
These projects result in exciting opportunities for KAUST faculty and students who work on providing science-based solutions to real industry challenges.