How Formula 1 car sensors create data at every turn

Modern F1 racing cars are networked, connected, intelligent machines that can include hundreds of sensors and nearly a mile of wiring. These sensors provide billions of data points for analysis that help teams outperform the competition, like when data from the Mercedes-AMG Petronas F1 car helped Lewis Hamilton achieve his spectacular victory at Silverstone this year.

So where are all of these sensors, what data are they collecting, and how is this data used by engineers and drivers? Here’s a closer look at the lean and average data factories within modern F1 cars.

What sensors are on an F1 car and what data do they collect?

Without going too deep into the way cars are built, there are different systems – the engine, exhaust system, gearbox, differential, and aerodynamics – that communicate with each other. Engine control unit (ECU) is the center of a car’s system, and the standard ECU (SECU) is a small, powerful computer inside the ECU. The SECU was commissioned in 2008 and acts as the basic car data storage unit, responsible for processing and transmitting data from the car to the team.

There is also a power control module (PCM), data logger main control unit (MCU) and steering wheel, which also serves as a remote data interface for drivers.

Then, sensors are affixed to various places in the car. Sensors fall into three distinct categories:

  • Instrumentation sensors, such as pressure and fuel flow sensors.
  • Surveillance sensors, that send data channels to the health of the car’s systems.
  • Control sensors, that transform the driver’s inputs into the car’s outputs (eg throttle or ignition).

They can be magnetic, optical, and even laser powered. Here are some examples of specific sensors:

  • Temperature sensors, including engine and airbox temperature sensors, and non-contact temperature sensors that measure friction between parts with infrared energy. Thermal cameras can also provide non-contact heat detection.
  • Accelerometers, which measure the g-forces created during turns or braking.
  • Pressure sensors, measurement of hydraulic systems.
  • Dual axis sensors, braking and steering measurement.
  • Tire sensors, measure wear, grip, temperature and pressure to tell engineers how tires hold or affect the car’s balance.
  • Pitot tubes, which are small tubes containing sensors that measure airspeed, the same type of sensor used on commercial airplanes.
  • Ultrasonic fluid flow sensors, that monitor fuel performance.
  • Laser, which measure the distance from the car to the ground.
  • Damping potentiometers, measurement of spring compression and chassis roll response.

And don’t forget the F1 car’s version of a ‘black box’: the Accident Data Recorder (ADR), which also collects data from the sensors and sends an immediate alert in the event of an accident.

How is the data from the sensors transmitted from the car to the team?

Sensors and other in-car components broadcast data to each other through an in-car network, which is connected to an on-board server. This data is then encrypted and sent to the teams by radio frequency from an antenna mounted on the car. All of this happens in fractions of a second.

It’s not just any radio frequency, however. On tracks in more crowded cities like Singapore, it can be difficult to cut through the noise on race day. Formula One Management (FOM) has created a standardized communications network that operates a fiber link and shared access points located throughout a track that provide encrypted communications for each team between the car and the garage. This sends out small data packets in real time while cars can also emit a burst of microwave data when in range during a pit stop.

What happens with the sensor data collected from the car?

In an article on how Formula 1 teams get agile data at the edge, we looked at how data is collected, processed and stored by the Mercedes F1 team with mobile data centers powered by Pure Storage®. But what do engineers do with this data?

Back in the race assistance room, the data is processed and mixed with audio and video data to paint a clearer picture of:

  • Pre-race testing. Similar to an airline pilot running a pre-flight checklist, pre-race sensor tests are performed by a data engineer, including calibration checks and adjusting the conditions of each track. Each circuit is unique, which makes those front and mid-race sensor readings so critical. Get track-by-track insight into how data about each circuit’s unique physics helps inform racing strategies.
  • Mid-race follow-up. On race day, engineers can spot monitoring issues, allowing the rider to make adjustments in a fraction of a second.

Two examples:

  • A driver is lagging behind a competitor in an aggressive attempt to pass. The exhaust of an F1 car, with temperatures ranging from 950 to 1000 degrees, can be like putting the car in an oven. If the engine temperature begins to rise to an unsafe level, engineers can tell the driver to back up until things cool down.
  • Data from the tire sensors helped inform a second pit-stop strategy at the Barcelona Grand Prix this year, giving Mercedes and Lewis Hamilton a winning edge on the fly.
  • Regulatory conformity. The Fédération Internationale de l’Automobile (FIA), the governing body of F1, has strictly regulated the technologies allowed on board and closely monitors them via sensor data. Each team’s data center is directly connected to the FIA.
  • Strategic watch. Car data isn’t just stored after a race. Data is added and processed over and over again, sometimes in future seasons. Competitor data also plays an important role in the overall analysis of F1. Sensor data can be analyzed from a car in isolation or combined with data from competitors. Look at the turns, for example. This is a great use case for overlaying sensor data with data from competitors to compare two rows on the same lap to see which vertex is better.
  • Driver behavior. The sensors generate telemetry and recording data from the car itself, but they also monitor driver behavior. This data is a great tool for teams to give operators quantifiable feedback on how to improve their handling. Driver metrics include the percentage of a lap a driver spends at full throttle, how he uses the brakes, and how he takes turns.

Mercedes-AMG Petronas F1: Driven by Data

Modern F1 cars are incredibly impressive and complex systems that have become more sophisticated over the years, giving engineers (and drivers) more responsibility but also more insight. Today, winning is a successful marriage of the two: a data-driven instinct.

Explore further the world of F1 and find out in detail how the Mercedes-AMG Petronas F1 team wins with data with the help of its official technology partner, Pure Storage. Download the Advanced Guide to learn how to earn with your business data.