Now for Part 3 of our series on telemetry data before we move on to other F1 performance related data. In our previous articles, we embarked on a journey through the crucial telemetry data points of speed, throttle position, brake pressure, tire temperatures, steering angle, suspension data, G-forces, and engine temperatures. Today, let's continue our voyage, unveiling a few more telemetry data points that hold immense influence over a car's performance. Let's dive right in!
Telemetry data captures the gear selection as the driver powers through the transmission. Gear data provides valuable insights into gear ratios and gear change points. Teams analyze this data to ensure the car's gears are appropriately matched to the track layout and optimize gear shifts for maximum acceleration and speed.
Example: During data analysis, a team may find that their driver is consistently hitting the rev limiter in a specific gear on a particular straight. By adjusting gear ratios or shifting points, engineers can improve acceleration and overall speed, maximizing the car's performance potential.
Telemetry data includes measurements of brake temperatures, providing critical insights into brake performance and durability. Monitoring brake temperatures helps teams understand how well the brakes manage the heat generated during heavy braking zones. Teams use this data to optimize brake cooling and ensure braking efficiency and reliability.
Example: Suppose telemetry data reveals that the brakes are reaching dangerously high temperatures during a race, increasing the risk of brake fade. The team can adjust the brake cooling ducts or modify brake materials to withstand the demanding braking conditions.
Telemetry data captures the rate at which fuel is consumed by the engine, providing teams with insights into fuel efficiency and consumption. Monitoring fuel flow rate data allows teams to calculate how long the car can run on a specific fuel load and optimize fuel strategies for each race.
Example: During data analysis, a team may notice that their car's fuel consumption is higher than expected during a race. By fine-tuning engine mapping or advising the driver to be more conservative with throttle inputs, the team can improve fuel efficiency and extend the car's range during races.
Telemetry data includes measurements of wheel slip, indicating how much the tires are slipping relative to the road surface during acceleration. Understanding wheel slip data helps teams optimize traction control and adjust throttle maps to minimize wheel spin and maximize acceleration.
Example: Suppose telemetry data reveals that the rear tires experience excessive wheel slip during acceleration out of slow corners. By fine-tuning the traction control system, engineers can improve grip, reducing wheel spin, and enhancing overall acceleration performance.
Telemetry data captures differential settings, which determine the distribution of power between the car's rear wheels. Differential data is crucial for achieving cornering stability, especially during tight turns and chicanes.
Example: Let's say telemetry data shows that the car suffers from oversteer during corner exits. By adjusting the differential settings, engineers can control the power distribution to the rear wheels, reducing oversteer and improving the car's cornering stability.
Telemetry data allows teams to compare current lap times with previous laps or reference laps from other drivers. Lap comparison data provides a benchmark for evaluating performance improvements or identifying areas for further development.
Example: During data analysis, a team may discover that their current lap times are slower than their fastest lap in a previous session. By analyzing specific sectors and comparing to the reference lap, engineers can pinpoint areas where improvements can be made to regain lost time.
Telemetry data includes measurements of tyre pressures, a crucial parameter that affects tyre performance and grip levels. Monitoring tyre pressure data allows teams to optimize pressure settings for different track conditions and improve overall tyre performance.
Example: Suppose telemetry data indicates that the car is experiencing inconsistent handling and grip during a race. By adjusting tyre pressures based on temperature and track conditions, the team can achieve a more balanced setup and maximize tyre performance.
So you can see just how important telemetry data from the car is for making strategic decisions to drive racing success. With Ludis Analytics, we can help your team make better use of the data that you collect to give you a competitive advantage. Reach out to us for questions about our products and services!
%203.png)
