Learning Corner: Data & Telemetry Webinar Series for the 2024 Season

Shell Eco-marathon Partner, Schmid Elektronik, will be hosting a series of Data & Telemetry Webinars on how to use data-driven racing to improve your performance on track. The sessions will be hosted by owner and CEO Marco Schmid himself.

This webinar series (basic, intermediate, advanced) will give you a competitive edge on-track by leveraging insights from race data – helping your team optimise your vehicle, innovate your mileage challenge strategy and driving tactics, and, ultimately, improve your on-track performance through greater energy efficiency.

With data and precision woven into your gameplan, you can even advance your way towards the Championships!

All sessions will be conducted in English.


Level: Basic, 30 minutes + Q&A
On Friday March 8th at 7:00 AM (GMT) and at 3:00 PM (GMT)

Participants will learn to understand the data provided by the Shell Eco-marathon telemetry system. Together we will find out how to interact with this data via the data and telemetry portal and how to catch the low-hanging fruit to improve your performance on the course.


  1. Recap of what the Telemetry System is and how it works
  2. The story behind the Telemetry System and Data-Driven Racing
  3. Understanding race data using the example of electrical energy consumption
  4. Dive into the GPS race line and GPS speed profile
  5. How to distinguish between instantaneous and cumulative energy use
  6. Identify the worst and best lap and improve based on driving patterns
  7. Develop an easy to understand and easy to implement race strategy


Level: Intermediate, 30-45 Minutes + Q&A
On Monday, March 18th at 7:00 AM (GMT) and at 3:00 PM (GMT)

In this intermediate webinar, participants will learn how to analyze race data using the familiar Python programming language and the Jupyter notebook. The goal is to create a foundation for your individual analysis by reusing the programming framework we provide. We also show you a nice way to look at individual race attempts and also compare lap by lap.


  1. CSV-Export into a Spreadsheet to load into custom programming environments
  2. Ad-hoc Cell-by-Cell Analysis with Python and the Jupyter Lab
  3. From Time-Series to Lap-Distance Motorsport Data, detect the Lap-Line Crossings
  4. Find the extremes with quantitative data analytics
  5. Identify race patterns with qualitative data analytics
  6. Catch the low-hanging fruits by combining qualitative and quantitative data analytics
  7. Fine-tune the energy efficiency of two similar laps


Level: Advanced, 45 Minutes + Q&A
On Tuesday March 26th at 7:00 AM (GMT) and at 3:00 PM (GMT)

In this advanced session, we will go one step further and show participants data-driven racing by solving physics problems in a data science way. You will learn to model a holistic race scenario that includes vehicle dynamics, track models and environmental factors. The key is to elegantly solve the multi-objective problem of best energy efficiency, shortest lap times and safety at all times. To do this, we use knowledge graphs and graph transformers such as the A*. In this way, we merge the dimensions of space, time and information into a holistic model that connects all the dots and leads to a global optimum.


  1. Understanding the challenge of several opposing goals and how to approach them
  2. Describe the states for speed and location with the graph nodes
  3. Describe the cost for each state transition with the graph edges
  4. Using a graph transformer to the optimal path through the graph
  5. Get to the edge with a dynamic racing framework



Turn this knowledge into actionable results on the bootcamp hosting by Schmid Elektronik and taking place at the physical events!