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IT trends spotted and checked by experts

IT director at Lotus F1 Team

Mr Michael Taylor is IT director at Lotus F1Team, a UK-based Formula One motor racing team. He has been a part of the Lotus F1 Team setup for the past eleven years; joining the Enstone-based Formula 1...


The race for perfect, actionable data

14 Apr, 2014 10:26 am

The excellent use of data is absolutely vital to winning a Formula One race. At Lotus F1 Team, we gather and analyse huge amounts of information to help us design and develop cars, and win races.

Once the base product is established at the start of the season, the typical design life cycle of our cars is two weeks. This is because there are extensive performance and development changes between each race. Over the course of any season, excluding homologated parts, practically every component is likely to be changed.

Data is vital to this. We collect a large amount of information from how the car performs on the track, as well as from our factory in Enstone, Oxfordshire, where we develop the cars. The information can include all aspects of a car's performance as well as how each component reacts.

Phenomenal data growth

We have experienced an 80 per cent data growth in the last two years, and we now generate 100 gigabytes of data per hour at the factory on computational fluid dynamics. Each season, we also create 15,000 design drawings. At the trackside, we tend to generate over 25 megabytes of data per lap. We have over 1.5 petabytes of usable storage ready for us for the next two to three years, and we're going to need it.

In order to handle this volume of data, we have established two data centres that are geographically split but onsite within our Enstone campus.

Advanced simulation

There are only three in-season test sessions per year when, under the race regulations, we can test a particular design in practice. This means that on the whole, any new parts or components can only be tried out during the race weekend, and simulation before races is vital.

We use a driver-in-the-loop simulator that allows us to simulate a designed component or part and see how it would perform in a race environment. It also enables our drivers to test and give direct feedback to the new setup. As you can imagine, this uses a vast amount of data and the analysis is complex.

Live at the track side

Data is also vital to us during a race. On average, we will only send one of our 36 IT staff out to a race, and the remainder will be back in the UK maintaining, changing and monitoring technology as the race weekend proceeds.

Huge amounts of data are generated between the car and the pit, as we monitor how the car is running. It is vital for us to have 100 per cent availability of systems. Different members of the team have different displays to show them exactly the information they need.

In advance of the race, we simulate a variety of scenarios to assess the different strategy options to ensure we maximize our potential result  The baseline strategy helps us to react to change in real-time as the race unfolds, continually refining our strategy to maximize the end result.

Analysis for change

Data remains our biggest challenge in the long run. The key for us all is learning how to get the most from the information we have. As it stands, we only properly maximise around 30 per cent of our data, and we would like to see this change. Improvements are vital to our competitive advantage, and to our cost control and efficiency.

Traditional business intelligence is a major part of what we need to do with data, and this is the same challenge every team faces. The next step will be learning to understand exactly what is happening from every factor in a race, and developing the ability to run complex queries. This means correlating the various datasets, such as GPS, weather, tyre wear, fuel and so on, with driver behaviour and competitor actions.

The ultimate goal is real-time analytics. When you are generating over 2,000 different statistics per lap for each car, there is a real challenge around delivering fast, useful, accurate information to team members. We would like to have real-time intelligence so that we can make even faster changes during a race.

We know that getting more from our data is vital, and will enable us to make a real performance gain. But it is a long process and something we will work on over a period of time. The first steps have already taken place, and we will focus on continued change for great wins.

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