Bright Lights, Big Data
The 2017 FORMULA 1 SINGAPORE AIRLINES SINGAPORE GRAND PRIX celebrates its 10th anniversary on the F1 calendar and is seen to be a firm favourite amongst teams and fans alike who all enjoy its quirky layout through the city streets, mixture of stop-start sections, furiously fast straights and the floodlit night-time atmosphere.
McLaren Honda Driver Fernando Alonso describes it as a ‘fun track’, ‘bumpy and challenging’, and over the past 10 years he’s built up a wealth of experience navigating and controlling his car through the unforgiving circuit.
But not all drivers can boast 10 years’ experience racing on the streets of Marina Bay and for McLaren Honda Formula One Team’s young driver Stoffel Vandoorne, it will be his debut drive on the track this year. So how does a Formula One driver prepare for a circuit they’ve never raced on before? The answer is data. Data plays an integral role in every driver’s approach to a race, and even more so for a rookie driver who relies solely on data supported by simulator practice in order to inform strategy and prepare for a new circuit.
Running on SAP HANA, the McLaren Honda Formula One Team have been capturing their race data for decades and now, equipped with SAP technology, they can access over eight billion data points spanning the last three seasons of F1 – and it’s this big data accessibility that makes a difference.
The use of historical data to aid the team’s strategic decision making and support a driver in preparing for a race is paramount. With limited practise sessions before Stoffel qualifies for his first Singapore Grand Prix, this valuable time cannot be wasted by learning the track layout, where to brake and what racing lines should be used to achieve the optimum lap time, therefore at the McLaren Technology Centre (UK) the team have a sophisticated simulator where both Stoffel and Fernando are able to drive the Singapore track in advance of the race weekend.
Through the use of the simulator, the team can help to replicate the car setup helping to make it as realistic as possible. The physical components of the simulator are a seven-poster rig with a McLaren chassis mounted on top, surrounded by a wide-angle display wall. To increase authenticity the cockpit features additional haptic feedback through the steering wheel and brake pedal, whilst pads placed on the drivers helmet replicate pressures the driver would feel under cornering , acceleration and braking.
Using historical car data and information obtained from laser scanning the track, what the driver sits in, sees and feels in the simulator is therefore familiar and very authentic and this simulator work will help Stoffel in familiarising himself with the track. However, a further unknown for both Stoffel and the team is that although they may know the track, this year’s McLaren Formula One car, the M32, has never raced at the Singapore track either. To overcome this problem, with the support of SAP HANA, Stoffel along with his race engineer can look at data not only from previous races in Singapore, but also from races earlier this year to help the team develop a baseline car setup before arriving at the track.
Using a query tool developed with SAP, the team engineers are able to use historical data to look for trends or abnormalities when comparing the mechanical demands and characteristics of the Singapore track to where the M32 car has already raced this year. As Mark Temple, McLaren Honda Race Engineer explains, “By having that historical reference, you can go into a Race Weekend more prepared than you were before. If you don't have historical information, you don't have the ability to save time before you get there. You need to be within the last 10% of performance in the first lap you're on track.”
Once at the track SAP will again be in the garage helping Stoffel and the team understand and develop the car as quickly as they can, this time by providing the ability to compare historical data alongside real time data coming from the car. As Mark Temple continues to explain, “So the big gain is that we have access to historical data as well as real-time data live in the form of summaries of every lap. We can pick out very specific parameters that help us pull together a lot of information into very simple charts and drafts that are easy to interpret. So for example, it might be that the driver is complaining about a particular corner that has become very oversteery, over the course of a day. We are now able to compare that back very quickly and say that that is a problem every year or perhaps that's a new problem. From this we can then relate that to differences that we see through the day and that helps us make plans to improve the balance of the car, and ultimately lap time.”
For a rookie driver, this all means the difference between being extremely exposed to unknowns versus being equipped with a depth of technical knowledge and insight that provides a huge advantage when taking to the track for the very first time.
So when the starting lights go out under the night-time sky in Singapore, Stoffel will be as prepared both physically and mentally as he possibly can be, as will his team of engineers all of whom will have poured over data to plan and prepare both Stoffel and themselves for the race. So it’s bright lights and big data as the team take to the track and Stoffel enjoys his first Singapore race experience – supported by SAP HANA.