The Perfect Lap Issue no.3 - Page 14

SAP Perfect Lap Issue 03 Their sophisticated data analysis and simulation tools meant McLaren arrived in Sochi with ultra-detailed circuit profiles, so the first exploratory practice laps on October 10 amounted to little more than finetuning of a well-established baseline, rather than a drawn-out process of trial-and-error. No coincidence, then, that from the very first practice session, McLaren were right at the sharp end of the competitive lap times and came away from the weekend with a strong, podium-chasing 4-5 finish. “We were able to use better-quality data ahead of Sochi to ensure that we were better prepared than we ever had been for any previous new grand prix,” notes Andy Latham, McLaren’s strategy team leader. “Data is hugely important whenever we go to a new track, like Sochi,” he adds, “because in order to prepare as best we can, there are so many different things that we need to know about – not just how to set the car up particularly well, but also about how to go racing at a racetrack.” As Latham relates, ‘data’, in the broadest sense, is all about providing intelligence to a race team – increasing its brainpower, by broadening and deepening its knowledge base. Details such as the 014 length of the pit lane (and therefore how much time is taken to enter and exit) are stored; as is vital information on how easy it is to overtake and where a circuit’s best passing spots might be. All this information arms driver and team, equipping them to achieve their best performance on a given race weekend. “The big one,” says Latham, “is how to set the car up, such that we extract the maximum lap time. That’s a matter of both pure performance, and also to make sure that the car is suited to the drivers.” The driver, he explains, is a key part of the team’s strategy process and tailoring bespoke race plans to a driver’s particular needs and style is a vital aspect of data analysis, both before and during a race. “Some drivers may be able to look after their tyres for longer than another, so making sure that we mould our strategy to work for him is part of what we’re here for.” But achieving that simple-sounding-yet-oh-sodifficult-to-realise-goal requires the maximum possible amount of data to populate factory-based simulators and models, which in turn allow the construction of the most accurate pre-race analysis.