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
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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.