The Perfect Lap Issue no.3 - Page 15
No model can ever fully replicate the real thing,
however, particularly at a venue where no
real-time running of any kind has taken place.
“Quirks,” as Latham refers to differences between
simulations and live running, are inevitable. “We
find out about them when we get there,” he says.
“Maybe the temperature is cooler, or there are
slightly different kerbs or bumps to what we were
expecting. Of course the drivers have to learn
the circuit, but, to be honest, they’re so good and
if the simulation’s been run before we get there,
then normally it doesn’t take them too many laps
to be up to speed.”
Once they are, Latham and his tech-team
colleagues will suddenly receive a glut of
fresh data to digest. This deluge of electronic
information is hugely valuable – indeed, for the
modern race team, data is the very essence
of performance – but the sheer quantity of
information presents challenges of its own.
From the basics of making sure that a car’s
essential systems are working correctly (eg is
the ERS energy recovery system harvesting
the requisite amount of power; is the DRS rear-
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wing-opening system deploying as and where it
should?), to fine details such as pressure loadings
on front wings at any given point of the circuit – all
of this is streamed to info-hungry engineers at
track and back at McLaren team HQ.
And it’s here that the McLaren-SAP partnership
pays one of its most valuable dividends. A key
philosophy for SAP is the mantra of ‘run simple’
– an idea that’s now central to its corporate
philosophy. And it’s as applicable to a race team
partner as it is to any data-rich environment.
“It’s easy to sink a little bit in the amount of data
and the volumes of data that are coming to you,”
says Latham, “so one of the key aspects is not to
get swamped by it. Try to simplify things and use
your experience to understand what’s important
and make sure that the data is being used to
solve the most important and critical decisions,
by the people who have the most knowledge to