INSIDE LOTUS INTERVIEW WITH JAMES ALLISON
You know when he gets in the car he’s going to wring whatever lap time is possible from that car and if it’s not fast enough, it’s because the car is not fast enough. If, for example, tyre wear is too high, it’s because it’s eating the tyres too quickly, it’s not the driver...you want that consistent baseline. If the driver is also articulate and capable of explaining to you what it is he feels is a limitation on the car, then that’s a very valuable bonus. With Kimi we are fortunate to have both of those things. He is very clear and very articulate in focusing on the things that we need to do. You don’t want a carpet bomb of random noise from the driver, but a clear set of ‘do this, do this, do that...’, that’s very helpful. And finally, when you have a very experienced, proven driver and you have a young, fast and raw driver, the benefit to the young, fast, raw guy in having the proven guy to work with and learn from is massive. The access to the data of the other car and the approach that the other car is taking through the weekend is completely and transparently visible to the newcomer. That helps the young driver ratchet themselves up the learning curve more rapidly.
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DL: How important is driver feedback versus what the electronic sensors and telemetrics tell you? For example, are there times when you have to trust the driver’s judgement when the data is apparently in conflict with the driver’s assessment? JA: There’s very rarely a conflict between the two because the data is excellent for certain things and lousy for others. The driver, for example, can’t tell you how hot the radiator is or whether he has overheating tyres. Some things lend themselves to objective measurement very easily. Data is terrific for that type of thing. Data can be good for seeing when the driver is over-revving or making small errors in the way he is using certain systems in the car. The drivers don’t fight against that; they regard that as a helpful thing because it is data they can’t gather any other way. But data doesn’t have much to say about the handling of the car. You could generate a channel that tells you whether the car is understeering or oversteering and that’s a mathematical channel, but it doesn’t tell you what an acceptable level of understeer might be. That is very much a driver preference and different drivers can tolerate different levels of understeer, or at different points of the race or track. You need to rely on the driver on what’s acceptable and once you have that threshold of acceptability established, then you can use the SPRING 2012 proActive magazine