Tyre behavior

warm-up phase (the firsts one or two laps)

performance phase (depending on the compound, from 10 to 20-30 laps),

degradation phase (depending on several factors, it can be very few laps),

Give-up (in very short time).

During the warm-up phase the tyre reach the optimal working temperature in its working range. The working range depends on the compound and other factors. Pirelli tyres for F1 2013 season have the following working ranges:

Low Working Range Super Soft, 85-110 deg

Medium, 90-115 deg

Hard New, 90-115 deg (from Bahrain 2013 onward in the season) High Working Range

Soft, 105-125 deg

Hard, 110-135 deg

The degradation phase occurs for wear, abrasion, graining and blistering and the lap time start to increase. It is time to make a pit-stop to change tyres.

The give-up occurs when the cyclic stress reached the maximum acceptable level for the compound and construction. The combination of stress and heating generate mechanical and chemical changes in the rubber causing the lap time increasing sharply. Usually the car is called at the pit stop before this phase because it can cause tenths of retard on the pace.





Weight effect (on lap time) The weight-effect is a value that expresses how faster the car run while the weight decrease because of the fuel burned. It is measured as seconds/lap/10 Kg.



It can be estimated at the Lap Time Simulator (LapSim), an application running on a PC, with experiments at different level of fuel or just by fitting real data public available from FIA.

The LapSim gives, for Australia 2013, a value for Weight Effect of 0.22 sec/lap/10kg.



As alternative, the Weight Effect can be easily estimated by fitting real data. Let’s consider the real lap times from Australia 2013 F1 race from three drivers. The weight-effect is a value that expresses how faster the car run while the weight decrease because of the fuel burned. It is measured asIt can be estimated at the Lap Time Simulator (LapSim), an application running on a PC, with experiments at different level of fuel or just by fitting real data public available from FIA.The LapSim gives, for Australia 2013, a value for Weight Effect ofAs alternative, the Weight Effect can be easily estimated by fitting real data. Let’s consider the real lap times from Australia 2013 F1 race from three drivers.







For comparison, if we take the best of the fitting cases above we get a Weight Effect of 0.0722 sec/lap. Knowing that the fuel consumption in Australia is somewhat as 2.5 kg/lap, the fitted Weight Effect will be 0.29 sec/lap/10kg, not so far from what we get from the more accurate simulation and not so bad considering the “noise” affecting the second measure.

Going through a normalized value per 10 Kg is not really needed for this purpose but it is important to compare the weight effect of different race circuits.



Race Strategy example Option-A and Option-B. Both options use the same sequence of tyres, SuperSoft/Medium/Medium. For comparison, if we take the best of the fitting cases above we get a Weight Effect of 0.0722 sec/lap. Knowing that the fuel consumption in Australia is somewhat as 2.5 kg/lap, the fitted Weight Effect will be, not so far from what we get from the more accurate simulation and not so bad considering the “noise” affecting the second measure.As a race strategy example, we want to compare two tyre management options for the Australia race, calledand. Both options use the same sequence of tyres, SuperSoft/Medium/Medium.





Option-A do pit at lap 13 and lap 35. Option-B do pit at lap 17 and lap 38. The pit-stop time is the same in both cases (20 seconds) and the tyre model, very simple and just for the purpose of this demonstration, is based on the Weibull degradation formula.





We calculate the lap time lap-per-lap for both options on the race distance including the weight reduction effect and the tyre behavior effect.









Then we sum the lap times in order to have a cumulative curve for Option-A and Option-B and we make the difference, lap by lap, of the last two cumulative curves. Results are plotted on the next chart.



By reading this chart, the conclusion is that at the end of the race, Option-A is slower of about 3.61 seconds respect to Option-B. Using this procedure, it is possible to play with different scenarios. During the race, simulated lap times are updated, lap by lap, with the real lap time and the scenario update in accordance. This is, in a very simplified way, what is behind a dynamic race strategy application. This tool is used trackside by the Performance Engineers with the support of the Strategy Engineer at remote garage, the facility located at the Team’s Headquarter. Such example is Neil Martin from Scuderia Ferrari, who has been known to update the team in terms of strategy via remote link from Italy.

Making the right strategy call is, of course, very important. The recent example was Mark Webber in Hungary, 2013 - he had to start P10, running for a long period on Medium compound and eventually making it to P4 with very late usage of the Softs.

Maurizio Bollini is the owner of MET Milano (www.met.it), a consultancy firm involved in motorsport. In the past he worked as engine engineer for Michael Schumacher when he was the Ferrari F1 driver, during 1996 to 2006. He can be contacted at maurizio.bollini@met.it.









A given set of tyres is used in a race stint. During the utilization in the stint, the tyres go through four phase of life:Theis a window whose duration depends on the compound, the track characteristics and the car. For the softer tyres it could be somewhat like 10 laps, for harder tyres it could be in the range 20-30 laps. In this phase the tyres gives the best performance and so the lowest lap time.