Antonelli won in Austin with a Medium–Hard one-stop and a 32-lap final stint on the C2. Leclerc and Verstappen, both on two stops, finished 13s and 17s behind. The first part of the race was already going Mercedes’ way: Antonelli had nearly 3s over Verstappen by Lap 10 despite starting on the Medium against his rival’s Soft. Red Bull brought Verstappen in around Lap 14; Antonelli stayed out until the end of Lap 24.

On the fuel-corrected traces, Antonelli’s first stint rises from about 1:36.8 to 1:39.1, with a fitted slope near +0.10 s/lap. The Hard stint is noticeably flatter, around +0.06 s/lap over 32 laps, equivalent to approximately 1.9s of lap-time drift. The fuel correction removes an estimated fuel-load contribution, not traffic, tire management, or changing track conditions, so neither slope should be treated as an isolated degradation coefficient.
Verstappen’s second Soft stint runs closer to +0.14 s/lap over 18 laps, versus roughly +0.08 s/lap on the final Medium. The Soft was not delivering a sustained advantage. Red Bull also reported debris damage and balance problems, which makes a purely compound-based explanation impossible. The two-stop still brought him back towards the front, but not close enough to challenge Antonelli.

Ferrari made better use of the final tire change. Leclerc switched to Hard after Lap 39, recorded the fastest lap in 1:37.976 on Lap 42, and passed Norris and Verstappen for second. Hamilton moved ahead of Norris as well and finished only 1.030s behind Verstappen; the late VSC halted his attempt at P3.

The ranking and violin plots add some context. Ferrari and Red Bull sit around 1:40.5–1:40.6 in median team lap time, with Mercedes nearer 1:40.9. Those samples combine two drivers and different stints: they should not be read as a clean comparison of car potential. Leclerc’s late Hard laps reach below 1:39, while most of his early Soft laps are above 1:40. Fuel load and stint timing matter more to that raw comparison than the colour of the tire.
Norris went Medium–Hard as well, but stopped after 16 laps and asked for the Hard to cover 40. He finished fifth, 30s behind Antonelli, after losing positions to drivers on fresher tires. Same nominal strategy, very different tire-age profile.

Pirelli found relatively high physical wear without a comparable rise in performance degradation, and the Hard worked better than expected. The distinction matters: material loss at the tread does not translate directly into the same loss of available lap-time performance. At COTA, Antonelli had enough pace left on the Hard to make the additional pit stop unnecessary.

Professor Flavio Farroni (“Federico II” University of Naples/MegaRide) is the project’s Principal Investigator

Milan, 21 October 2026 – Prometeon Tyre Group, a global tyre manufacturer serving the industrial, agricultural and OTR sectors, announces the launch of EPIMETEO – Enhanced Paradigm in Innovative Materials and Engineering for Tires Energy Optimization, a research and innovation project that focuses on developing a new generation of sustainable tyres for heavy-duty commercial vehicles.

The project, which involves the Vehicle Dynamics research group of the Department of Industrial Engineering (DII) of the “Federico II” University of Naples, aims to combine innovative materials, digital technologies and new design approaches to improve tyre energy efficiency, performance and sustainability. Scientific responsibility for the project and its coordination have been entrusted to the Principal Investigator Flavio Farroni, a lecturer in the university’s Department of Industrial Engineering and co-founder of MegaRide, a leading company in the modelling and simulation of tyre-vehicle-road interaction.

The initiative falls within the scope of the Italian Fund for Applied Sciences (FISA) promoted by the ItalianMinistry of University and Research, a funding instrument supporting research programmes capable of turning scientific and technological results into practical applications for industry.

Michela Caprio, Head of Materials & Compounding and Deputy Chief R&D Officer at Prometeon, commented: “EPIMETEO stems from our belief that sustainable innovation requires close collaboration between industry and scientific research. Together with the ‘Federico II’ University of Naples, we are working to develop new technological solutions that can improve the efficiency of heavy-duty vehicle tyres, addressing one of the industry’s most complex challenges: reducing energy consumption and emissions while maintaining high levels of safety, performance and durability. This project marks another step on our journey towards more efficient and sustainable mobility”.

Professor Flavio Farroni added: “Prometeon is a long-standing partner with whom we have been collaborating for over ten years and with whom, once again, we are perfectly in tune. EPIMETEO will focus on three scientific aspects: improving tyre contact with deformable surfaces, reducing energy consumption through lower rolling resistance, and limiting acoustic impact. Being selected under the highly competitive FISA calls, which require scientific and technical excellence and strong links with industry, is a source of great pride for us, as well as a responsibility in the use of the resources provided by the Ministry. Through this project, our research group aims to strengthen its role by combining technology transfer with basic and applied research”.

The sustainability challenge in road transport

The transport sector represents one of the major challenges of the global environmental transition. According to the Italian Ministry of Sustainable Infrastructure and Mobility, transport accounts for around a quarter of Italy’s total greenhouse gas emissions and more than a third of its CO₂ emissions.

For commercial vehicle tyres, it is therefore essential to reduce energy consumption and CO₂ emissions in both electric and combustion-engine vehicles by improving rolling efficiency. This is one of the main technological challenges in tyre development: finding the right balance between low rolling resistance and high wear resistance.

Tyre wear, which contributes to microplastic pollution^[1], is another increasingly important and related issue. This area, too, is undergoing profound change, driven by the need to reduce consumption and emissions, increase energy efficiency and incorporate more sustainable materials throughout the product life cycle.

It is therefore essential to design and develop tyres that combine lower rolling resistance with greater durability, ensuring optimal performance, safety and efficiency throughout the product life cycle.

EPIMETEO, the research project promoted by Prometeon in collaboration with the “Federico II” University of Naples, addresses this challenge.

A new paradigm for more sustainable tyres

EPIMETEO aims to develop a tyre prototype intended for research and technological validation rather than immediate commercialisation, designed to reduce the product’s overall environmental impact throughout its entire life cycle.

One of the project’s main objectives is to achieve a rolling resistance of 3.6 kg/tonne, corresponding to Class A, with expected benefits in terms of reduced energy consumption and CO₂ emissions associated with road transport.

The prototype will also incorporate advanced sensor systems to monitor parameters such as tyre pressure and temperature in real time, thereby optimising performance during use and helping to reduce fuel consumption and, consequently, CO₂ emissions, while promoting more even wear.

Sustainable materials and digital design

Sustainability is one of the project’s central pillars. The new tyre will be developed using up to 65% renewable, recycled or tyre-derived waste materials, through the study of new formulations and manufacturing processes capable of maintaining high standards of safety and performance.

EPIMETEO will adopt an advanced virtual prototyping approach that relies on mathematical and simulation models to replace experimental tests that tyres would otherwise undergo, in order to reduce the number of physical prototypes required during development and thereby cutting the time, costs and environmental impact associated with testing.

The university’s research team will contribute to the development of predictive models aimed at optimising energy consumption, studying energy loss through deformation (Strain Energy Loss), and analysing the viscoelastic properties of materials and tread design, with special emphasis also on noise reduction.

Research, innovation and technological expertise

The models will be validated through a hybrid process combining laboratory tests and road testing on physical prototypes, with the aim of ensuring high levels of safety, reliability and long-term durability.

Indoor testing will take place at the RACEARCH LAB laboratories of the “Federico II” University’s Department of Industrial Engineering and at Prometeon’s Innovation Center in Cinisello Balsamo (Milan), which will also conduct outdoor testing. The project will involve a multidisciplinary team of engineers, chemists, testing technicians and test drivers, with the aim of accelerating the development of technological solutions with a lower environmental impact.

Prometeon has an international network of four Research and Development facilities in Italy, Brazil, Turkey and Egypt, dedicated to developing products for the various global markets. The Cinisello Balsamo facilityhouses an important materials research area as well as a tyre performance testing area, and benefits from a €7 million investment allocated in 2024 to state-of-the-art equipment for its advanced chemical and physical laboratory.

Prometeon and the “Federico II” University of Naples team up for sustainable innovation

The collaboration between Prometeon and the “Federico II” University of Naples is a concrete example of synergy between industry and scientific research, aimed at transforming technological expertise and academic knowledge into solutions applicable to industry.

Through EPIMETEO, Prometeon reaffirms its commitment to more sustainable mobility by combining industrial innovation, scientific research and a focus on reducing environmental impact.

^[1] JRC (Joint Research Centre), Contribution of Road Vehicle Tyre Wear to Microplastics and Ambient Air Pollution, 23 October 2023; Regulation (EU) 2024/1257 (Euro 7), taking into account 20

Target tire pressures are defined for each circuit according to its layout, surface roughness and track temperature. Target tire temperatures are established by analysing how the compound responds to different excitation frequencies at the tire-road contact. These frequencies depend on surface roughness and local sliding velocity, which varies with circuit layout and vehicle dynamics.

MegaRide’s models use these pressure and temperature targets to evaluate warm-up procedures. Predicting how tire conditions evolve during the warmup helps identify the preparation strategy best suited to achieving the required temperatures and pressures during the flying lap.

Camber analysis examines how changes in wheel inclination affect tire-road contact, helping the team compare setup options and identify the settings that maximise grip under the expected operating conditions. The models also account for tire ageing, assessing how compound properties change over time and how these changes affect the tire’s ability to generate grip.

MegaRide and TRIDENT jointly define test programmes to assess tire operating conditions on track. MegaRide analyses the data collected during testing and racing, using these insights together with simulation results to guide car setup, tire management and the development of qualifying and race strategies.

At Budapest, with track temperatures around 50°C, MegaRide analysed whether the soft tires could maintain their performance over the full race distance. The analysis indicated that they would degrade too quickly, supporting TRIDENT’s decision to use the hard compound. This choice helped the driver maintain competitive pace throughout the race and finish in first place, while several rivals on soft tires struggled with degradation.

This work is made possible by a simulation infrastructure built jointly through years of technical collaboration. Its development draws on the team’s experience on track and the knowledge gained together over successive seasons. This continued exchange has contributed to TRIDENT’s FIA Formula 3 Teams’ title in 2021 and three consecutive Drivers’ titles in 2023, 2024 and 2025.

Max Verstappen converted pole into his first win at Marina Bay, finishing 7.3s ahead of Charles Leclerc and 24.6s clear of Kimi Antonelli. Behind the result were two contrasting approaches to the Soft C5: extending the opening stint to protect track position, or returning to the compound after the late Virtual Safety Car.

The lap-time distributions put Red Bull and Ferrari within around 0.1s/lap in team median, near 1:37.5 and 1:37.6, with McLaren and Mercedes around 1:37.9. These are uncorrected race-lap medians, not a measure of absolute car pace. Hadjar’s much slower distribution also makes the Red Bull team median less representative of Verstappen’s race.

Verstappen completed 32 laps on Soft before switching to Medium for the remaining 30. His fuel-corrected first-stint baseline sits roughly 0.2-0.4s ahead of Leclerc at comparable early laps. The fitted trend rises by around 0.06s per lap of stint, but this cannot be attributed solely to tyre degradation: traffic, management and evolving track conditions still matter.

The second VSC let Leclerc and Antonelli fit fresh Soft tyres on lap 39. At the start of the final stint, Leclercs fitted corrected pace was around 1:34.2, compared with roughly 1:35.2 for Verstappen on Medium. The advantage faded as the laps accumulated: Leclerc’s fitted trend rose by about 0.13s per lap, versus about 0.08 for Verstappen. These are observed pace trends, not directly comparable compound degradation rates.

Leclerc reduced his deficit from about 15 seconds on lap 46 to 7.3 at the finish, but the lead was never seriously threatened. Antonelli’s fresher tyres helped him exploit Norris’s battle with Hamilton and claim third. Hamilton, meanwhile, missed the VSC pit entry and completed a 44-lap Soft stint, eventually falling to sixth.

Pirelli reported virtually no degradation on the C4 Medium and strong durability from the C5 Soft, with no use of the Hard. Verstappen’s win came from combining a competitive opening pace with a long first stint and enough tyre life to avoid an extra stop.

MegaRide develops physics-based tire models that describe how grip, temperature and wear evolve during a lap and across a race stint. Used in desktop simulations and driving simulators, these models help drivers and engineers assess tire response, compare setup options and prepare qualifying and race strategies. Race support activities provide track data acquisition and analysis to characterize tire behavior and support simulation work.

VESevo measures the viscoelastic properties of racing compounds directly on the tread, without removing samples or damaging the tire. Teams can compare compounds, assess their consistency and track changes in material properties before and after track use. Repeated tests on the same tire provide data to support tire selection and management throughout a race weekend.

RIDEsense develops virtual sensors to estimate grip, sideslip angle, internal tire temperatures and wear in real time. The software platform provides data for vehicle and tire dynamics analysis, particularly in championships with limited onboard instrumentation.

Visit us at stand 4080 to meet the MegaRide Group team and discover our technologies for motorsport and automotive applications.

Max Verstappen took his first win of the 2026 season ahead of Kimi Antonelli, second at 2.3 seconds, and Lewis Hamilton, third at 4.9. Weather and neutralisations heavily shaped the race, with rain delaying the start, a Safety Car on Lap 9, and another late neutralisation after Albon stopped. Russell, who had been running in podium contention, retired with a power-unit issue.

The most relevant phase for pure pace comes after the first Safety Car. Verstappen switched from Intermediate to Soft, while Antonelli moved to Medium. After the restart, Verstappen passed the Mercedes and progressively opened the gap, reaching around 5 seconds by Lap 21 and more than 10 seconds before the neutralisation on Lap 43.

The fuel-corrected analysis helps explain that advantage. Between roughly Laps 15 and 32, Verstappen’s fitted pace moves from about 1:38.3 to 1:40.4, corresponding to an observed increase of around 0.12 s/lap per lap. Antonelli shows a very similar trend on the Medium, close to 0.10 s/lap per lap, but his corrected pace remains roughly 0.4 to 0.6 seconds per lap slower through much of the stint.

This suggests that Red Bull’s main advantage was not a dramatically lower degradation rate, but a lower performance baseline. Verstappen was simply operating in a faster lap-time window while maintaining comparable tyre evolution.

Hamilton provides another useful reference. Once slick conditions were established, his long first Soft stint shows a much flatter corrected trend, moving only gradually through the mid 1:39s to low 1:40s. That points to relatively limited degradation in that phase and helps explain why the Soft remained viable for such a long stint.

Leclerc’s first dry stint should be interpreted more carefully. His corrected lap time rises more sharply, but that phase is also affected by traffic and the consequences of the opening laps. It would therefore be misleading to attribute the full slope directly to tyre degradation.

The team median ranking places Red Bull at around 1:41.5, Mercedes at approximately 1:41.6, and Ferrari close to 1:41.9. McLaren is more than one second per lap further back in median pace, although its race was heavily conditioned by strategy and by spending long phases on the Hard.

The late Safety Car erased the gap Verstappen had built, but it did not create the performance advantage. The decisive phase came earlier, when the combination of lower corrected pace, strong Soft performance and consistent tyre behaviour allowed Red Bull to convert the compound choice into track position and race control.

George Russell converted pole into his third win of the season, beating Max Verstappen by only 0.2s. Isack Hadjar completed the podium at +10.7s, with Charles Leclerc fourth. Russell had built a clear lead before two successive Safety Cars compressed the field.

The opening stint already separated pace from compound choice. Russell and Verstappen started on the Medium, Hadjar and Leclerc on the Soft. Russell was nearly ten seconds clear of Piastri around halfway, while Verstappen reported that the Medium lacked grip. Fuel correction reinforces Russell’s advantage: his fitted pace rises from roughly 1:44.8 to 1:45.2 by Lap 30, about +0.01 s/lap, with a steeper trend for the other three.

That slope should not be read directly as degradation. Wear on C4 and C5 remained low and no significant graining emerged, allowing teams to extend the opening stint while waiting for a neutralisation.

The first Safety Car then created the most useful comparison. Russell and Verstappen switched Medium to Soft; Hadjar and Leclerc went Soft to Medium. After the restart, Russell and Verstappen improved towards 1:44.7–1:44.8 corrected pace, while Hadjar remained around the mid-1:45s and Leclerc drifted towards roughly 1:45.9. The Red Bull comparison matters: same car, opposite tire sequence, and the gap grows through the stint.

The Soft was not simply a short-life option. In these conditions, it became the stronger race tire. The main restart issue was how quickly the front axle returned to its operating window. Piastri’s race fits that picture: after the second Safety Car he locked up into Turn 1 on the Medium and lost a potential podium, while that compound appeared more difficult to bring back into the right temperature window in that phase.

Mercedes and Red Bull are separated by only about a tenth in median lap time, effectively the same performance window relative to the spread. Ferrari and McLaren sit roughly half a second back, although McLaren’s result was distorted by Norris retiring in the restart collision and Piastri’s Turn 1 error.

Russell’s win was not created by the Safety Cars. The lower corrected baseline, the shallowest first-stint trend and the gap built before the neutralisation all point in the same direction. The open question is the late Medium behaviour: Hadjar stabilises, Leclerc fades more clearly, while the Soft runners continue to improve.

Cadence is a leading computational software company, providing tools for electronic design, system analysis and multiphysics simulation. Through Adams, part of its System Design and Analysis portfolio, Cadence supports the modelling, analysis and validation of complex mechanical systems, including vehicle dynamics applications. Adams extends these capabilities to real-time validation workflows, enabling multibody models to be used in advanced virtual testing environments.

RIDEsuite combines physics-based tire models that account for the main phenomena influencing tire-road interaction, including grip behaviour, temperature evolution, road-surface irregularities, multi-contact conditions and tread wear development.

By connecting Adams with MegaRide’s research-based tire modelling technologies, the partnership supports a unified development process for vehicles and tires.

The integration brings tire behaviour directly into the vehicle model, enabling the evaluation of how tire properties, operating conditions and road inputs affect vehicle response. By strengthening the link between tire modelling and digital validation, it enables earlier virtual assessments, helping reduce development time and costs.”

Madrid gave Antonelli the win, but Norris was the quickest of the leading group for much of the race. Once fuel correction is applied, the McLaren trend sits ahead of both Mercedes and Red Bull through most of the long Hard stint.

By Lap 10, Norris had already opened a gap of roughly five seconds over Antonelli. Stroll’s stoppage and the Lap 13 VSC then reshuffled the race. Antonelli and Verstappen stopped under neutralisation; Norris came in once the track was green again and also lost time with a stop of around seven seconds. He rejoined P5, about 14 seconds behind Antonelli. From there, the task was no longer just about pace.

On the Hard, Norris moves from about 1:35.5 to 1:36.8, with a fuel-corrected slope of roughly +0.033 s/lap. Antonelli goes from around 1:35.8 to 1:36.9 (+0.027 s/lap), while Verstappen runs from about 1:36.0 to 1:36.8 (+0.020 s/lap).

At Lap 30, the Norris fit is around 0.24 s/lap quicker than Antonelli and 0.36 quicker than Verstappen. At Lap 40, those gaps are still around 0.18 and 0.23 s/lap. Only in the closing phase do the three curves come very close together.

Norris recovered enough to get back into the fight. Around Lap 45, the first four cars were separated by roughly four seconds, with Leclerc still leading on the Hard he had started on. Ferrari left him out until Lap 48, hoping for a neutralisation that never came. Once Leclerc stopped, Antonelli had clear air in front. Norris still had Verstappen to deal with.

Leclerc’s opening stint gives another useful indication of how far the Hard could be stretched. His fit moves from roughly 1:35.9 to 1:37.1, around +0.038 s/lap across almost the whole race. The late Soft immediately brings him back into the mid-1:35s before the pace starts dropping away. That final run is only nine laps long and comes in a completely different fuel and race condition, so its slope cannot be read in the same way as the longer Hard stints.

The team ranking is less straightforward than the order suggests. Mercedes and Ferrari sit almost together around a 1:38.2 median, McLaren near 1:38.5 and Red Bull around 1:38.7. Those distributions mix compounds, tyre ages, traffic and different race phases. Piastri’s first-lap damage and Hamilton’s early retirement also affect the team picture.

Antonelli eventually finished 4.351s ahead of Verstappen, with Norris another 0.738s behind. Despite track temperatures around 54°C, the Hard still allowed very long stints: the leading trio completed more than 40 laps on it, while Leclerc ran 48 laps on his opening set.

The VSC put Antonelli in control. From that point, Mercedes had enough pace and enough tyre life to keep him there. Norris was quicker for much of the race, but the margin was not large enough to recover the strategic loss and clear Verstappen as well.

MegaRide is a tech transfer holding born from the Vehicle Dynamics group at the University of Naples Federico II, specializing in the development of real time models to simulate the interaction between tires and the road. The company has started a collaboration with Raceyard, the Formula Student team based in Kiel, to provide dedicated training in tire engineering, vehicle dynamics, testing and simulation.

As the contact between the vehicle and the track, tires play a central role in vehicle performance. Understanding their behavior helps engineers interpret the vehicle’s response and assess the influence of tires when evaluating development choices.

The program will cover tire fundamentals, laboratory and track testing, tire modeling and vehicle modeling for data correlation. These activities will help the team relate experimental measurements to simulation results and examine how tire dynamics affect vehicle performance.

Drawing on MegaRide’s experience in automotive and motorsport, the training will connect the students’ academic knowledge with the engineering work carried out within Raceyard. The aim is to give the team’s young engineers a stronger basis for interpreting test data and making informed decisions during the development and testing of their Formula Student vehicle