Ferrari is seeking a swift comeback in Formula 1. The Maranello team aims to do so as early as next weekend at the 5.807-kilometre Suzuka Circuit, sending a clear message to the rest of the grid that the Prancing Horse is still in the fight. The simulation aspect, namely what is developed and derived from virtual data, is becoming increasingly relevant in modern motorsport. This is especially true in the most important motorsport series, where, as seen in the Chinese Grand Prix, even the smallest detail makes a difference.
So let’s take a detailed look at Ferrari’s approach to simulation. The Italian side entered the current racing season with a car that has undergone significant aero-mechanical revisions, including a different flow management, modified suspension efforts, and adjusted dive angles to stabilize the platform.
However, such an ambitious project requires time to be fine-tuned, and looking back, the amount of data gathered by the Maranello engineers and technicians has not been particularly extensive.
Over the winter, the team conducted every possible test to expand the car’s operating window using the simulator. However, real-world track conditions ultimately dictate performance: from the Fiorano shakedown to pre-season testing session at the Bahrain International Circuit, Ferrari’s engineers have been collecting data in order to recalibrate the parameters set in the simulator. As has been repeatedly stated, the simulator is used to prepare for race weekends but also plays a crucial role during and after the event.
The reason is that it allows for enriching the dataset used for event preparation with real-world data gathered on track. In the simulation environment, all vehicle parameters—especially those related to ambient conditions—are reset. These are then used to study setup changes for the race weekend and, more importantly, to define future developments aimed at improving the car.
Ferrari conducted the entire Sakhir pre-season testing session with a specific program, never chasing performance peaks. It was a “smooth” program, focused on finding a correlation with the data collected over the winter. It is unclear whether the Maranello team was fully satisfied with the comparison between real-world and simulated data, although the key figures involved have not expressed concerns.
Never pushing the car to its limit may have hindered the discovery of so-called “marginal gains,” which are particularly valuable when the car is pushed to the maximum. With the data gathered at the Bahrain International Circuit, the Italian side recalibrated its simulators in Maranello, though without a clear picture of how the car behaves in long runs. Ferrari’s engineers have certainly conducted simulations, but that is only part of the equation.
As we recall, the over two-second gap was not real. Rather, it was a sign of the different approach the team was taking. Once the spotlight faded from the Bahrain circuit, Ferrari analyzed the data collected on track before preparing for an atypical circuit like the Albert Park circuit in Melbourne, which is one with numerous irregularities and several unique characteristics.
We are talking about slow 90-degree corners, others with a limited radius, and a long high-speed section that effectively forced the team to raise the SF-25 car’s ride height, leading to a significant loss of aerodynamic load generated by the floor. After the Australian Grand Prix, the time available to analyze the collected data was relatively short, considering the back-to-back race with the Chinese Grand Prix.
Moreover, the range of race data gathered was not sufficient in order to fully understand the car’s behavior in long runs. However, one thing was clear: the Italian car was faster with an empty fuel tank, carrying less fuel, and running a lower ride height. This very principle was the basis for Lewis Hamilton’s completely unexpected success in the Sprint race.
The track data matched the simulator data. With a more efficient ride height, the Ferrari car showed a more stable rear end, allowing the balance to be shifted toward the front to improve corner entry. During the Chinese Grand Prix weekend, however, where the Maranello team suffered a heavy blow, there was only one free practice session before the serious action began.
The lack of simulator experience was evident during Sunday’s main race. On the first truly demanding circuit of the year, with a race pushed to the limit from start to finish, the absence of adequate simulation support became apparent. This factor contributed in part to the miscalculated weight on Charles Leclerc’s car and the excessive skid wear on Lewis Hamilton’s single-seater, following a more aggressive choice regarding static ride heights.
The importance of the data collected in China was therefore crucial. Japan is now just around the corner and from what we know, Ferrari has clarified many of these doubts. At the same time, the car’s behavior in long runs should now be well understood. The double disqualification at the Shanghai circuit highlighted the car’s limitations and allowed for more precise parameter adjustments in the simulator. Additionally, last week saw an in-depth analysis of the collected data, which proved to be highly beneficial.
Shanghai provided solid references, testing the Italian car from every perspective and allowing engineers to understand how far it can be pushed. With these new insights, the setup study for Suzuka has been completed effectively and coherently. The Ferrari engineers are now better prepared to handle unexpected behavior and, by utilizing the three free practice sessions, will be able to fine-tune the car more appropriately for both qualifying and the race.
This is a key step toward the much-anticipated performance improvement for the Italian cars. A greater level of mechanical efficiency is expected, reinforcing the crucial relationship with aerodynamics, an essential factor on the complex Japanese circuit. The primary focus? Stabilizing the car’s platform in the first sector, the most demanding part of the Suzuka track for the entire vehicle system.
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