Early results show the potential to reduce aerodynamics simulation time.
A top technology company has joined hands with a high-performance vehicle manufacturer to advance vehicle design using AI and explore the use of quantum computing.
IBM and the Dallara Group, a world-leading racing vehicle manufacturer, are starting to explore how to integrate quantum computing in the design workflow and further boost simulation fidelity for complex aerodynamic problems. The two companies are also collaborating on the development of new physics-based AI foundation models. One early model was trained on Dallara’s proprietary and validated aerodynamic data of a high-performance vehicle.
Potential to reduce aerodynamics simulation time
The companies revealed that early results show the potential to reduce aerodynamics simulation time from many hours to few minutes and help engineers explore more design options earlier in vehicle development.
“Racing has taught Dallara that there are two possible outcomes: you either win or are forced to learn. IBM’s close collaboration on this innovative project is a testament of Dallara’s willingness to continuously push its boundaries and never stop learning,” said Andrea Pontremoli, Dallara CEO.
The companies revealed that AI models are being designed to help predict aerodynamic behaviors directly from geometry and related engineering inputs. As the collaboration progresses, IBM and Dallara plan to expand the AI models across a wider range of conditions, such as different maneuvers or overtaking scenarios, apply them to design new vehicles and develop tools that enable faster exploration of new aerodynamic configurations, before investing in intensive full-vehicle simulations, according to a press release.
AI to speed up aerodynamic design
“Some of the hardest engineering challenges come down to accurately simulating the physical world,” said Alessandro Curioni, IBM Fellow and VP, Algorithms and Applications, IBM Research.
“With Dallara, IBM is applying AI to speed up aerodynamic design today while advancing quantum computing in parallel to push simulation farther. Together, these technologies can help engineers move faster, explore more possibilities, and ultimately design better-performing vehicles.”
It’s also claimed that the IBM has been developing domain-specific foundation models in close coordination with Dallara. The companies revealed that the models leverage not only Dallara’s high-fidelity aerodynamic simulation data but also the company’s deep technical expertise. In a future step, the teams aim to integrate validated measurements of real vehicles in wind tunnels and on the track, but the use of high-quality simulation data alone is already producing compelling early results.
The companies also revealed that designing a high-performance vehicle means balancing downforce, drag, stability, and responsiveness across conditions that can change from race to race. Because some parts are designed with exacting precision, even small design changes can lead to surprisingly large impacts on performance, and the best aerodynamic solution is not always obvious. The companies claim that the AI models could help predict aerodynamic behaviors directly from geometry.
IBM and Dallara are starting to explore how quantum and hybrid quantum-classical approaches could further enhance race car design workflows. By combining Dallara’s expertise in high-fidelity vehicle engineering and CFD-driven design with IBM’s leadership in quantum computing and AI, the collaboration will evaluate where these methods can complement traditional simulation workflows in the near-term while identifying longer-term opportunities for practical use in automotive and motorsport design, as per the release.
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Prabhat, an alumnus of the Indian Institute of Mass Communication, is a tech and defense journalist. While he enjoys writing on modern weapons and emerging tech, he has also reported on global politics and business. He has been previously associated with well-known media houses, including the International Business Times (Singapore Edition) and ANI.