IBM, Dallara to Advance Quantum-Powered Design for Performance Vehicles

IBM and the Dallara Group, a racing and high-performance vehicle manufacturer, announced a collaboration to advance vehicle design and optimization using AI and explore the use of quantum computing.

The work combines Dallara’s expertise in high-performance vehicle engineering with IBM’s leadership in AI for physics and quantum computing to investigate how to accelerate aerodynamic design and open a path to even more advanced simulation workflows.

For more than 50 years, Dallara has designed and supplied high-performance vehicles for some of the world’s top racing series, including IndyCar as well as Formula 2, Formula 3, Super Formula, and Indy NXT, with additional work in top-tier series such as Formula E, WEC, and IMSA.

These racing programs provides ability to validate simulation results against real-world vehicle performance. Dallara also applies its engineering to high-performance road vehicles and aerospace. 

As part of the project, IBM has been developing domain-specific foundation models in close coordination with Dallara. The models leverage Dallara’s high-fidelity aerodynamic simulation data and the company’s technical expertise. Teams also aim to integrate validated measurements of real vehicles in wind tunnels and on the track.

IBM and Dallara are using AI to speed up those workflows without replacing physics. In one early example, which focused on the geometry of a conceptual Le Mans Prototype 2 (LMP2)-like race car, the two companies jointly compared CFD analyses of multiple configurations of the rear diffuser with results from the new physics-based AI method.

The traditional approach took a few hours to calculate all the configurations. Meanwhile, the AI model completed the same evaluations in about 10 seconds, identifying the same optimal design with roughly the same error margins as CFD, according to IBM and Dallara. 

These and other preliminary results suggest Dallara engineers can evaluate more vehicle configurations in a fraction of time to move faster in early design phases.

Sources: Press materials received from the company and additional information gleaned from the company’s website.