Presentation: how BMW uses AI to accelerate crash tests
The use of artificial intelligence (AI) combined with historical vehicle test data is an increasingly popular solution in engineering product development and is poised to be a game-changer in the automotive industry. In his presentation, Dr. Richard Ahlfeld will discuss how BMW Group engineers adopted Monolith AI software to reduce crash test times by training self-learning models with their valuable test data to accurately predict the force on a passenger’s tibia. As a result, BMW engineers can optimise crash performance earlier and reduce time-intensive testing. Dr. Ahlfeld will touch on other areas where the Monolith no-code AI software is being adopted in automotive product development to help engineers do less physical testing and explore more design parameters and operating conditions whilst significantly cutting development time.
This event is world’s leading international expo for every aspect of automotive testing, development, and validation technologies. It is the leading event for the technologies and services in ADAS and autonomous vehicle testing, electric and hybrid powertrain testing, battery and range testing, EMI and NVH test and analysis, and the full spectrum of test and validation technologies for full-vehicle, component, and systems development.
"Using Monolith, BMW Group engineers built self-learning models using the wealth of their existing crash data and were able to accurately predict the force on the tibia for a range of different crash types without doing physical crashes."
Jota Sport cuts car setup time by 50% with Monolith AI
Since teaming up with Monolith AI, Jota engineers can better understand and predict the aerodynamics of their cars by building self-learning models. As a result, they have reduced the number of simulations and tests by 50%, cut car time-to-setup in half, and achieved a 66% reduction in overall costs.
