Case studies were shared of shortening development periods and reducing costs through the introduction of artificial intelligence and machine learning in automotive product design, modeling, and analysis.

Hexagon Manufacturing Intelligence, a global leader in digital reality solutions combining sensors, software, and autonomous technologies, announced on the 21st that it participated in the 2024 Korea Society of Automotive Engineers Spring Conference held at Sono Calm Geoje on the 20th and held a seminar with Hyundai Motor Company on the topic of “Virtual Development of Future Mobility Driving Performance Using Artificial Intelligence (AI) and Machine Learning (ML).”

Hosted by Hyundai Motor Company and sponsored by Hexagon, this presentation, attended by over 100 mobility experts, focused on the introduction of AI and machine learning-based predictive models into engineering processes in the automotive industry and research into improving the driving performance of future mobility.

The detailed program of the session is as follows: △Virtual development of future mobility driving performance using AI/ML △Engineering advancement using AI R&H automation tools △Integrated modeling of vehicles and e-powertrains for noise prediction and application to machine learning prediction △Prediction of radiation noise of EV drive motors using AI/ML △Real-time virtual development of PBV (Platform Beyond Vehicle) using AI/ML △Hexagon's automotive industry AI/ML research trends and consists of cases.

The research presented at the session utilized Hexagon products such as Adams, which can simulate various driving situations, Nastran, a multi-disciplinary structural analysis solution, Actran, an acoustic solution, and ODYSSEE, an artificial intelligence and machine learning platform, to develop predictive models.

Hexagon’s Adams and Odyssey were used to rapidly iterate through tolerance range changes in a variety of case studies of high-performance sports cars to optimize gearbox mechanisms that directly affect the quality and efficiency of gear shifting. Adams supports mechanism behavior review, design goal definition, and DoE (Design of Experiment). After generating a data matrix that can be used as input data in Adams, Odyssey can learn the data and predict results for new design variables according to design specifications.

In addition, Gwangsoo Yoon, team leader of the Manufacturing and Platform Team of Hexagon Manufacturing Intelligence Korea Design & Engineering Division, introduced various cutting-edge technologies and application examples, such as the global case of Odyssey utilized for crash performance prediction, the 3D-ROM function built into Hexagon's Cradle CFD solver, and CT data defect inspection using deep learning, in his presentation, 'Hexagon's AI/ML Research Trends and Cases in the Automotive Industry.'

“This joint research between Hyundai and Hexagon has once again confirmed the importance of introducing artificial intelligence and machine learning to automotive product design, modeling, and analysis,” said Yongdae Kim, Hyundai Motor Company Master, who chaired the presentation. “Through our collaboration with Hexagon, we expect to shorten Hyundai Motor Company’s virtual vehicle development period and achieve cost savings.”

“We hope that Hexagon’s solutions will be utilized in research for future mobility technology innovation,” said Sung Brian Hexagon, President of Manufacturing Intelligence Korea. “We will continue to provide support through ongoing exchanges to help domestic researchers increase productivity and efficiency in product research and development.”

Meanwhile, the Society of Automotive Engineers Spring Conference will be held from June 19th to 22nd, and the seminar titled 'Virtual Development of Future Mobility Driving Performance Using AI/ML', a specialized research presentation held during the event, was hosted by Hyundai Motor Company and sponsored by Hexagon.