In a new development, Nexen Tire America, Inc., announced that it has developed a new AI-based tire performance prediction system. The system employs machine learning in the design stage to preempt performance parameters more quickly and precisely. This includes parameters such as noise, handling, fuel efficiency, and stopping distance.
Nexen tire is currently a world leader in the development and production of high-performance, winter, SUV/light truck, and passenger tire technology. The ability to predict parameters in the development stage will help reduce the number of prototypes needed.
The company previously used a 3D-based method called Finite Element Analysis (FEA). This can be used to predict mechanical properties, but with much more computer processing power as it is based on numerical calculations. It also takes a long time and slows down development.
The new AI system will facilitate faster and more accurate performance and design improvements. This will add value to the FEA-based prediction method. Nexen Tire already has plenty of data from historical and current testing. This will help create models with accurate predictive capabilities.
The data must be accurate, as its integrity determines how well the AI system works. Nexen has data pre-processing technology that helps to identify irregularities and screen them out.
“We aim to finalize the development of the ‘Virtual Brain Loop System,’ a tire-development system based on our own virtual design technology, and apply it to OE and RE tires,” said Seong Rae Kim, Researcher of THE NEXEN univerCITY, Nexen Tire’s central R&D Institute. “Through combined industry-academic research, we intend to increase talent training and R&D skills.”