NEXEN TIRE DEVELOPS TIRE-PERFORMANCE PREDICTION SYSTEM USING A. I. TECHNOLOGY

Nexen Tire America, Inc., a worldwide leader in high-performance, passenger, SUV/light truck and winter tire technology, today announced it has developed an Artificial Intelligence (AI)-based tire-performance prediction system. Nexen Tire will use machine-learning technology in the design stage to predict tire-performance parameters more precisely and rapidly, such as fuel efficiency, noise, stopping distance and handling.

The ability to forecast tire performance early in the development process has the benefit of reducing the quantity of prototypes produced and the development time. Traditionally a method called Finite Element Analysis (FEA) has been used to build and analyze virtual 3D-tire models. With FEA, the mechanical properties can be precisely predicted through numerical calculation, but the process requires a lot of computer-processing power and can take a long time, slowing the development process. The newly developed AI-based tire-performance prediction system will allow faster and more accurate tire design and performance improvement during the design stage, adding a valuable tool to the existing FEA-based performance-prediction methods.

Nexen has vast amounts of tire data from both current and historical testing that was used to create a forecasting model with accurate predictive capabilities. However, the predictions made by the new AI-based system are only as good as the data that is input, therefore it was necessary to assure only quality data was used. To assure the integrity of the data, Nexen Tire created a data pre-processing technology that detects irregularities in the data and screens 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.”

Professor Seoung Bum Kim of Korea University and Professor Ki Chun Lee of Hanyang University collaborated on the newly created tire-performance prediction system using AI technology.