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  • Summary & Details

Target Cascading of Tire Performances Using Machine Learning

Detailed Information

Author(J)1) Yeonsang Yoo, 2) Benjamin Schäfer, 3) Yongdae Kim, 4) Jinsil Kyeong
Author(E)1) Yeonsang Yoo, 2) Benjamin Schäfer, 3) Yongdae Kim, 4) Jinsil Kyeong
Affiliation(J)1) Hyundai Motor, 2) RWTH Aachen University, 3) Hyundai Motor, 4) Hyundai Motor
Affiliation(E)1) Hyundai Motor, 2) RWTH Aachen University, 3) Hyundai Motor, 4) Hyundai Motor
Abstract(E)The automotive industry is shifting towards Model-Based Systems Engineering (MBSE) to manage increasing complexity in development. However, virtual tire development has a significant limitation: setting tire performance targets in early stage is difficult without physical testing. To overcome this situation, this study proposes a Target Cascading (T/C) process to derive tire performance targets directly from vehicle performance requirements and validated the process. Previously developed performance prediction models were improved for refined T/C process. Additionally, a GUI was developed to integrate the prediction models and T/C process for user convenience.

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