Abstract
This study presents a method for developing a tire indoor wear test mode that reflects road driving conditions using a Flat-trac. Using a machine learning model, the slip angle, slip ratio, longitudinal force, and lateral force change according to vehicle speed and acceleration changes are estimated. Reduced data representing the estimated data are calculated using a peak–valley (PV) algorithm. Through the blocking process, representative test modes for driving and braking, right turning and left turning are derived and converted into a test mode for application to the Flat-trac. The evolution of tire tread wear is observed through 120 repeated tests, and the applicability of the test mode developed in this study is discussed.
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The data that support the findings of this study are not available due to manufacturer's request.
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Acknowledgements
This study was supported by the Ministry of Trade, Industry, and Energy and the Korea Evaluation Institute of Industrial Technology (KEIT) in 2021 (20015841, sustainable material-based eco-friendly tire-manufacturing technology development).
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Jung, S., Lee, J. Development of Indoor Wear Test Method for Passenger Car Tires Reflecting Road Driving Conditions. Int.J Automot. Technol. 25, 413–425 (2024). https://doi.org/10.1007/s12239-024-00034-6
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DOI: https://doi.org/10.1007/s12239-024-00034-6