International Journal of Automotive Technology. 2024; 25(2): 413-425.
Development of Indoor Wear Test Method for Passenger Car Tires Refl ecting Road Driving Conditions
Korea Automotive Technology Institute
ABSTRACT
This study presents a method for developing a tire indoor wear test mode that refl ects road driving conditions using a Flattrac.
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.
Keywords :
Tire test mode · Flat-trac · Machine learning · Peak–valley algorithm · Wear
