DEVELOPMENT OF INDOOR TEST METHOD FOR PASSENGER CAR TIRES REFLECTING ROAD DRIVING CONDITIONS

다국어 초록 (Multilingual 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 tovehicle speed and acceleration changes are estimated. Reduced data representing the estimated data are calculated using apeak–valley (PV) algorithm. Through the blocking process, representative test modes for driving and braking, right turningand left turning are derived and converted into a test mode for application to the Flat-trac. The evolution of tire tread wearis observed through 120 repeated tests, and the applicability of the test mode developed in this study is discussed.

참고문헌 (Reference)

1 서영기 ; 곽성우 ; 이재천 ; 이호승 ; Liu, Hao ; 조해준 ; 박상수 ; 이은진, "Vehicle load measurement using tire deformation values" 28 (28): 170-176, 2018

2 Stalnaker, D., "Vehicle and course characterization process for indoor tire wear simulation" 30 (30): 100-121, 2002

3 Wilkin, M., "Use of an extended Kalman fi lter as a robust tyre force estimator" 44 (44): 50-59, 2006

4 UN, "UNECE Regulation No. 30, uniform provisions concerning the approval of pneumatic tyres for motor vehicles and their trailers"

5 서영기 ; 곽성우 ; 양정민, "Tire speed measurement using strain gauge sensor" 13 (13): 376-382, 2021

6 Jeong, D., "Tire load estimation using intelligent tire with accelerometer" 6-9, 2018

7 Pacejka, H., "The magic formula tyre model" 21 (21): 1-18, 1992

8 정성필 ; 조준희, "Test method of rolling resistance of a tire considering cornering condition" 26 (26): 736-744, 2018

9 Matsuzaki, R., "Strain monitoring and applied load estimation for the development of intelligent tires using a single wireless CCD camera" 6 (6): 935-949, 2012

10 Quddus, M., "Shortest path and vehicle trajectory aided map-matching for low frequency GPS data" 55 : 328-339, 2015

11 Scikit-learn, "Regression"

12 Jian, K., "Real-time estimation and prediction of tire forces using digital map for driving risk assessment" 107 : 463-489, 2019

13 Smith, K., "Prediction of tire profi le wear by steady-state FEM" 36 (36): 290-303, 2008

14 Snoek, J., "Practical Bayesian optimization of machine learning algorithms" 25 : 1-9, 2012

15 Nopiah, Z., "Peakvalley segmentation algorithm for fatigue time series data" 7 (7): 698-707, 2008

16 Ray, L., "Nonlinear tire force estimation and road friction identification : Simulation and experiments" 33 (33): 1819-1833, 1997

17 Herbert, A., "Load program development and testing of super single wheels in the biaxle wheel test rig and numerical pre-design" SAE 2004

18 Gultlinger, J., "Investigations of road wear caused by studded tires" 42 (42): 2-15, 2014

19 Stalnaker, D., "Indoor simulation of tire wear : Some case studies" 24 (24): 94-118, 1996

20 ISO, "ISO 28580:2009(E), Passenger car, truck and bus tyres - methods of measuring rolling resistance - single point test and correlation of measurement results"

21 Gipser, M., "FTire : A physically based application-oriented tyre model for use with detailed MBS and fi nite-element suspension models" 43 (43): 76-91, 2005

22 Nurkala, L., "Development of the SAE biaxial wheel test load file" SAE 2004

23 Gadola, M., "Development and validation of a Kalman fi lter-based model for vehicle slip angle estimation" 52 (52): 68-84, 2014

24 Singh, K., "Accelerometer based method for tire load and slip angle estimation" 2 : 174-186, 2019

25 "AIR5797. Aircraft tire wear profi le development and execution for laboratory testing"

26 Mathissen, M., "A novel real-world braking cycle for studying brake wear particle emissions" 414–415 : 219-226, 2018

27 Knisley, S., "A correlation between rolling tire contact friction energy and indoor tread wear" 30 (30): 83-89, 2002