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Assessment and Monitoring of Tyre Wear Testing
HELSINKI2002/F02I042

Authors

Halén, Ismo - Helsinki University of Technology
Sainio, Panu - Helsinki University of Technology
Lehtonen, Tero - Helsinki University of Technology

Abstract

Tyre and road wearing has been researched in the European Commission research project called TROWS (Tyre and Road Wear and Slip assessment). The objective of the project is to gain insight into the tyre and road wear processes in order to reduce both tyre and road wear.

One of the subtasks is to monitor and record data of driving situations that test vehicles will experience during test route. Tests are performed with two passenger cars and with heavy truck and trailer. This data will be used to evaluate aggressiveness of different test sections and drivers behavior in wear testing. Test route is 131 km long and includes different types of roads from minor roads in industrial area up to main highways and mountain sections. Test route is located in Italy.

By recording several parameters like accelerations, speed, traction force and GPS-location it is possible to have information of aggressiveness of different sections of test route with respect of forces present in tyre road interaction. Presenting vehicle data in function of distance (location) makes it possible to link it with data of road pavement characteristic.

Distribution of speed, accelerations etc. used during testing can be utilized for simulation, statistical research and to determine testing parameters for rubber material in laboratory testing. Also from point of view of road pavements, locations and distribution of forces generated by vehicles are interested. Wear testing carried out in normal roads includes also effect of driving style and traffic density. These parameters can be evaluated with some accuracy by recording GPS data.

In presentation test methods are described and there will be discussion of using this data to estimate forces generated in the tyre road interaction during lifetime of tyre and connecting this data with road pavement data based on known location.

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