Noise testing of series of 30 truck tyres succesful
After months of intensive work we are happy that our project results have been accepted by the client, a consortium of the transport ministries of Norway, Sweden, Finland and Denmark. In total 8.000 pass-by signals are recorded of a series of 30 truck tyres rolling over four different test surfaces at speeds ranging from 40 to 80 km/h. The acoustic performances are assessed with 19.000 regression functions and outcomes are stored in a structured data-base for further analysis.
In 2014 our research proposal, made together with SINTEF of Norway, was awarded with a contract. It was agreed to select 30 truck tyres representative for the Scandinavian truck fleet. These include special arctic tyres, mandatory during the winter season and retreaded tyres. The acoustic performance of these tyres was tested under coasting conditions and with a representative load of about 75% of the nominal load.
The objective of the study was three fold:
- study the relation between the tyre noise label value and the results of actual tests done according to UN/ECE R117;
- understand the representativity of the test results on the ISO 10844 surface for rolling noise on much coarser real roads;
- identify tonal components in the rolling noise signal that might be extra annoying in the environment.
The total produced data set consists of LAFmax and SEL values at a height of 1,2 and 3,0 m at speeds ranging from 40 to 80 km/h. Four test surfaces were used: ISO 10844, SMA11, TSL8 and AC16. Results are expressed in both overall and 1/3rd octave band values. Tonal components are identified on base of narrow band CPX signals.
The relevant acoustic properties of the tested tyres and the road surfaces are assessed in great detail on base of mechanical and acoustic impedance testing, profile and texture scanning and additional parameters.
Not only could we respond succesful to the research objectives but the extended and well-structured data set is a valuable source for tyre/road interaction modelling and enables addressing a wide range of what-if questions. First results were presented at Euronoise2015.