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Understanding the contribution of groove resonance to tire-road noise on different surfaces under various operating conditions

Pinay, Julien; Saito, Yoshinori; Mignot, Christian; Gauterin, Frank

Reducing tire-road noise is now becoming more and more important during the tire development process. Tread profile randomization is used to avoid tonal components and reduce groove resonance noise. To better understand the groove resonance contribution to tire-road noise, we performed acoustic measurements on a test bench with two serial tires. We filled the grooves with acoustic foam to highlight the groove resonance’s contribution. We then varied the road surface, the tire load and the driving speed. In the end, we used a multiple linear regression to quantify the interaction between the varying parameters and the groove resonance noise. We show that groove resonance contributes an average of 1.7 dBA to the tire rolling noise of passenger car tires. Groove resonance noise also increases with the driving speed. While the tread pattern and the tire load are responsible for the spectral content of the groove resonance noise, the orientation of the road surface’s texture mainly influences the noise level of the groove resonance. The tire manufacturers should carefully consider these findings when developing noise-optimized patterns. This is especially true for tire approval tests, which take place on tracks and usually have a relatively low texture level that is oriented negatively.

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Verlagsausgabe §
DOI: 10.5445/IR/1000121421
Veröffentlicht am 17.07.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Fahrzeugsystemtechnik (FAST)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 2681-4617
KITopen-ID: 1000121421
Erschienen in Acta Acustica
Band 4
Heft 2
Seiten Article: 6
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Vorab online veröffentlicht am 12.05.2020
Schlagwörter Tire road noise; Groove resonance; Regression; Pavement; Experimental method
Nachgewiesen in Web of Science
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