Active Control of Structure-Borne Road Noise Based on the Separation of Front and Rear Structural Road Noise Related Dynamics

Paper #:
  • 2015-01-2222

Published:
  • 2015-06-15
DOI:
  • 10.4271/2015-01-2222
Citation:
Zafeiropoulos, N., Ballatore, M., Moorhouse, A., and Mackay, A., "Active Control of Structure-Borne Road Noise Based on the Separation of Front and Rear Structural Road Noise Related Dynamics," SAE Int. J. Passeng. Cars - Mech. Syst. 8(3):886-891, 2015, doi:10.4271/2015-01-2222.
Pages:
6
Abstract:
Axle forces from tire-road interaction can excite different structural resonances of the vehicle hence a high number of sensors is required for observing and separating all the vibrations dynamics that are coherent with the cabin noise. Feed-forward road noise control strategies adopted so far rely mainly on capturing these dynamics and thus the number of sensors constitutes one major limitation of this approach.Therefore there is a necessity for reducing the number of sensors without degrading the performance of an ANC system. In the past coherence function analysis has been found to be a useful tool for optimizing the sensor location. In this case coherence function mapping was performed between an array of vibration sensors and the headrest microphones in order to identify the locations on the structure that are highly correlated with road noise bands in the compartment.A vehicle with an advanced suspension system was used for applying the method and defining some locations as reference signals for feed-forward active road noise control.Three different real-time control experiments were performed with structure-borne road noise simulated by applying broad band random forces to tires through shaker transducers. A single reference feed-forward adaptive controller evaluated the signals from each sensor location with simulated road noise excitation applied to: front wheels only, rear wheels only and whole vehicle. This way it is demonstrated that the control can be focused at specific road noise bands with a low number of sensors.
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