Speaker
Description
This study explores the effect of utilizing the Multiple Coherence Function (MCF) analyzation in optimizing reference sensors and installment positions of Active Road Noise Cancellation (ARNC) system. The ARNC system broadly consists of speakers, microphones, sensors which provide reference of noise source and electronic controller which filters the unwanted noise through algorithm. ARNC is influenced diversely in differenct frequency domains of road noise: booming noise, tire-pavement interaction noise, and rumble noise. Since a vehicle contains various systems within a limited installment space and budget, optimization of ARNC system became necessary. MCF is one of the analyzations using coherence to outstand the most referring sensors to a road noise out of others. Throughout the experiment, two different vehicles, the vehicle speeds, and the number of people loaded conditions were varied while the vehicles ran on the same testing road on each trial to observe the consistency of the result. Three-axis accelerometer sensors were attached to each wheel side, and target and error microphones were placed near the ear sites at each seat. In conclusion, the contribution of each noise source sensor in main road noise frequency domain can be evaluated by using the MCF. The MCF also allows a coherence comparison between reference noise source sensors and the effect of combination of those sensors. It suggests that the closer the sensors are to the cabin, the higher the contribution level of providing the reference of the road noise source. Furthermore, it suggests at least two sensors in opposite locations to strengthen the contribution.