Vehicular Cabin Noise Source Identification and Optimization Using Beamforming and Acoustical Holography

The automobile market is witnessing a different trend altogether - the trend of shifting preference from powerful to fuel efficient machines. Certain factors like growing prices of fuel, struggling global economy, environmental sensitiveness and affordability have pushed the focus on smaller, efficient and cleaner automobiles. To meet such requirements, the automobile manufacturers, are going stringent on vehicle weights. Using electric and hybrid power-plants are other options to meet higher fuel efficiency and emission requirements but significant cost of these technologies have kept their growth restricted to only few makers and to only few regions of the globe. Optimizing the vehicle weight is a more attractive option for makers as it promises lesser time to market, is low on investment and allows use of existing platforms. However, lightweighting and NVH often conflict each other in vehicle development and hence design optimization plays a vital role in assigning a tradeoff between the lightweighting and NVH.

The paper seeks to use noise source identification systems like Spherical Beamforming and Acoustical Holography to identify the major engine noise radiating zones in the dash silencer and develop a methodology to optimize the design of the sound package in a way that is low on weight yet delivers superior insulation performance.