Low Noise Optimization of Automotive Air Conditioning Based on Response Surface Methodology

Abstract

Air conditioning is an important contributor to in-vehicle noise. In order to achieve low noise optimization, investigations were performed in a typical air conditioning unit. Computational fluid dynamics and computational aeroacoustics were combined to simulate the noise characteristics. Steady and transient simulations were conducted to identify noise sources, revealing that the dipole noise is mainly distributed on the fan blades and the volute tongue, and the fan contributes more significantly to the far-field noise. Based on the response surface methodology (RSM), three key structural parameters of the fan-volute tongue clearance, volute tongue radius, and blade outlet angle were selected as design variables, while the far-field A-weighted sound pressure level (SPL) was set as the response index. The final optimization parameter are: volute tongue clearance of 13.36 mm, volute tongue radius of 11.83 mm, and blade outlet angle of 110○. The far-field SPL is reduced from 61.8 dB to 55.5 dB, with a relative reduction of 10.2%. This research validates the effectiveness and reliability of the proposed method, providing an efficient and systematic technical reference for the noise reduction design of automotive air conditioning systems.