Investigation and improvement of vehicle A/C system compressor noise by 6sigma approach

• Main Author: Mehdi YILDIZ
• Format: Article
• Language: English
• Published: Bursa Technical University 2018-12-01
• Series: Journal of Innovative Science and Engineering
• Subjects: air conditioning compressor; structural- borne noise; airborne noise
• Online Access: http://jise.btu.edu.tr/tr/download/article-file/609634

Recent developments on the vehicle engine noise show that tonal sounds such as a compressor noise is audible if its sound is 7-9dB higher than level of masking noise. Therefore, the acoustic performance of air-condition (A/C) compressors becomes more important for passenger comfort during engine idling and run up. The air conditioning system compressor noise is transmitted to interior cabin in both air-borne paths and structure-borne paths of the compressor pipes. The compressor is driven by the engine and it has also a high interaction with the other components of the system such as Expansion Valve (TXV), Electric cooling fan, Condenser and Evaporator. Therefore, to make a proper NVH design of the air conditioning system in terms of customer satisfaction, it is necessary to consider all these interactions when determining the type of compressor. In this study, the noise problem induced by the A/C system compressor was investigated by Six Sigma approach to determine solution alternatives. The air conditioning system was examined in detail as a cooling process in order to determine individual factors of each system components affecting the compressor noise issue. The most important factors are defined by Cause and Effect matrix to simplify the working model. The effect of each factor/input on internal noise level was measured with the microphones and accelerometers based on the pressure increase in the A/C system. A correlation analysis is performed between these factors/inputs and interior noise level to define high correlated factors of each system component. Besides, a regression analysis is performed to identify the compressor noise generation model (equation describing the noise model) based on these highly correlated factors. A series of experiments is designed (DOE) on these regression model to find out the optimum solution to improve compressor noise problem perceived in the vehicle cabin.