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.
Primary Language | English |
---|---|
Subjects | Engineering |
Journal Section | Research Articles |
Authors | |
Publication Date | December 29, 2018 |
Published in Issue | Year 2018 |
The works published in Journal of Innovative Science and Engineering (JISE) are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.