AUTOMOTIVE EXTERIOR NOISE OPTIMIZATION USING GREY RELATIONAL ANALYSIS COUPLED WITH PRINCIPAL COMPONENT ANALYSIS

This paper investigates optimization design of the thickness of the sound package performed on a passenger automobile. The major characteristics indexes for performance selected to evaluate the processes are the SPL of the exterior noise and the weight of the sound package, and the corresponding parameters of the sound package are the thickness of the glass wool with aluminum foil for the first layer, the thickness of the glass fiber for the second layer, and the thickness of the PE foam for the third layer. In this paper, the process is fundamentally with multiple performances, thus, the grey relational analysis that utilizes grey relational grade as performance index is especially employed to determine the optimal combination of the thickness of the different layers for the designed sound package. Additionally, in order to evaluate the weighting values corresponding to various performance characteristics, the principal component analysis is used to show their relative importance properly and objectively. The results of the confirmation experiments uncover that grey relational analysis coupled with principal analysis methods can successfully be applied to find the optimal combination of the thickness for each layer of the sound package material. Therefore, the presented method can be an effective tool to improve the vehicle exterior noise and lower the weight of the sound package. In addition, it will also be helpful for other applications in the automotive industry, such as the First Automobile Works in China, Changan Automobile in China, etc.

[1]  Zou Li-hua,et al.  Grey forecasting model for active vibration control systems , 2009 .

[2]  N. Z. Al-Mutairi,et al.  Traffic-generated noise pollution: exposure of road users and populations in Metropolitan Kuwait , 2011, Environmental monitoring and assessment.

[3]  Victor R. L. Shen,et al.  A novel application of grey system theory to information security (Part I) , 2009, Comput. Stand. Interfaces.

[4]  Yong-Huang Lin,et al.  Practical expert diagnosis model based on the grey relational analysis technique , 2009, Expert Syst. Appl..

[5]  Suhas S. Joshi,et al.  Multi-objective optimization of surface roughness and cutting forces in high-speed turning of Inconel 718 using Taguchi grey relational analysis (TGRA) , 2011 .

[6]  Won Tae Kwon,et al.  Optimization of EDM process for multiple performance characteristics using Taguchi method and Grey relational analysis , 2010 .

[7]  Deng Ju-Long,et al.  Control problems of grey systems , 1982 .

[8]  A. Noorul Haq,et al.  Optimizing the weld bead characteristics of super austenitic stainless steel (904L) through grey‐based Taguchi method , 2010 .

[9]  T. Senthilvelan,et al.  Multi-response optimization of machining parameters in hot turning using grey analysis , 2011 .

[10]  Yoshihiro Noguchi,et al.  Development of a Lightweight Sound Package for 2006 Brand-New Vehicle Categorized as C , 2006 .

[11]  Chitra Sharma,et al.  Optimisation of electrical discharge machining process with CuW powder metallurgy electrode using grey relation theory , 2011 .

[12]  Douglas B. Moore.  The Revised ISO 362 Standard for Vehicle Exterior Noise Measurement , 2006 .

[13]  N. C. Hwang,et al.  Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling , 2009 .

[14]  Anne Vernez Moudon,et al.  Real noise from the urban environment: how ambient community noise affects health and what can be done about it. , 2009, American journal of preventive medicine.

[15]  H. Doygun,et al.  Analysing and mapping spatial and temporal dynamics of urban traffic noise pollution: a case study in Kahramanmaraş, Turkey , 2008, Environmental monitoring and assessment.

[16]  Jerome E. Manning.  Statistical Energy Analysis , 2008 .

[17]  Shuming Chen,et al.  Research on prediction and control method of car exterior noise , 2012 .

[18]  Chi-Chuan Wang,et al.  Analysis of a 50 kW organic Rankine cycle system , 2011 .

[19]  C. Fung,et al.  Multi-response optimization in friction properties of PBT composites using Taguchi method and principle component analysis , 2005 .

[20]  Wei Liu,et al.  Use of SEA to Support Sound Package Design Studies and Vehicle Target Setting , 2009 .

[21]  Ming-Jong Tsai,et al.  Multi-objective optimization of laser cutting for flash memory modules with special shapes using grey relational analysis , 2009 .

[22]  Richard H. Lyon.  Statistical energy analysis of dynamical systems : theory and applications , 2003 .

[23]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[24]  Arshad Noor Siddiquee,et al.  Feasibility study of use of recycled High Density Polyethylene and multi response optimization of injection moulding parameters using combined grey relational and principal component analyses , 2010 .

[25]  Jens Forssén,et al.  Modelling the interior sound field of a railway vehicle using statistical energy analysis , 2012 .

[26]  Shuming Chen.  Statistical Energy Analysis Method for Car Exterior Noise Prediction , 2010 .

[27]  Takeo Hashimoto.  Sound quality approach on vehicle interior and exterior noise. Quantification of frequency related attributes and impulsiveness. , 2000 .

[28]  Gösta Leon Bluhm,et al.  Road traffic noise and hypertension , 2006, Occupational and Environmental Medicine.

[29]  Jeong Chang Seong,et al.  Spatio-temporal patterns of road traffic noise pollution in Karachi, Pakistan. , 2011, Environment international.

[30]  Mohamed Ichchou,et al.  Dynamic analysis of an automobile floorpan using a hybrid approach of the finite element method and statistical energy analysis , 2008 .