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Squeak and rattle (S&R) problems in body structure and trim parts have become serious issues for automakers because of their influence on the initial quality perception of consumers. In this study, various CAE and experimental methods developed by Hyundai Motors for squeak and rattle analysis of door systems are reported. Friction-induced vibration and noise generation mechanisms of a door system are studied by an intelligent combination of experimental and numerical methods. It is shown that the effect of degradation of plastics used in door trims can be estimated by a numerical model using the properties obtained experimentally. Effects of changes in material properties such as Young's modulus and loss factor due to the material degradation as well as statistical variations are predicted for several door system configurations. As a new concept, the rattle and squeak index is proposed, which can be used to guide the design.

Design optimization of a vehicle is required to increase a product value for noise and vibration performances and for a fuel-efficient car. This paper describes the development process of a high stiffness and lightweight vehicle. A parameter study is carried out at the initial stage of design using the mother car, and a design guide with a good performance is achieved early prior to the development of the proto car. Influences of body stiffness based on the relative weight ratio of the floor and side structures are analyzed. Results show that bending and torsional stiffness has a significant effect on weight distribution ratio. Influences of the distribution of side joint stiffness are analyzed through numerical experiments. Results reveal that the stiffness difference between the upper and lower parts should be small to increase the stiffness of a body.

With the recent development of technologies for interpreting vibration and noise of vehicles, it has become possible for carmakers to reduce idle vibration and driving noise in the phase of preceding development. Thus, the issue of noise generation is drawing keen attention from production of prototype car through mass-production development. J. D. Power has surveyed the levels of customer satisfaction with all vehicles sold in the U.S. market and released the Initial Quality Study (IQS) index. As a growing number of emotional quality-related items are added to the IQS evaluation index, it is necessary to secure a sufficiently high quality level of low-frequency speaker sound against rattle noise. It is required to make a preceding review on the package tray panel, which is located at the bottom of the rear glass where the woofer speakers of a passenger sedan are installed, the door module panel in which the door speakers are built.

The analytic wavelet transform (AWT) is a wavelet transform that works much like a transient Fourier transform. Therefore the AWT enables utilizing advantages of both the wavelet transform and Fourier transform. A special form of AWT developed for transient vibration and acoustics signal analyses is applied to various engineering signals in this paper. Application examples include a general time-frequency (T-F) analysis, analysis of exposures to impulsive vibrations and noises, and estimation of reverberation times. Some new definitions such as the T-F noise reduction and frequency weighted time history are defined by taking the advantage of unique capabilities of the AWT. Possible automotive applications of these new concepts are briefly discussed.

In highly transient sounds, time and frequency components are highly dependent of each other. A time-frequency (T-F) analysis is necessary for such signals. The wavelet transform is a T-F signal analysis algorithm which uses variable scales to satisfy both time and frequency resolution requirements more effectively. The analytic wavelet transform (AWT) is a wavelet transform that retains most of the basic features of the Fourier transform. We developed a form of AWT specifically made for acoustics applications. The method obtains the amplitude as well as phase of the sound signal as the Fourier transform does, however in the transient sense. Advantages of the method over the short time Fourier transform method, a commonly used Fourier transform based transient signal analysis method, are demonstrated using two impulsive signals as examples.

Two potential applications of a dynamic stiffness matrix (DSM) based direct damping matrix identification method are presented in this paper. The method was proposed to identify both the mechanism and spatial distribution of damping as a matrix of general function of frequency. First potential application is the analytical-experimental hybrid structural dynamics modeling, in which the model is constructed by combining analytically formulated mass and stiffness matrices with the experimentally identified damping matrix. Second application is the direct measurement of complex shear modulus of viscoleastic materials. The real and imaginary parts of the dynamic stiffness measured on a test setup that resembles a single degree of freedom system is used to compute the shear modulus and the loss factor of viscoelastic materials.

This paper is intended to describe some of the advances in automotive NVH research and applications based on recent developments in the Structural Dynamics Research Laboratory (SDRL) at the University of Cincinnati. State-of-the-art vibro-acoustic research capabilities and infrastructure ranging from advanced vibration modal analysis and spectral techniques for linear and nonlinear automotive systems to computational tools for structure-borne acoustic noise generation, transmission and synthesis problems are discussed. These systems have been devised with the intent of integrating a versatile set of experimental, computational and analytical approaches in order to be able to investigate a variety of crucial automotive NVH concerns. The materials will be grouped into three separate but closely related sets of applications consisting of (i) powertrain noise and vibration control, (ii) analysis and control vehicle system dynamics, and (iii) NVH and sound quality.

A new algorithm to detect and to quantify the seriousness of the detected squeak and rattle (S&R) events was developed. A T-F analysis technique called AWT, the Zwicker loudness model and leaky integration are employed to define new concepts we called transient specific loudness time histories and perceived transient loudness time history. The detection threshold of the perceived transient loudness was identified by a clever interpretation of jury test results. The proposed algorithm showed a good promise producing results that are well correlated with the jury tests. The new algorithm developed in this work will be able to automate detection and rating of the S&R events with good accuracy and with minimum possibility of false alarm under normal operating conditions

Squeak and rattle (S&R) noises are undesirable noises caused by friction-induced vibration or impact between surfaces. While several computer programs have been developed to automatically detect and rate S&R events over the years, no reported work has been found that can detect squeak and rattle noises and distinguish them. Because the causes of squeak noises and rattle noises are different, knowing if it is a squeak noise or rattle noise will be very helpful for automotive engineers to choose an appropriate measure to solve the problem. The authors have developed a new algorithm to differentiate squeak noises and rattle noises, and added it to the S&R detection algorithm they had developed previously. The new algorithm utilizes a combination of sound quality metrics, specifically sharpness, roughness, and fluctuation strength.

Theoretical development of a dynamic stiffness matrix (DSM) based direct damping matrix identification method is revisited in this paper. This method was proposed to identify both the mechanism and spatial distribution of damping in dynamic structures as a matrix of general function of frequency. The objective of this paper, in addition to the review of the theoretical development, is to investigate some major issues regarding the feasibility of this method. The first issue investigated is how the errors in measured frequency response functions (FRF) affect the accuracy of the DSM. It was already known that the DSM is highly sensitive to errors that are present in the FRF. A detailed analytical and computational study is conducted, which finally leads to a sound physical explanation of the high sensitivity of the DSM to measurement errors. A new and also important conclusion is that the leakage error drastically affects the accuracy of the computed DSM.

It is common knowledge that body structure is an important factor of road noise performance. Thus, a high stiffness of body system is required, and determining their optimized stiffness and structure is necessary. Therefore, a method for improving body stiffness and validating the relationship between stiffness and road noise through CAE and experimental trials was tested. Furthermore, a guideline for optimizing body structure for road noise performance was suggested.