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In automotive infotainment systems, multiple types of digital audio signals are usually present. Some come from internal sources, such as a CD or USB stick, and some come from external sources, such as an internet stream or digital radio. These sources usually have different sample-rates, and may also be different from one or more system sample-rates. Managing and transporting these signals throughout the system over different sample-rate domains require detailed upfront architecture analysis and correct system design to ensure signal quality is maintained to the desired level. Incorrect design can add significant user-perceivable noise and distortion. This paper examines the key analysis factors, the effects of poor design and the approaches for achieving robust signal handling and ensuring desired signal quality.

In this paper, an analytical procedure for prediction of shell radiated noise of air induction systems (AIS) due to engine acoustic excitation, without a prototype and physical measurement, is presented. A set of modeling and simulation techniques are introduced to address the challenges to the analytical radiated noise prediction of AIS products. A filter seal model is developed to simulate the unique nonlinear stiffness and damping properties of air cleaner boxes. A finite element model (FEM) of the AIS assembly is established by incorporating the AIS structure, the proposed filter seal model and its acoustic cavity model. The coupled acoustic-structural FEM of the AIS assembly is then employed to compute the velocity frequency response of the AIS structure with respect to the air-borne acoustic excitations.

Flow noise from automotive HVAC (Heating, Ventilating and Air Conditioning) systems is one of the major considerations of occupant comfort. The noise generated at high blower speed is a major contributor to the vehicle interior noise. This paper reviews automotive HVAC air rush noise prediction models for estimating register, buck (air handling subsystem) and vehicle noise levels. The vehicle noise prediction method correlates well with measured noise levels at driver right ear location: with a standard deviation of 1.31 dB where standard deviation is the difference between measured and predicted noise levels for a sample size of 10 vehicles.

A frequency domain substructure method is employed for deriving the motion transmissibility equation on a coupled structure. Various errors in its experimental implementation are investigated by numerical calculations in order to identify the most important source of errors so that future effort can be more focused. The interfaces with and without the tangential and rotational DOF's are taken into account when the DOF deficiency error is studied. By decomposing the DOF deficiency error into different components, it is shown that all six interfacial DOF's must be taken into account for general structures. The bias, noise, and underflow errors are investigated and their relative importance is compared with the DOF-deficiency error. It reveals that these three errors are moderate in nature and can be handled with traditional methods while there is no simple way to compensate for the DOF deficiency error.

The sound field in a vehicle is one of the most complex environments being a mixture of multiple, correlated and uncorrelated sound sources. The simulation of vehicle interior sound has traditionally been produced by combining multiple test results where the influence of one source is enhanced while the other sources are suppressed, such as towing the vehicle on a rough surface for road noise, or measuring noise in a wind tunnel. Such methods are costly and provide inherent inaccuracies due to source contamination and lack of synchronization between sources. In addition they preclude the addition of analytical predictions into the simulation. The authors propose an alternative approach in which the component sounds are decomposed or separated from a single operating measurement and which provide the basis for accurate sound synthesis.

The quietness of the interior of automobiles is perceived by consumers as a measure of quality and luxury. Great strides have been achieved in isolating interiors from noise sources. As noise is reduced, in particular wind and power train noise, other noise sources become evident. Noise reduction efforts are now focused on components like power steering pumps. To understand the contribution of power steering pumps a world-class noise and vibration test stand was developed. This paper describes the development of the test stand as well as it's objective to understand and improve the sound quality of power steering pumps.

Brake groan noise and vibration occurs in a stopped vehicle by the simultaneous application of torque to the wheel and the gradual release of brake pressure. Eventually the torque load breaks the friction between pad and rotor causing slippage and energy release. If the torque load is not large enough to maintain slippage, a sustained stick-slip vibration, called groan, can occur which transmits a low frequency noise to the vehicle interior. In some cases the noise levels caused by groan can be objectionable, thus procedures for developing remedial designs are needed. To this end, a project was performed to analytically simulate groan vibration in a vehicle with a McPherson strut type suspension. The goal was to demonstrate that analytical models could be used to simulate groan behavior and to identify suspension components that affect the groan behavior. The ADAMS software was used to model a brake/suspension system.

Many structures of practical interest exhibit a significant degree of nonlinearity. In such cases, the modal frequencies, damping, and amplitudes will change depending upon the excitation force level, response level and spectrum shape. When reporting the measured modal parameters from an artificial excitation test, the excitation conditions and response levels should be specified, and different modal models may be needed to represent the structural dynamics at different response amplitude levels. If the frequency responses are measured by moving accelerometers in multiple test runs, then it is important to maintain a consistent response level for all test runs. This paper describes a method to eliminate the variability of the response level between data sets by means of closed-loop control of the RMS level. The amplitude control program uses a nonlinear gain estimation technique to set the gain on a “proportional-integral” controller.

Many analytical approaches have been proposed in the literatures to evaluate the brake squeal dynamics, the complex eigenvalue approach probably being the most popular. Although this method is generally accepted, it suffers from several drawbacks. One is that the analysis does not provide a clear indication of the squeal mechanism. Another is that the predictions are sensitive to slight changes to the system model. For this reason, a variation of the complex eigenvalue approach has been developed that is more robust and provides insight into the squeal mechanism. In this paper, the new method is used to identify the types of modal coupling mechanisms that lead to squeal. Based on this investigation, the authors present three different types of mode coupling conditions that cause squeal.

Analytical methods are used extensively in the automotive industry to validate the feasibility of component and assembly designs and their dynamic behavior. Correlation of analytical models with test data is an important step in this process. This paper discusses the Finite Element model of an innovative Slip-in-Tube Propshaft design. The Slip-in-Tube joint (slip joint) poses challenges for its dynamic simulation. This paper discusses the methods of simulating the joint and correlating it to experimental results. Also, the Noise and Vibration (NVH) characteristics of the Slip-in-Tube Propshaft design. In this paper, a Finite Element model of the proposed propshaft is developed using shell and beam element formulations. Each model is verified to optimize the feasibility of using accurate and computationally efficient elements for the dynamic analysis.

Reliable prediction of the radiated noise due to the air pressure pulsation inside air-intake manifolds (AIM) is of significant interest in the automotive industry. A practical methodology to model plastic AIMs and a prediction process to compute the radiated noise are presented in this paper. The measured pressure at the engine inlet valve of an AIM is applied as excitation on an acoustic boundary element model of the AIM in order to perform a frequency response analysis. The measured air pressure pulsation is obtained in the crank-angle domain. This pressure is read into MATLAB and transformed into the frequency domain using the fast Fourier transform. The normal modes of the structure are computed in ABAQUS and a coupled analysis in SYSNOISE is launched to couple the boundary element model and the finite element model of the structure. The computed surface vibration constitutes the excitation for an acoustic uncoupled boundary element analysis.

The present work demonstrates the application of Design of Experiments (DOE) statistical methods to the design and optimization of a hydraulic steering pump for NVH performance. DOE methods were applied to RPM-domain data to examine the effect of several different factors, as well as the interactions between these factors, on pump NVH. Whereas most DOE analyses typically consider only a single response variable, the present work considered multiple response variables. Specifically, pump NVH performance curves for several pump rotational orders over a range of shaft speeds were analyzed. Thus, it was possible to determine the effect of the factors in question over the entire speed range of pump operation, rather than a single speed or setting. Statistical methods were applied to determine which factors and interactions had a significant effect on pump NVH. These factors were used to construct an empirical mathematical prediction model for NVH performance.

Induction noise, which radiates from the open end of the engine air induction system, can be of significant importance in reducing vehicle interior noise and tuning the interior sound to meet customer expectations. This makes understanding the source noise critical to the development of the air induction system and the vehicle interior sound quality. Given the ever-decreasing development times, it is highly desirable to use computer-aided engineering (CAE) tools to accelerate this process. Many tools are available to simulate induction noise or, more generally, duct acoustics. The tools vary in degrees of complexity and inherent assumptions. Three-dimensional tools will account for the most general of geometries. However, it is also possible to model the duct acoustics with quasi-three-dimensional or one-dimensional tools, which may be faster as well.

Identification of vibration transfer paths is critical to proper isolation of vibration excitations from becoming objectionable noise in a vehicle. Traditional transfer path methods involve comparing vibration inputs to the outputs of each joint. This method can be time consuming and inefficient due to a complexity of paths. A new statistical method was developed to improve the efficiency of testing. This method requires the measurement of the excitation vibration input at each joint of the source component and response sound measurements in the vehicle. Identification of transfer paths using regression analysis will determine the trouble paths to scrutinize.

The present work demonstrates the application of Design of Experiments (DOE) statistical methods to the design and the improvement of a hydraulic steering pump noise, vibration, and harshness (NVH) performance in relief. DOE methods were applied to subjective ratings to examine the effect of several different factors, as well as the interactions between these factors on pump relief NVH. Specifically, the DOE was applied to the geometry of the cross ports on a hydraulic relief valve to improve “whistle” noise in the pump. Statistical methods were applied to determine which factors and interactions had a significant effect on pump whistle. These factors were used to produce a more robust cross port configuration reducing whistle noise. Lastly, the final configuration was experimentally verified on the test apparatus and subjectively confirmed in vehicle-level testing.

Engine air induction noise can play a significant role in the reduction of vehicle interior noise levels and tuning interior sound quality. Given the need to reduce prototyping and testing costs, it is important to gain an understanding of the level and frequency structure of the noise radiating from the open inlet of the air induction system. Engine simulation used independently can predict inlet noise; however, its utility is limited to systems that are largely one-dimensional. Systems that exhibit a three-dimensional nature, such as the wave dynamics in an engine air cleaner, require a more intensive approach. Boundary Element Analysis (BEA) has been demonstrated to be a tool that can be used to predict the frequency response of ducted systems and is particularly useful in highly three-dimensional systems.

The quest to simulate noise problems has led to the building of larger and more detailed finite element models in order to perform vibration solutions to higher frequencies. This leads to the building of solid finite element models of complex geometries, such as castings, which might previously have contained less detail or even been built with shell elements. Unfortunately, detailed geometric representations used to build models do not always agree with as built parts and lead to discrepancies between analysis results and test data. This paper presents an approach that reduces the time and cost necessary to identify these differences.

This work demonstrates a practical method for predicting vehicle-level automotive steering system NVH performance from component-level NVH measurements of hydraulic steering pumps. For this method, in-vehicle measurements were completed to quantify vehicle noise path characteristics, including steering system structure borne, fluid borne and airborne paths. At the component level, measurements of steering pump reaction forces, sound power and dynamic hydraulic pressure were also completed. The vehicle-level measurement data was used to construct NVH transfer functions for the vehicle. These transfer functions were in turn combined with the pump component data measured on a test stand to create a prediction for steering pump order vehicle interior noise. The accuracy of these predicted values was assessed through comparison with actual vehicle interior noise measurements.