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Squeak and rattle (SAR) noise audible inside a passenger car causes the product quality perceived by the customer to deteriorate. The consequences are high warranty costs and a loss in brand reputation for the vehicle manufacturer in the long run. Therefore, SAR noise must be prevented. This research shows the application and experimental validation of a novel method to predict SAR noise on an actual vehicle interior component. The novel method is based on non-linear theories in the frequency domain. It uses the harmonic balance method in combination with the alternating frequency/time domain method to solve the governing dynamic equations. The simulation approach is part of a process for SAR noise prediction in vehicle interior development presented herein. In the first step, a state-of-the-art linear frequency-domain simulation estimates an empirical risk index for SAR noise emission. Critical spots prone to SAR noise generation are located and ranked.

Transfer path analyses of vehicle bodies are widely considered as an important tool in the noise, vibration and harshness design process, as they enable the identification of the dominating transfer paths in vibration problems. It is highly beneficial to model uncertain parameters in early development stages in order to account for possible variations on the final component design. Therefore, parameter studies are conducted in order to account for the sensitivities of the transfer paths with respect to the varying input parameters of the chassis components. To date, these studies are mainly conducted by performing sampling-based finite element simulations. In the scope of a sensitivity analysis or parameter studies, however, a large amount of large-scale finite element simulations is required, which leads to extremely high computational costs and time expenses. This contribution presents a method to drastically reduce the computational burden of typical sampling-based simulations.

Uncertainties play a major role in vibroacoustics - especially in car body design in the preliminary development because of the overall spread in the production that should be covered with one simulation model. Therefore, we use uncertain input parameters to determine the stochastically distributed admittance of the car body before each part of the car is fully designed. To gain a stochastic result - the stochastically distributed admittance curve - we calculate a deterministic finite element simulation several times with sets of stochastically distributed input parameter values. To reduce simulation time and cost of the car model with many million degrees of freedom we focus on the uncertain parameters that show a significant influence on the admittance curve. It is therefore necessary to be able to accurately estimate for each parameter if its influence on the admittance of the car body plays a major role for the noise vibration harshness simulation.

Substructuring approaches are helpful methods to solve and understand vibro-acoustic problems involving systems as complex as a vehicle. In that case, the whole system is split into smaller, simpler to solve, subsystems. Substructuring approaches allow mixing different modeling “solvers” (closed form solutions, numerical simulations or experiments). This permits to reach higher frequencies or to solve bigger systems. Finally, one of the most interesting features of substructuring approaches is the possibility to combine numerical and experimental descriptions of subsystems. The latter point is particularly interesting when dealing with subdomains that remain difficult to model with numerical tools (assembly, trim, sandwich panels, porous materials, etc.). The Patch Transfer Functions (PTF) method is one of these substructuring approaches. It condenses information (impedance matrix) of subsystems on their coupling surfaces.

The Noise Vibration and Harshness (NVH) characteristics and requirements of vehicles are changing as the automotive manufacturers turn their focus from developing and producing cars propelled by internal combustion engines (ICE) to electrified vehicles. This new strategic orientation enables them to offer products that are more efficient and environmentally friendly. Although electric powertrains have many advantages compared to their established predecessors they also bring new challenges that increase the difficulty of matching the high quality requirements of premium car producers especially regarding NVH. Electric motors are one of the most important sources of vibrations in electric vehicles.

Model Order Reduction (MOR) methods such as Component Mode Synthesis (CMS) have been used in order to simulate large linear dynamic systems for many years and have reached a considerable level of saturation. These reduction methods have many advantages such as minimizing computational costs but also have restrictions. One of their disadvantages is that material damping characteristics can only be defined in form of Rayleigh damping. Another disadvantage is that the reduced order model can only represent one state of the structure determined in the generation process of the reduced matrices. In this paper we present a way to consider material damping in reduced matrices that contain one or more materials having different damping characteristics without the disadvantages of using Rayleigh damping.

Noise, vibration, and harshness (NVH) attribute is needed to be included in the vehicle structure design since improving the NVH characteristics enhances the ride quality experienced by the occupants. In this regard, an efficient method was proposed to investigate the structural dynamic response of an automotive body considering low-frequency NVH performances. Moreover, the improvement of an automotive structure under the constraint of NVH behavior was investigated by using the design of experiments (DOEs) method. The DOEs methodology was for screening of the design space and generating approximation models. Here, the thicknesses of panels consisting of a body-in-white (BIW) of an automotive were employed as design variables for optimization, whose objective was to increase the first torsional and bending natural frequencies. Central composite design (CCD) for DOEs sampling and response surface methodology (RSM) were employed to optimize the dynamic stiffness.

The analysis of the acoustic behavior of flow fields has gained importance in recent years, especially in the automotive industry. The comfort of the driver is heavily influenced by the noise levels and characteristics, especially during long distance drives. Simulation tools can help to analyze the acoustic properties of a car at an early stage of the development process. This work focuses on the low-frequency sound effects, which can be a significant noise component under certain operating conditions. As a first step in the fluid-structure interaction workflow, the flow around a series-production vehicle is simulated, including passenger cabin and underhood flow. The complexity of this model poses extensive demands on the simulation software, concerning meshing, turbulence modeling and level of parallelism. We conducted a transient simulation of the compressible fluid flow, using a hybrid RANS/LES approach.

Characterizing the acoustic properties of sound-absorbing materials is costly and time consuming. The acoustic material database helps the automotive designers design their interior trims in accordance with target level for interior noise. In this paper, a two-microphone impedance tube was used to measure the normal sound absorption coefficient. The main parameters that are used in the theoretical model for interior noise level assessment are investigated. These parameters include thickness, airflow resistivity, porosity, tortuosity, viscous and thermal characteristics length. The measured results have been validated by the theoretical models. The validation of normal sound absorption coefficient was found to be in agreement with its corresponding measurement data. Finally, the sensitivity of the sound absorption coefficient which is related to the physical properties mentioned above is further analyzed.

The development and application of the vehicle advanced CAE (computer aided engineering) allowed the vehicle designers to considerably reduce the weight and improve the structural performance of the body. However, the current advanced CAE model can only be available in the late design phase of the vehicle when only minor changes of the structure is feasible. Despite the detailed CAE model, which requires all detailed design, the concept CAE model can be created with less need for the detailed CAD data and it can be created in the early (concept) design phase. The members and panels of the automotive body in white (BIW) are modeled and approximated using beam and shell elements. The joints properties are then obtained from the original detailed CAE model using Guyan reduction method. The automotive seat concept model is also created and added to the concept BIW model.

In many application fields, such as automotive and aerospace, the full FE Biot model has been widely applied to vibro-acoustics problems involving poro-elastic materials in order to predict their structural and acoustic performance. The main drawback of this approach is however the large computational burden and the uncertainty of the input data (Biot parameters) that may lead to less accurate prediction. In order to overcome these disadvantages industry is asking for more efficient techniques. The vibro-acoustic behaviour of structures coupled with poroelastic trims and fluid cavities can be predicted by means of the Patch Transfer Function (PTF) approach. The PTF is a sub-structuring procedure that allows for coupling different sub-systems via impedance relations determined at their common interfaces. The coupling surfaces are discretised into elementary areas called patches.

Wind noise is a significant source of interior noise in automobiles at cruising conditions, potentially creating dissatisfaction with vehicle quality. While wind noise contributions at higher frequencies usually originate with transmission through greenhouse panels and sealing, the contribution coming from the underbody area often dominates the interior noise spectrum at lower frequencies. Continued pressure to reduce fuel consumption in new designs is causing more emphasis on aerodynamic performance, to reduce drag by careful management of underbody airflow at cruise. Simulation of this airflow by Computational Fluid Dynamics (CFD) tools allows early optimization of underbody shapes before expensive hardware prototypes are feasible. By combining unsteady CFD-predicted loads on the underbody panels with a structural acoustic model of the vehicle, underbody wind noise transmission could be considered in the early design phases.

A KIA Soul was instrumented to measure the relative velocity (magnitude and yaw angle) at the front of the vehicle and in-cabin sound at a location close to the side glass near the A-pillar vortex impingement. Tests were conducted at a proving ground under a range of conditions from low wind conditions (~3 m/s) to moderate (7-8 m/s) wind speeds. For any given set of atmospheric conditions the velocity and sound data at any given position on the proving ground were noted to be very repeatable, indicating that the local wakes dominated the "turbulent" velocity field. Testing was also conducted in an aeroacoustic wind tunnel in smooth flow and with a number of novel turbulence generating methods. The resulting sounds were analyzed to study the modulation at frequencies likely to result in fluctuation strength type noise.

Wind noise sources are described including those from the A-pillar region, cavities and bluff bodies. Hydrodynamic pressure fluctuations results from flow separations (in such areas as the A-pillars and mirrors) that generate relatively broad band in-cabin noise. The influence on local radii of the A-pillar is outlined and shown to be a dominant factor in determining hydrodynamic pressure fluctuations in the side-glass regions. Small cavities (eg. styling or water management channels on the mirror casing) generate high-frequency acoustic tones that can also be heard in the cabin and an example of tones from a whistling mirror cavity is shown. A spectrogram of in-cabin noise obtained whilst driving in strong winds is used to illustrate the variability of noise that can be heard on-road and to consider the influence of the relative wind speed.

According to upcoming legislative regulations in certain countries, electric and hybrid-electric vehicles (EVs and HEVs) will have to be equipped with devices to compensate for the lack of engine noise needed to warn pedestrians against the vehicles. This leads to the question of appropriate sound design which has to meet specific psychoacoustic requirements. The present paper focuses on auditory features of warning sounds to enhance pedestrians' safety with a major focus on the detectability of the exterior noise of the vehicle in an ambient noise. For the evaluation of detectability, the psychoacoustic model developed by Kerber and Fastl will be introduced allowing for the prediction of masked thresholds of the approaching vehicle. The instrumental assessment yields estimates of the distance of an approaching vehicle at the point it becomes audible to the pedestrians.

For most car manufacturers, aerodynamic noise is becoming the dominant high frequency noise source (> 500 Hz) at highway speeds. Design optimization and early detection of issues related to aeroacoustics remain mainly an experimental art implying high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the development of a reliable numerical prediction capability. The goal of this paper is to present a computational approach developed to predict the greenhouse windnoise contribution to the interior noise heard by the vehicle passengers. This method is based on coupling an unsteady Computational Fluid Dynamics (CFD) solver for the windnoise excitation to a Statistical Energy Analysis (SEA) solver for the structural acoustic behavior.

A widely common principle of sound quality engineering is the development of objective measures determining human perception. Beside stationary sound parts, auditory events that are based on time-variant attributes have a traceable influence on human perception, particularly in the field of product sound quality. In this paper the significance and identification of the relevant sound quality parameters for power seat adjusters are investigated with a specific design of experiments (DoE). This methodology was used to advance the efficiency of subjective tests. The necessity of an efficient design is given through a relatively high number of variable parameters and, furthermore, through the demands of a qualitative experiment with limited effort for each subject in the listening tests. Instead of investigating randomly picked sounds this approach concentrates on a systematic scanning of the parameter space.

This paper presents an integrated simulation process which has been performed in order to assess the riding comfort performance of a vehicle seat system virtually. Present methods of seat comfort design rely on the extensive testing of numerous hardware prototypes. In order to overcome the limitations of this expensive and time-consuming process, and to fasten innovation, simulation-based design has to be used to predict the seat comfort performance very early in the seat design process, leading to a drastic reduction in the number of physical prototypes. The accurate prediction of the seat transfer function by numerical simulation requires a complete simulation chain, which takes into account the successive stages determining the final seat behaviour when submitted to vibrations. First the manufacturing stresses inside the cushion, resulting from the trimming process, are computed.

Noise and vibration have an important influence on a customer's perception of vehicle quality and cabin interior noise levels are a key criteria. The interior sound levels of automobiles have been significantly reduced over the years, with reductions in power train, tire and external wind noise. One of the highest in-cabin noise levels now arises from heating, ventilating and air conditioning systems, generated by the air-rush noise at various HVAC settings. Thus quieter climate control systems are desired by car manufacturers. A systematic benchmarking study was performed to investigate the in-cabin noise of vehicles. 21 passenger cars including compact, mid-size, full-size, and a truck were selected. Tests were conducted on relatively new production vehicles in various conditions. A binaural head system was used in front passenger seat to measure noise levels. The methodology used and the experimental results were presented in this paper.

A computational analysis of underbody windnoise sources on a production automobile at 180 km/h free stream air speed and 0° yaw is presented. Two different underbody geometry configurations were considered for this study. The numerical results have been obtained using the commercial software PowerFLOW. The simulation kernel of this software is based on the numerical scheme known as the Lattice-Boltzmann Method (LBM), combined with a two-equation RNG turbulence model. This scheme accurately captures time-dependent aerodynamic behavior of turbulent flows over complex detailed geometries, including the pressure fluctuations causing wind noise. Comparison of pressure fluctuations levels mapped on a fluid plane below the underbody shows very good correlation between experiment and simulation. Detailed flow analysis was done for both configurations to obtain insight into the transient nature of the flow field in the underbody region.