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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.

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.

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.

Over the past 30 years, the computer-aided engineering (CAE) tools have been applied extensively in the automotive industry. In order to accelerate time-to-market while coping with legal limits that have become increasingly restrictive over the last decades, CAE has become an indispensable tool covering all major fields in a modern automotive product design process. However, when tackling complex real-life engineering problems, the computational models might become rather involved and thus less efficient. Therefore, the overall trend in the automotive industry is currently heading towards combined approaches, which allow the best of the both worlds, namely the experimental measurement and numerical simulation, to be merged into one integrated scheme. In this paper, the so-called patch transfer function (PTF) approach is adopted to solve coupled vibro-acoustic problems. In the PTF scheme, the interfaces between fluid and structure are discretised in terms of patches.

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.

Nowadays there is an increasing need to streamline CAE processes. One such process consists of translating a Multibody Dynamics System (MBS) model into an equivalent Finite Element Analysis (FEA) model. Typically, users start with the creation of a MBS model which is set at a desired operating point by means of running simulations in the MBS domain (e.g. dynamics, statics.) The MBS model is then further translated into an equivalent FEA model which is used to perform simulations in the FEA domain (e.g. passive safety/crash, noise vibration harshness/NVH.) Currently, the translation of the MBS model into a FEA model is done either manually or by means of using a user-written script. This paper shows that a user-written script that translates a MBS model into a FEA model can not provide a high fidelity translation. In general, it is found that eigenvalues computed by the FEA code would not match eigenvalues computed by the MBS code.

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.

The trend in the previous years showed that an ideal product is not obtained as a sum of development results of several separated disciplines but rather as a result of a holistic multidisciplinary CAE approach. In the course of the whole component development process it is necessary to consider all functions of an individual component equivalent to their importance in the system as a whole, in order to achieve both a technical and a financial optimum. The predictability and the accuracy of an individual computational method have to be regarded against the background of the entire simulation process. A continuative CAE-standard and a harmonious interaction between the different computational disciplines promise more success than focusing specifically on individual topics and thereby neglecting the “bigger picture”. This awareness provided the basis for a decision to change the entire crash simulation software to ABAQUS.

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.

Comfort and well-being have always been connected with a flawless interior acoustic, free of any background noise or BSR, (buzz, squeak and rattle). BSR noises dominate the interior acoustic and represent one of the main sources for discomfort often causing considerable warranty costs. Traditionally BSR issues have been identified and rectified through extensive hardware testing, which by its nature intensifies toward the end of the car development process. In the following paper the integration of a virtual BSR validation technique in a modern development process by the use of appropriate CAE methods is presented. The goal is to shift, in compliance with the front loading concept, the development activities into the early phase. The approach is illustrated through the example of an instrument panel, from the early concept draft for single components to an assessment of the complete assembly.

This study inquired into perceived attributes of car interior noise and correlating psychoacoustic parameters. Auditory assessments of a total of 29 vehicles were performed during cruise and acceleration in two independent road tests. Four perceptual dimensions were found to determine the sound evaluations: comfort/loudness, sportiness, harshness, and timbre. A regression model was used to predict comfort/loudness from sound level, roughness, sharpness and speech intelligibility (SVI). Instrumental assessments of engine roughness demonstrated to predict harshness to a large extent. Sportiness was substantially correlated with the increase of engine sound level due to load change. The latter finding was further examined in a third experiment, using sound synthesis in a test vehicle.

The importance of the automotive interior as a characteristic feature in the competition for the goodwill of the customer has increased significantly in recent years. Whilst there are established, more or less efficient CAE processes for the solution of problems in the areas of occupant safety and service strength, until now the implementation of CAE in themes such as dimensional stability, warpage and corrugation1 of plastic parts has been little investigated. The developmental support in this field is predominantly carried out by means of hardware tests. Real plastic components alter their form as a result of internal forces often during the first weeks following production. The process, known as “creep”, can continue over an extended period of time and is exacerbated by high ambient temperatures and additional external loads stemming from installation and post assembly position.

Cutting development times in car manufacturing means bringing forward the knowledge processes. Simulations based directly on CAD data reduce or replace time-consuming hardware loops significantly and therefore make a significant contribution to this. Ergonomic product design is an area that is challenged as far as the further development of virtual methods is concerned. Simulation of the static and quasi-static positions of passengers inside the car is the current state of the art in ergonomic product design. For this reason, interest is strongly focused on the simulation of complex movement processes within the context of enhancing simulation tools. For the car manufacturer, the manner in which people enter and leave the car is of particular interest. Getting into the car is the customers' first actual contact with it. It may also develop into a serious problem for car drivers, as they get older.

Sport Activity Vehicle (SAV) share a growing market of an entirely new class of vehicles. Outstanding comfort in traditional on-road and also off-road terrain combined with leading edge technology are basic features of this concept. But in addition to that, the SAV has to offer the same overall safety features, expected by e.g. a luxury-segment sedan. A way to ensure the BMW X5 becoming one of the safest cars was the consequent use of simulation techniques in passive safety development. This paper deals with introduction of a CAE driven development process for passive safety in the BMW X5 project, focusing on examples in front and side impact.