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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.

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.

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.

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.

For car manufacturers, seating comfort is becoming more and more important in distinguishing themselves from their competitors. There is a simultaneous demand for shorter development times and more comfortable seats. Comfort in automobile seats is a multi-dimensional and complex problem. Many current sophisticated measuring tools were consulted, but it is unclear on which factors one should concentrate attention when measuring comfort. The goal of this paper is to find a model in order to predict the overall seating discomfort based on body area ratings. Besides micro climate, the pressure distribution appears to be the most objective measure comprising with the clearest association with the subjective ratings. Therefore an analysis with three different test series was designed, allowing the variation of pressure on the seat surface. In parallel the subjects were asked to judge the local and the overall sensation.

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.

Efficiency and dynamic behavior of a vehicle are strongly affected by its weight. Taking into consideration comfort, safety and emissions in modern automobiles, lightweight design is more of a challenge than ever in automotive engineering. Materials development plays an important role against this background, since significant weight decrease is made possible through the substitution of high density materials and more precise adjustment of material parameters to the functional requirements of components. Reinforced light metals, therefore, offer a promising approach due to their high strength to weight ratio. The paper gives an overview on matrix and reinforcement structures suited for the high volume output of the automotive industry. Further analytical and numerical approaches to describe the strengthening effects and the good mechanical characteristics of these composite materials are presented.

During early phases of interior car layout a lot of different aspects have to be considered like crashworthiness, regulations, philosophy of the company etc.. Ergonomic aspects do not always play the most important role in these cases. Since aspects of comfort in cars are getting more and more important in nowadays these aspects should be taken into account very early in the interior car layout process. This paper shows a way to design the interior layout of a car from scratch for a good postural comfort for all anthropometries with the aid of a digital human model (RAMSIS). The novelty of this approach is to use the digital human model to design the interior and not to verify or correct an existing one.

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.

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.

Advanced material technologies play a key role in automotive engineering. The main objective of the development of advanced material technologies for automotive applications is to promote the desired properties of a vehicle. It is characteristic of most materials in modern cars that they have been developed especially for automotive requirements. Requirements are not only set by the customer who expects the maximum in performance, comfort, reliability, and safety from a modern car. Existing legal regulations also have to be met, e.g., in the areas of environmental compatibility, resource preservation, and minimization of emissions. To achieve goals like weight reduction or increased engine performance permanent material developments are essential. In this paper, numerous examples chosen from body, suspension, and powertrain components show clearly how low weight technologies, better comfort, and high level of recyclability can be achieved by advanced material solutions.