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Finite element simulation (FE) makes it possible to analyze the structural dynamic behavior of vehicle seat structures in early design phases to meet Noise-Vibration-Harshness (NVH) requirements. For this purpose, linear simulations are usually used, which neglect many nonlinear mechanical properties of the real structure. These models are trimmed to fit global vibration behavior based on the complex description of contact or jointed definitions. Targeted design is therefore only possible to a limited extent. The aim of this work is to characterize the entire seat structure and its sub-components in order to identify the main contributors using experimental and simulative data. The Lagrange Multiplier Frequency Based Substructuring (LM-FBS) method is used for this purpose. Therefore, the individual subsystems of seat frame, seat backrest and headrest are characterized under different conditions.

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.

Squeak and rattle noise in a vehicle’s interior is perceived as an annoying sound by customers. Since persistent noise (e.g. engine, wind or drive train noise) has been reduced continuously during the last decades, the elimination of sounds, which have their origin in the vehicle’s interior components, is getting more important. Therefore, noise prediction based on simulation models is useful, since design changes can be realized at lower costs in early virtual development phases. For this task, linear simulation methods are state of the art for the identification of noise risk, but in general without knowing if a sound is audible or not. First approaches have been developed based on the Harmonic Balance Method to predict squeak noise and assess their audibility. This paper presents vibroacoustic measurements at a door trim panel for squeaking and non-squeaking configurations. Vibrations are excited harmonically by a force controlled low noise shaker.

Thermoplastic fibre reinforced composites offer a wide range of adjusting the material behaviour by varying material selection, layup and fibre orientation. By default, damping and stiffness of composites are contradictory material properties related to the fibre orientation. Thus, finite element analysis (FEA) based composite design requires special modelling efforts implying anisotropic damping of the composite as well as fluid-structure-inter-action for the oil filling. In contrast, multi-dimensional optimisations for various layups require computationally fast numerical solutions. In this study, a complex but efficient vibro-acoustic modelling approach of a composite oil pan is presented. The FEA model includes a strain energy based modal damping approach for the layerwise accumulation of the anisotropic composite damping as well as a structural representation of the additional mass of the oil filling avoiding fluid modelling.

As a key part of numerical analysis, the modeling process has a tremendous influence on the quality of the results. While there is general awareness concerning uncertainties that arise during modeling, their quantity and sensitivity rarely are known. Hence, modeling quickly can become inaccurate and inefficient. The scope of the present paper is to innovate predictive modeling processes concerning the dynamics of real complex structures by means of linear modal analysis with the finite element method (FEM). The aim is to offer a transparent design catalog relating specific uncertainties to each model component in order to achieve error prevention for engineers dealing with comparable systems. A complex system is simplified and investigated for different levels of detail. Only after the model uncertainties for one level of detail are obtained, the next level of complexity is approached.