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It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

In the last decades the development time of vehicles has been drastically reduced due to the application of advanced numerical and experimental methods. Specifications concerning durability and other functional attributes for every new model improve for every vehicle. In particular, for machines and components under variable multiaxial loading, fatigue evaluation is one of the most important steps in the design process. Appropriate material testing and simulation is the key to efficient life prediction. However, the life of automotive components, power plants and other high-temperature facilities depends mostly on thermo-mechanical fatigue (TMF). This is due to the normally variable service conditions, which contain the phases of startup, full load, partial load and shut-down.

The need of weight reduction for fuel reduction and CO₂ regulations enforces the use of light-weight materials for structural parts also. The importance of reinforced composites will grow in this area. While the structural behavior and the simulation up to high strain-rate processes for those materials have been in the focus of investigation for many years, nowadays the simulation of high cycle fatigue behavior is getting important as well. Efficient fatigue analysis for metals was developed by understanding the microscopic behavior (crack nucleation and initiation) and bringing it to the macroscopic level by combining it with the matching test data (SN curves, etc.). Similar approaches can be applied to composite materials as well.

Impact noise, inside a car, due to tire-launched gravel on the road can lead to loss of quality perception. Gravel noise is mainly caused by small-sized particles which are too small to be seen on the road by the driver. The investigation focuses on the identification of the mechanisms of excitation and transfer. The spatial distribution of the particles flying from a tire is determined, as well as the probable impact locations on the vehicle body-panels. Finally the relative noise contributions of the body-panels are estimated by adding the panel-to-ear transfer functions. This form of Transfer-Path-Analysis allows vehicle optimization and target setting on the level of the tires, exterior panel treatment and isolation.

This paper presents four methodologies for modeling gear mesh excitations in simple and compound planetary gear sets. The gear mesh excitations use simplified representations of the gear mesh contact phenomenon so that they can be implemented in a numerically efficient manner. This allows the gear mesh excitations to be included in transmission system-level, multibody dynamic models for the assessment of operating noise and vibration levels. After presenting the four approaches, a description is made regarding how they have been implemented in software. Finally, example models are used to do a comparison between the methods

The work presented in this paper outlines the design and development of a compliant sprocket for balancer drives in an effort to reduce the noise levels related to chain-sprocket meshing. An experimental observation of a severe chain noise around a resonant engine speed with the Dual-Mass Flywheel (DMF) and standard build solid (fixed) balancer drive sprocket. Torsional oscillation at the crankshaft nose at full load is induced by uneven running of crankshaft with a dual-mass flywheel system. This results in an increase of the undesirable impact noise caused by the meshing between the chain-links and the engagement/disengagement regions of sprockets, and the clatter noise from the interaction between the vibrating chain and the guides. This paper evaluates and discusses the benefits that the compliant sprocket design provided. A multi-body dynamics system (MBS) model of the balancer chain drive has been developed, validated, and used to investigate the chain noise.

In the present work we investigated experimentally and computationally the unsteady flow around a BMW car model including wheels*. This simulation yields mean flow and turbulence fields, enabling the study aerodynamic coefficients (drag and lift coefficients, three-dimensional/spatial wall-pressure distribution) as well as some unsteady flow phenomena in the car wake (analysis of the vortex shedding frequency). Comparisons with experimental findings are presented. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (TRANS) equations. Special attention is devoted to turbulence modelling and the near-wall treatment of turbulence. The flow calculations were performed using a robust, eddy-viscosity-based ζ - ƒ turbulence model in the framework of the elliptic relaxation concept and in conjunction with the universal wall treatment, combining integration up to the wall and wall functions.

The firewall design of a BMW1 is optimized for interior noise and weight using a Hybrid Interior Noise Synthesis (HINS) approach. This method associates a virtual firewall with a test based body model. A vibro-acoustic model of the firewall panel, including trim elements and full vehicle boundary conditions, is used for predictions in the 40 Hz - 400 Hz range. The short calculation time of this set-up allows multiple design iterations. The firewall noise is reduced by 0.9 dB and its mass by 5.1% through structural changes. Crashworthiness is maintained at its initial level using advanced steel processing. The total interior noise shows improvement in the 90 Hz - 140 Hz range.

Current CAE modeling and simulation techniques in the time domain allow, by now, very accurate prediction of many ride-comfort performances of the cars. Nevertheless, the prediction of the steering wheel rotation vibration excited by, for instance, wheel unbalance or asymmetric obstacle impact, often runs into the difficulty of modeling the steering line with sufficient accuracy. For a classic rack and pinion, hydraulic assisted steering line, one of the challenges is to model the complex and non linear properties - stiffness, friction and damping - of the rack-rack case system. This paper proposes a rack model, thought for easy implementation in complex multi-body models, and an identification procedure of its parameters, based on measurements, in the operational range of the wheel unbalance excitation. The measurements have been gathered by specific tests on the components and the test set-up is also shown here.

This paper presents a CAE based approach to accurately simulate and optimize Ride and Handling metrics. Because of the wide range of vehicle phenomena involved, across the variety of frequency ranges, it is essential that the vehicle model includes proper representation of the dynamic properties of the various subsystems (e.g. tires, steering, PT, etc.) Precise correlation between test and simulation for standalone vehicle components and systems is achieved by replicating in the MBS (Multi-body Simulation) the same tests and boundary conditions. This allows the analyst to correctly define those crucial elements and parameters which have the greatest effect on the R&H attribute to be investigated. Setting up the simulation to correctly represent only one single maneuver simulation at a time would not allow the analyst to consider how the dynamic properties of the chassis design variables should be tuned to achieve to best balance and trade-offs.

A multi-body dynamics model that considers elastic deformation of the body was formulated in order to predict transient body deformation, a factor that affects handling. A comparative analysis with body deformation during handling maneuvers identified using a modal forced response method was conducted, and a good correlation was obtained between vehicle dynamic performance, transient body deformation, and the body modal contribution factor.

This paper describes a practical approach to extract the global static stiffness of a body in white (BIW) from dynamic measurements in free-free conditions. Based on a limited set of measured frequency response functions (FRF), the torsional and bending stiffness values are calculated using an FRF based substructuring approach in combination with inverse force identification. A second approach consists of a modal approach whereby the static car body stiffness is deduced from a full free-free modal identification including residual stiffness estimation at the clamping and load positions. As an extra important result this approach allows for evaluating the modal contribution of the flexible car body modes to the global static stiffness values. The methods have been extensively investigated using finite element modeling data and verified on a series of body in white measurements.

In order to accurately estimate the intake sound pressure level, it is important to improve the accuracy of the air cleaner simulation model and precisely estimate the sound source of the intake. It has been confirmed that the modeling accuracy of an air cleaner can be improved by considering the vibro-acoustic coupling. Meanwhile, the sound source of the intake depends not only on the engine specifications, but on the intake system and even the exhaust system design. In this reported example, since it is difficult to estimate the sound source of the intake only by calculation, due to the aforementioned reasons, actual measurements were carried out to define the sound source. The method is such that the sound source is modeled by acoustic impedance and volume velocity in the engine, and the acoustic impedance is measured using an impedance tube. Then, the sound pressure at the intake opening is measured.

The aim of the project is to reliably identify the set of constructive features responsible for the highest noise levels in the interior of motor vehicles. A simulation environment based on artificial intelligence techniques such as neural networks and genetic algorithms has been implemented. We used a system identification approach in order to approximate the functional relationship between the target noise series and the sets of constructive parameters corresponding to the cars. The noise levels were measured with a microphone positioned on the driver''s chair, and corresponded to a variation of the engine rotation of 600-900 rot/min. The database includes 45 different cars, each described by vectors of 67 constructive features.

The very first step when starting an experimental modal analysis project is the definition of the geometry used for visualization of the resulting mode shapes. This geometry includes measurement points with a label and corresponding coordinates, and usually also connections and surfaces to allow a good visualization of the measured mode. This step, even if it sounds straightforward, can be quite time consuming and is often done in a rather approximate way. Photogrammetry is a technique that extracts 2D or 3D information through the process of analyzing and interpreting photographs. It is widely used for the creation of topographic maps or city maps, and more and more for quick modeling of civil engineering structures or accident reconstruction. The purpose of this paper is to evaluate the use of this technique in the context of modal testing of automotive structures.

The pressure on development cycles in the automotive industry forces the acoustical engineers to create awareness of sound quality in the early stages of development, perhaps even before a physical prototype is available. Currently, designers have few tools to help them listen to their “virtual” models. For the design of a synthesis platform of in-vehicle binaural sound, the sound should be modeled with almost identical sound quality perception. A concept is presented where the total sound of a vehicle is split in a number of components, each with its own sound characteristics. These characteristics are described in a signal model that allows the analysis of an existing sound into a limited number of signal components: orders-frequency spectra, time envelopes and time recordings.

A joint study was conducted between BMW and Goodyear with the objective of analysing the cause and identifying methods to reduce the structure-borne interior noise in a vehicle driving on rough road surfaces. A vibro-acoustic characterization of the car was performed by measuring the car vibro-acoustic transfer functions and by using a transfer path analysis technique to identify the main suspension parts affecting the interior noise at target frequencies. The vibration transmissibility characteristics of the tire were measured and also simulated by Finite Element in [1-200Hz] frequency range. The vibro-acoustic interaction between the tire and car sub-systems was examined. A Finite Element sensitivity analysis was used to define and build new prototype tires. A 3dB(A) interior noise improvement was obtained with these new tires at target frequencies.