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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.

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.

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 development of new design tools to predict the vibro-acoustic behavior within the vehicle development process is of essential importance to achieve better products in an ever shorter timeframe. In this paper, an energy flow post-processing tool for structural dynamic analysis is presented. The method is based on the conversion of conventional finite element (FE) results into energy quantities corresponding with each of the vehicle subcomponents. Based on the global dynamic system behavior and local subcomponent descriptions, one can efficiently evaluate the energy distribution and analyze the vibro-acoustic behavior in complex structures. By using energy as a response variable, instead of conventional design variables as pressure or velocity, one can obtain important information regarding the understanding of the vibro-acoustic behavior of the system.

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 optimization of the vaporization and mixture formation process is of great importance for the development of modern gasoline direct injection (GDI) engines, because it influences the subsequent processes of the ignition, combustion and pollutant formation significantly. In consequence, the subject of this work was the development of a measurement technique based on the laser induced exciplex fluorescence (LIF), which allows the two dimensional visualization and quantification of the in-cylinder air/fuel ratio. A tracer concept consisting of benzene and triethylamine dissolved in a non-fluorescent base fuel has been used. The calibration of the equivalence ratio proportional LIF-signal was performed directly inside the engine, at a well known mixture composition, immediately before the direct injection measurements were started.

Traditionally, vibration analysis in operating conditions (on the road or on a bench) had to be combined with experimental modal analysis in controlled laboratory conditions in order to understand the modal behaviour of the structure. This requires additional measurements, costs and time. However, in many applications, the real operating conditions may differ significantly from those applied during the modal test and hence the vibration modes from the modal test might not be representative for the active modes in operation conditions. The need for a capability of doing a modal analysis on data from operating conditions is obvious. Over the last years, several modal parameter estimation techniques have been proposed and studied for modal parameter extraction from output-only data. Each method needs to make a number of assumptions and has some limitations.

One of the scientific fields where, for already more than 20 years, system identification plays a crucial role is this of structural dynamics and vibro-acoustic system optimization. The experimental approach is based on the “Modal Analysis” concept. The present paper reviews the test procedure and system identification principles of this approach. The main focus though is on the real problems with which engineers, performing modal analysis on complex structures on a daily basis, are currently confronted. The added value of several new testing approaches (laser methods, smart transducers…) and identification algorithms (spatial domain, subspace, maximum likelihood,..) for solving these problems is shown. The discussed elements are illustrated with a number of industrial case studies.

Driveline torsional vibration in vehicles equipped with an automatic gearbox can lead to increased fuel consumption. At low rpm the torque converter of the automatic gearbox is active. The earlier the torque converter can be disengaged and bypassed by a lock-up clutch, the better the efficiency of the engine. Torsional vibrations in the drivetrain could prevent this early locking of the torque convertor and thus lead to a higher fuel consumption. Furthermore, these torsional vibrations can also lead to lower driver comfort. In order to improve the efficiency and the passenger comfort, a hybrid approach has been developed to predict the torsional vibrations of a full vehicle during a run-up manoeuvre on a chassis dyno, including transient effects. The hybrid approach is based on multi body modeling of the full car in LMS DADS, taking into account the flexibility of all major components of the powertrain.

“Noise and vibration are not invented here!”. Undesirable structural dynamic behaviour is normally experienced on final assemblies, by which time the underlying cause of the problem is difficult to solve intuitively. Solving the problems classically involves the partial breakdown of assemblies and the application of various structural dynamics testing and analysis procedures. Preferably, noise and vibration problems should be avoided by designing the product right the first time, by the use of various integrated analysis and testing disciplines, from the component level to the final assembly. Such an approach is referred to, in a broader sense, by trendy themes as concurrent engineering, forward engineering, simultaneous engineering.... This paper analyzes trends in analytical and experimental structural dynamics toward better integration of the various discipline oriented techniques that are currently used.

Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.

A local Gaussian process regression approach is presented, which allows to model nonlinearities of internal combustion engines more accurate than global Gaussian process regression. By building smaller models, the prediction of local system behavior improves significantly. In order to predict a value, the algorithm chooses the nearest training points. The number of chosen training points depends on the intensity of estimated nonlinearity. After determining the training points, a model is built, the prediction performed and the model discarded. The approach is demonstrated with a benchmark system and air charge test bed measurements. The measurements are taken from a turbocharged SI gasoline engine with both variable inlet valve lift and variable inlet and exhaust valve opening angle. The results show how local Gaussian process regression outmatches global Gaussian process regression concerning model quality and nonlinearities in particular.

Tip-in/Tip-out of the accelerator pedal generates transient torque oscillations in the driveline. These oscillations may be amplified by P/T, suspension and body modes and will eventually be sensible at the receiver side in the vehicle, for example at the seat or at the steering-wheel. The forces that are active during this transient excitation are influenced by non-linear effects in both the suspension and the power train mounts. In order to understand the contribution of each of these forces to the total interior target response (e.g. seat rail vibration) a detailed investigation is performed. Traditional force identification methods are not suitable for low-frequent, transient phenomena like tip-in/tip-out. Mount stiffness method can not be used because of non-linear effects in the P/T and suspension mounts. Application of matrix inversion method based on trimmed body vibration transfer functions is not possible due to numerical condition problems.

Active suspension systems aim at increasing safety by improving vehicle ride and handling performance while ensuring superior passenger comfort. Good control of this active system can only be achieved by providing the control algorithm with reliable and accurate signals for the required quantities. This paper presents the design and development of a state estimator that accurately provides the information required by a sky-hook controller, using a minimum of sensors. The vehicle inertial parameters are estimated by an algorithm based on Monte Carlo simulations and anthropometric data. All state updating is performed using Kalman filters. The resulting performance enhancement has been proven during test drives.

The investigation of critical noise sources on pass-by noise tests is demanding development of the current techniques in order to locate and quantify these sources. One recent approach is to use beamforming techniques to this purpose. The phased array information can be processed using several methods, for example, conventional delay-and-sum algorithms, deconvolution based algorithms, such as DAMAS, and more recently, the generalized inverse beamforming. This later method, presents the advantage of separating coherent sources with better dynamic range than conventional beamforming. Also, recent developments, such as Iteratively Re-Weigthing Least Squares, increases the localization accuracy allowing it to be used in a challenging problem as a fast moving source detection, a non-stationary condition. The work will raise the main advantages and disadvantages on this method using a practical case, a passenger vehicle pass-by test.

A key issue in noise emission studies of noise producing machinery concerns the identification and analysis of the noise sources and their interaction and radiation into the far field. This paper presents a new acoustic measurement technique for noise source identification in stationary applications. The core of the technology is a handheld measurement instrument combining a position and orientation tracking device with a 3D sound intensity probe. The technique allows an on-line 3D visualization of the sound field while moving the probe freely around the test object. By focusing on the areas of interest, troublesome areas can be identified that require further in-depth analysis. The measurement technique is flexible, interactive and widely applicable in industrial applications. This paper explains the working principle and characteristics of this new technology and positions it to existing methods like traditional sound intensity testing and array techniques.

Air conditioning acoustics have become of paramount importance in electric vehicles, where noise from electromechanical components is no longer masked by the presence of the internal combustion engine. In a car HVAC systems, the coolant compressor is one of the most important sources in terms of vibration and noise generation. The paper, the generated structural noise is studied in detail on a prototype installation, and the noise transmission and propagation mechanisms are analyzed and discussed. Through ”in situ” measurements and virtual point transformation, the rotor unbalance forces and torque acting within the component are identified. The dynamic properties of the rubber mounts, installed between the compressor and its support, are identified thanks to matrix inversion methods. To assess the quality of the proposed procedure, the synthesized sound pressure level is compared with experimental SPL measurements in different operational conditions.

Wing Anti-Icing Systems (WAIS) are integral part of a wing design. Their presence ensures safety in all-weather conditions. In standard designs, the WAIS are fitted in the slat internal structure and runs throughout its span in between the ribs. Given its critical function, such a system has to pass qualification test. The test specification is dictated by international standards. In the case discussed in this article, the standard adopted is the RTCA DO-160G “Environmental Conditions and Test Procedures for Airborne Equipment”. In particular, the work presented here concerns with the Vibration environmental test. The standard prescribes a number of dynamic tests to be carried out on the AIS: random, shock and sine excitation tests have to be performed in order to study their effect on the parts composing the Anti-Icing System. The standard prescribes vibration levels at the attachment locations of the AIS to the wings' ribs.