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During the last ten years, there is a significant tendency in automotive design to use lower aspect ratio tires and meanwhile also more and more run-flat tires. In appropriate publications, the influences of these tire types on the dynamic loads - transferred from the road passing wheel center into the car - have been investigated pretty well, including comparative wheel force transducer measurements as well as simulation results. It could be shown that the fatigue input into the vehicle tends to increase when using low aspect ratio tires and particularly when using run-flat tires. But which influences do we get for the loading and fatigue behavior of the respective rims? While the influences on the vehicle are relatively easy to detect by using wheel force transducers, the local forces acting on the rim flange (when for example passing a high obstacle) are much more difficult to detect (in measurement as well as in simulation).

In the eighties, the main concern in the automotive industry from a designer's standpoint was a level issue. In the nineties, the market has put more stringent requirements on the automotive industry with respect to noise in general and psychoacoustics. The governments have imposed lower limits with respect to pass-by noise standards. Customers are spending more time in their car than in the past and are demanding acoustical comfort. All of this is leading to an environment where a sound quality system is becoming a daily tool in the design and trouble-shooting world. This paper describes what should be looked for in a sound, how to quantify these properties and what tools are needed. These steps are then applied in a case study.

Vehicles with electrified powertrains are being introduced at an increasing pace. On the level of interior sound, one is often inclined to assume that NVH problems in EV have disappeared together with the combustion engine. Three observations demonstrate that this is not the case. First of all, only the dominant engine sound disappears, not the noise from tire, wind or auxiliaries, which consequently become increasingly audible due to the removal of the broadband engine masking sound. Secondly, new noise sources like tonal sounds from the electro-mechanical drive systems emerge and often have, despite their low overall noise levels, a high annoyance rating. Thirdly, the fact that engine/exhaust sounds are often used to contribute to the “character” of the vehicle leads to an open question how to realize an appealing brand sound with EV. Hybrid vehicles are furthermore characterized by mode-switching effects, with impact on both continuity feeling and sound consistency problems.

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.

The continuous encouragement of lightweight design in modern vehicles demands a reliable and efficient method to predict and ameliorate the interior acoustic comfort for passengers. Due to considerable psychological effects on stress and concentration, the low frequency contribution plays a vital rule regarding interior noise perception. Apart other contributors, low frequency noise can be induced by transient aerodynamic excitation and the related structural vibrations. Assessing this disturbance requires the reliable simulation of the complex multi-physical mechanisms involved, such as transient aerodynamics, structural dynamics and acoustics. The domain of structural dynamics is particularly sensitive regarding the modelling of attachments restraining the vibrational behaviour of incorporated membrane-like structures. In a later development stage, when prototypes are available, it is therefore desirable to replace or update purely numerical models with experimental 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.

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 covers the application of hybrid vibro-acoustic simulation methods to shorten the design cycle of power-plant components. A comparison is made between Frequency Response Function based and Modal based algorithms for the generation of a predictive powerplant assembly model. The effectiveness of design modifications is evaluated by loading the original and modified predictive models with experimentally identified excitation forces. The procedure is validated by correlation with experimental data.

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.

Inverse numerical acoustics is a method which reconstructs the source surface normal velocity from the sound measured in the near-field around the source. This is of particular interest when the source is rotating or moving, too light or too hot to be instrumented by accelerometers. The use of laser vibrometers is often of no remedy due to the complex shape of the source. The Inverse Numerical Acoustics technique is based on the inversion of transfer relations (Acoustic Transfer Vectors) using truncated Singular Value Decomposition (SVD). Most of the time the system is underdetermined which results in a non unique solution. The solution obtained by the truncated SVD is the minimal solution in the RMS sense. This paper is investigating the impact of non homogeneities in the mesh density (local mesh refinement) on the retrieved solution for underdetermined systems. It will be shown that if transfer quantities are inverted as such, big elements get a higher weight in the inversion.

The present work attempts a complete noise and vibration analysis for an electric vehicle at concept stage. The candidate vehicle is the Future Steel Vehicle (FSV), a lightweight steel body with an electric motor developed by WorldAutoSteel [1,2,3]. Measurements were conducted on two small Mitsubishi vehicles that both share the same body, yet one is equipped with an internal combustion engine and the other with an electric motor. The outcome was used as a starting point to identify assets and pitfalls of electric motor noise and draw a set of Noise Vibration and Harshness (NVH) targets for FSV. Compared to a combustion engine, the electric motor shows significantly lower sound pressure levels, except for an isolated high frequency peak heard at high speeds (3500 Hz when the vehicle drives at top speed). The prominence of this peak is lowered by increased use of acoustic absorbent materials in the motor compartment.

Two models for the forecast of road traffic emissions, independently developed in parallel, are comparatively presented and assessed: EPROG developed by BMW and enlarged by VDA for a national application (Germany) and FOREMOVE, developed for application on European Community scale. The analysis of the methodological character of the two algorithms proves that the models are fundamentally similar with regard to the basic calculation schemes used for the emissions. The same holds true as far as the significant dependencies of the emission factors, and the recognition and incorporation of the fundamental framework referring to traffic important parameters (speeds, mileage and mileage distribution etc) are concerned.

Low frequency noise from engine- and wheel-vibrations often dominates the interior noise spectrum in vehicles. For the optimization of vehicle bodies it is necessary to know the contribution of individual body panels to sound pressures at the passengers ear. An experimental approach is presented which makes use of reciprocal acoustic transfer function measurements and surface acceleration measurements in normal road operation. This method, called Airborne Source Quantification, has been applied as a diagnostic tool to the interior noise of a four cylinder diesel engined van.

This paper presents the results of an experimental test campaign carried out on a city bus powered by serial hybrid power train. The driveline system combines an Internal Combustion Engine with a battery pack and two electric motors. Tests were aimed at identifying the salient signal characteristics of the noise spectra recorded during operating conditions and to assess the acoustic comfort in the passenger compartment. Transfer Path Analysis technique was applied to identify airborne and structure borne vibro-acoustic loads, to measure transfer functions linking source locations to target locations and to estimate the internal vibro-acoustic comfort in operating conditions.

Friction-induced vibration is a serious problem in many industrial applications containing systems with rotating and/or sliding parts. Brake noise is a typical example. The critical element in the noise generation process is the combination of friction-induced loads with the dynamics of the braking system. In the present paper, a detailed experimental and numerical study of a specific low-frequency brake squeal problem is made on a simplified brake noise test rig. First, the signal and spatial characteristics of the noise were analyzed by spectral and acoustic holography techniques. A parametric study of influence factors as brake pressure, rotation speed, etc. was made. Operational deformation analysis during squeal confirms the dominant modal behavior of the components, implying the critical role of the assembly structural dynamics.

In vehicle NVH development, vibroacoustic simulations with Finite Element (FE) models are a common technique. The computational costs for these calculations are steadily rising due to more detailed modelling and higher frequency ranges. At the same time, the need for multiple evaluations of the same model with different input parameters, e.g., for uncertainty quantification, optimization, or robustness investigations, is also increasing. Therefore, it is crucial to reduce the computational costs in these cases. A common technique is to use surrogate models that replace the computationally intensive FE model to perform repeated evaluations. Several different methods in this area are well established, but with the continuous advancements in the field of machine learning, interesting new methods like the Gaussian Process (GP) regression arises as a promising approach.

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 increasing complexity of communication protocols for asynchronous multiplex systems requires the use of simulation during the optimisation of these protocols or the integration of other control units. Consideration of realistic communication behaviour of the connected control units is essential for performance analysis of multiplex systems. For a first pass, the use of simple statistical distributions (e.g. Poisson distribution) is suitable to get some simulation results. A better way to get realistic results is the approximation of empirical communication data through the use of more complex statistical distribution (e.g. mixed Erlang distributions). In this paper several approaches for the approximation of empirical data are presented. Beside simple statistical distributions (with one parameter), the use of more complex statistical distributions is discussed and methods for the identification of their parameters are presented.

In this contribution functional safety is discussed from a car manufacturer's point of view. Typical elements of a safety standard concerning safety activities during the product development process are described as well as management and other supporting processes. Emphasis is laid on the aspect of risk assessment and the determination of safety classes. Experiences with methods for safety analysis like FTA or FMEA are discussed and pros and cons of quantitative safety assessment are argued.

This paper presents the measurement & analysis procedures and the results of a complete road noise identification and reduction project on a midsize passenger car. Operational interior noise signals and structural accelerations are measured for several test conditions. The operating data are decomposed into sets of mathematically independent phenomena by Principal Component Analysis. Operating Deflection Shape Analysis and Transfer Path Analysis are applied to each of these independent phenomena. Critical transfer paths are thus identified and quantified. The interior sound level is amplified when the frequency content of the transmitted energy coincides with structural resonances or standing waves of the interior car cavity. The vehicle is dynamically characterized by Experimental Structural Modal Analysis and by Acoustic Modal Analysis.