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The statistical energy analysis (SEA) is widely used to support the development of the sound package of cars. This paper will present the preparation of a model designed to investigate the sound package of the new Audi A3 and associated correlation against measurements. Special care was given during the creation of the model on the representation of the structure to enable the analysis of structure borne energy flow on top of the classical airborne analysis usually done with SEA. The sound package was also detailed in the model to allow further optimization and analysis of its performance. Two real life load cases will be presented to validate the model with measurements. First, the dominating powertrain and a second load case with dominating rolling noise. An analysis of the contribution of the different source components and a way to diagnose the weak paths of the vehicle will be presented. The focus of this investigation is the application of optimally adjusted treatment.

Electrified vehicles are particularly quiet, especially at low speeds due to the absence of combustion noises. This is why there are laws worldwide for artificial driving sounds to warn pedestrians. These sounds are generated using a so-called Acoustic Vehicle Alerting System (AVAS) which must maintain certain minimum sound pressure levels in specific frequency ranges at low speeds. The creation of the sound currently involves an iterative and sometimes time-consuming process that combines composing the sound on a computer with measuring the levels with a car on an outside noise test track. This continues until both the legal requirements and the subjective demands of vehicle manufacturers are met. To optimize this process and reduce the measurement effort on the outside noise test track, the goal is to replace the measurement with a simulation for a significant portion of the development.

With battery electric vehicles (BEV), due to the absence of the combustion process, the rolling noise comes even more into play. The BEV technology also leads to different concepts of how to mount the electric engine in the car. Commonly, also applied with the Audi e-tron, the rear engine is mounted on a subframe, which again is connected to the body structure. This concept leads to a better insulation in the high frequency range, yet it bears some problems in designing the mounts for ride comfort (up to 20Hz) or body boom (up to 70Hz). Commonly engine mounts are laid-out based on driving dynamics and driving comfort (up to 20Hz). The current paper presents a new method to find an optimal mount design (concerning the stiffness) in order to reduce the dynamic chassis forces which are transferred to the body (>20Hz). This directly comes along with a reduction of the sound pressure level for the ‘body boom’ phenomena.

Since the last decade, the automotive industry has expressed the need to better understand how the different trim parts interact together in a complete car up to 400 Hz for structureborne excitations. Classical FE methods in which the acoustic trim is represented as non-structural masses (NSM) and high damping or surface absorbers on the acoustic cavity can only be used at lower frequencies and do not provide insights into the interactions of the acoustic trims with the structure and the acoustic volume. It was demonstrated in several papers that modelling the acoustic components using the poroelastic finite element method (PEM) can yield accurate vibro-acoustic response such as transmission loss of a car component [1,2,3]. The increase of performance of today's computers and the further optimization of commercial simulation codes allow computations on full vehicle level [4,5,6] with adequate accuracy and computation times, which is essential for a car OEM.

The acoustic trim components play an essential role in NVH behavior by reducing both the structure borne and airborne noise transmission while participating to the absorption inside the car. Over the past years, the interest for numerical solutions to predict the noise transmission through trim packages has grown, leading to the development of dedicated CAE tools. The incrementally restrictive weight and space constraints force today CAE engineers to seek for optimized trim package solution. This paper presents a two-steps process which aims to reduce the structure borne road noise due to floor panel using a coupled simulation with MSC NASTRAN and Actran. The embossment of the supporting steel structure, the material properties of porous layers and the thickness of visco-elastic patches are the design variables of the optimization process.

At single irregularities, such as manhole covers and joints in concrete road surfaces, axle and engine vibrations are increased. Depending on the response characteristic of the vehicle chassis and seats and the duration of the event, such excitations can have a considerable influence on the comfort of vehicle occupants. With the objective of optimising the vibration characteristics of the axles of a vehicle, a procedure is presented which clarifies the motion sequences due to certain types of excitation on a roller test stand. This knowledge permits the optimisation of the axle kinematics, the axle bearings, and the spring-damper system.

In recent years, driving simulators have become a valuable tool in the automotive design and testing process. Yet, in the field of vehicle dynamics, most decisions are still based on test drives in real cars. One reason for this situation can be found in the fact that many driving simulators do not allow the driver to evaluate the handling qualities of a simulated vehicle. In a driving simulator, the motion cueing algorithm tries to represent the vehicle motion within the constrained motion envelope of the motion platform. By nature, this process leads to so called false cues where the motion of the platform is not in phase or moving in a different direction with respect to the vehicle motion. In a driving simulator with classical filter-based motion cueing, false cues make it considerably more difficult for the driver to rate vehicle dynamics.

To assure high comfort for vehicle passengers, the interior noise has to be designed to be low in volume as well as in a pleasant way. Vehicle’s HVAC (heating, ventilation and air-conditioning) noise becomes increasingly audible when the main sound sources are acoustically optimized. Thus, the Sound Quality of HVAC noise needs to be evaluated early in the development process. For assessing the Sound Quality of HVAC noise, suitable evaluation criteria as well as the knowledge of the acoustics of the new HVAC system are required. Suitable evaluation criteria were identified using listening tests. In a second step HVAC noise was investigated in different environments: HVAC as a component, HVAC as a system (including air ducts and vents) and HVAC system integrated in a simplified car model. The model was designed acoustically similar to a series vehicle. Thus, the size as well as the interior paneling of a series vehicle was approximated by using sound-absorbing and -reflecting material.

Hybrid vehicle simulation methods combine physical test articles (vehicles, suspensions, etc.) with complementary virtual vehicle components and virtual road and driver inputs to simulate the actual vehicle operating environment. Using appropriate components, hybrid simulation offers the possibility to develop more accurate physical tests earlier, and at lower cost, than possible with conventional test methods. MTS Systems has developed Hybrid System Response Convergence (HSRC), a hybrid simulation method that can utilize existing durability test systems and detailed non-real-time virtual component models to create an accurate full-vehicle simulation test without requiring road load data acquisition. MTS Systems and Audi AG have recently completed a joint evaluation project for the HSRC hybrid simulation method using an MTS 329 road simulator at the Audi facility in Ingolstadt, Germany.

1. The present work introduces an approach for the analysis of the noise propagation behavior of mechatronic brake systems in modern passenger vehicles. While on the one hand, the number of features realized through the mechatronic brake system is strongly increasing; on the other hand, a continuous reduction of the overall vehicle interior noise level can be observed. This leads to an increase of interfering noise phenomena in the vehicle interior that customers might perceive as insufficient product quality. Therefore, noise elimination always plays an important role in vehicle development. The mechatronic brake system induces interfering noise that is transferred into the vehicle interior, differing from vehicle to vehicle and maneuver to maneuver. Supposedly, a wide frequency range, numerous components, and various branched transfer paths in the physical domains of airborne, structure-borne, and fluid-borne sound are involved in the noise propagation.

Computational Fluid Dynamics (CFD) is state of the art in the aerodynamic development process of vehicles nowadays. With increasing computer power the numerical simulations including meshing and turbulence modeling are capturing the complex geometry of vehicles and the flow field behavior around and behind a bluff body in more detail. The ultimate goal for realistic automotive simulations is to model the under-hood as well. In this study vehicle simulations using the finite volume open source CFD program OpenFOAM® are validated with own experiments on a modified generic quarter-scale SAE body with under-hood flow. A model radiator was included to take account of the pressure drop in the under-hood compartment. Force and pressure measurements around the car, total-pressure and hot-wire measurements in the car flow field and surface flow patterns were simulated and compared with the experiment.

The following document offers insight into the work of the MOST Cooperation. Now that MOST is on the road, a short overview of five years of successful collaborative work of the partners involved and the results achieved will be given. Emphasis is put on the importance of a shared vision in combination with shared values as a prerequisite for targeted collaborative work. It is also about additional key success factors that led to the success of the MOST Cooperation. Your attention will be directed to the way the MOST Cooperation sets and achieves its goals. And you will learn about how the organization was set-up to support a fast progression towards the common goal. The document concludes with examples of recent work as well as an outlook on future work.

Brake Particle Emission (BPE) is gaining considerable importance for the friction brake and automotive industry. So far no common approach or legislation for BPE characterization exists although many activities in this field have been started during the last years. Taking this into account, the authors carried out a joint measurement campaign to investigate a new approach regarding the sampling location using a brake dynamometer. During preliminary investigations the influence of the cooling air quality has been examined and a sampling point position validation has been carried out. At first the stabilization behavior for repeated test cycles and variations of volumetric air flow rates are analyzed. As a next step the role of volatile particle emissions is determined. Subsequently, the influence of load history and friction power is studied. Finally results in terms of the role of high temperature applications are presented.

To significantly increase fuel efficiency while keeping power and performance of its signature S models, AUDI developed a new 4.0 TFSI engine with Cylinder on Demand technology and introduced it with its new S6, S7 and S8 models. To manage upcoming NVH issues due to this new technology and keep the intended sporty V8 note of the engine under all operating conditions, a broad range of new and advanced technologies was introduced with these vehicles. This paper focusses on the Active Noise Control system and its development. It describes the ANC system from a control theory perspective in addition to the acoustical perspective. Special features of the system include the availability of multiple tunings (4/8 cylinder mode) to support the specific overall sound character and the fast switching process as switching between different cylinder configurations might be as fast as 300 ms. In addition, the system also includes specific features that allow an advanced audio system diagnosis.