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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.

Battery-electric vehicles (BEVs) require new chassis components, which are realized as mechatronic systems mainly and support more and more by-wire functionality. Besides better controllability, it eases the implementation of integrated control strategies to combine different domains of vehicle dynamics. Especially powertrain layouts based on electric in-wheel machines (IWMs) require such an integrated approach to unfold their full potential. The present study describes an integrated, longitudinal vehicle dynamics control strategy for a battery electric sport utility vehicle (SUV) with an electric rear axle based on in-wheel propulsion. Especially the influence of electronic brake force distribution (EBD) and torque blending control on the overall performance are discussed and demonstrated through experiments and driving cycles on public road and benchmarked to results of previous studies derived from [1].

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.

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.

The electrification of the powertrain and the thereto related recuperation of the electric engine saves the energy in the battery and thus reduces the thermally dissipated brake energy, which leads to lower brake rotor temperatures compared to combustion engine vehicles (ICEVs). These new conditions enable to reconsider brake disc concepts. Including lightweight design in heavy battery electric vehicles (BEVs) and the increasingly reliant corrosion resistance of brake rotors, Aluminum is a promising approach for new brake disc concepts. In the past, Aluminum brake disc concepts have already been deployed. For instance Aluminum Metal-Matrix Composite (Al-MMC) concepts in the Lotus Elise S1 and on the rear axle of the Volvo V40 [1]. The presented concept is a different approach and separates the friction system from the bulk Aluminum brake disc, achieved by coating of the friction rings.

As the importance of sustainability increases and dominates the powertrain development within the automotive sector, this issue has to be addressed in motorsports as well. The development of sustainable high-performance fuels defined for the use in motorsports offers technical and environmental potential with the possibility to increase the sustainability of motorsports at the same or even a better performance level. At the moment race cars are predominantly powered by fossil fuels. However due to the emerging shift regarding the focus of the regulations towards high efficient powertrains during the last years the further development of the used fuels gained in importance. Moreover during the last decades a huge variety of sustainable fuels emerged that offer a range of different characteristics and that are produced based on waste materials or carbon dioxide.

The engine development process has been enhanced significantly by virtual engineering methods during the last decades. In terms of in-cylinder flow field, charge flow and combustion modelling, 3D-CFD (three dimensional) simulations enable detailed analysis and extended investigations in order to gain additional knowledge about design parameters. However, the computational time of the 3D-CFD is an obvious drawback that prevents a reasonable application for extensive analysis with varying speed, load and transient conditions. State-of-the-art 0D (zero dimensional) approaches close the gap between the demand of high computational efficiency and a satisfying accordance with experimental data. Recent improvements of phenomenological combustion approaches for gasoline spark ignition engines deal with the consideration of detailed flow parameters, the accuracy of the laminar flame speed calculation and the prediction of the knock limit.

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.

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.

The aerodynamic development of the new Audi Q5 (released in 2017) is described. In the course of the optimization process a number of different tools has been applied depending on the chronological progress in the project. During the early design phase, wind tunnel experiments at 1:4 scale were performed accompanied by transient DES and stationary adjoint simulations. At this stage the model contained a detailed underbody but no detailed engine bay for underhood flow. Later, a full scale Q5 model was built up for the aerodynamic optimization in the 1:1 wind tunnel at Audi AG. The model featured a detailed underbody and engine bay including original parts for radiators, engine, axles and brakes from similar vehicles. Also the 1:1 experiments were accompanied by transient DES and stationary adjoint simulations in order to predict optimization potential and to better understand the governing flow.

During series production of modern combustion engines a major challenge is to ensure the correct operation of every engine part. A common method is to test engines in end-of-line (EOL) cold test stations, where the engines are not fired but tugged by an electric motor. In this work we present a physically based 0D model for dynamic simulation of combustion engines under EOL test conditions. Our goals are the analysis of manufacturing faults regarding their detectability and the enhancement of test procedures under varying environmental conditions. Physical experiments are prohibitive in production environments, and the simulative approach reduces them to a minimum. This model is the first known to the authors exploring advanced engine test methods under production conditions. The model supports a wide range of manufacturing faults (with adjustable magnitude) as well as error-free production spread in engine components.

The aerodynamic optimization of an AUDI Q5 vehicle is presented using the continuous adjoint approach within the OpenFOAM framework. All calculations are performed on an unstructured automatically generated mesh. The primal flow, which serves as input for the adjoint method, is calculated using the standard CFD process at AUDI. It is based on DES calculations using a Spalart-Allmaras turbulence model. The transient results of the primal solution are time averaged and fed to a stationary adjoint solver using a frozen turbulence assumption. From the adjoint model, drag sensitivity maps are computed and measures for drag reduction are derived. The predicted measures are compared to CFD simulations and to wind tunnel experiments at 1:4 model scale. In this context, general challenges, such as convergence and accuracy of the adjoint method are discussed and best practice guidelines are demonstrated.

More than 120 authors from science and industry have documented this essential resource for students, practitioners, and professionals. Comprehensively covering the development of the internal combustion engine (ICE), the information presented captures expert knowledge and serves as an essential resource that illustrates the latest level of knowledge about engine development. Particular attention is paid toward the most up-to-date theory and practice addressing thermodynamic principles, engine components, fuels, and emissions. Details and data cover classification and characteristics of reciprocating engines, along with fundamentals about diesel and spark ignition internal combustion engines, including insightful perspectives about the history, components, and complexities of the present-day and future IC engines.

The aim of this investigation is the improvement of the lateral vehicle dynamics by optimizing the rim width. For that purpose, the rim width is considered as a development tool and configured with regard to specified targets. Using a specifically developed method of simulation, the influence of the rim width is analysed within different levels - starting at the component level “tyre” and going up to the level of the whole vehicle. With the help of substantial simulations using a nonlinear two-track model, the dimensioning of the rim width is brought to an optimum. Based on both, tyre and vehicle measurements, the theoretical studies can be proved in practice. As a result, the rim width has a strong influence on the behaviour of the tyre as well as on the overall vehicle performance, which emphasises its importance as a potential development tool within the development of a chassis.

Precise three-dimensional dummy head trajectories during crash tests are very important for vehicle safety development. To determine precise trajectories with a standard deviation of approximately 5 millimeters, three-dimensional video analysis is an approved method. Therefore the tracked body is to be seen on at least two cameras during the whole crash term, which is often not given (e.g. head dips into the airbag). This non-continuity problem of video analysis is surmounted by numerical integration of differential un-interrupted electrical rotation and acceleration sensor signals mounted into the tracked body. Problems of this approach are unknown sensor calibration errors and unknown initial conditions, which result in trajectory deviations above 10 centimeters.

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 optimization of the flow field around new vehicle concepts is driven by aerodynamic and thermal demands. Even though aerodynamics and thermodynamics interact, the corresponding design processes are still decoupled. Objective of this study is to include a thermal model into the aerodynamic design process. Thus, thermal concepts can be evaluated at a considerably earlier design stage of new vehicles, resulting in earlier market entry. In a first step, an incompressible CFD code is extended with a passive scalar transport equation for temperature. The next step also accounts for buoyancy effects. The simulated development of the thermal boundary layer is validated on a hot flat plate without pressure gradient. Subsequently, the solvers are validated for a heated block with ground clearance: The flow pattern in the wake and integral heat transfer coefficients are compared to wind tunnel simulations. The main section of this report covers the validation on a full-scale production car.

In current research projects such as "Vehicle to Grid" (V2G), "Vehicle to Building" (V2B) or "Vehicle to Home" (V2H), plug-in vehicles are integrated into stationary energy systems. V2B or V2H therefore stands for intelligent networking between vehicles and buildings. However, in these projects the objective is mostly from a pure electric point of view, to smooth the load profile on a household level by optimized charging and discharging of electric vehicles. In the present paper a small energy system of this kind, consisting of a building and a vehicle, is investigated from a holistic point of view. Thermal as well as electrical system components are taken into account and there is a focus on reduction of overall energy consumption and CO₂ emissions. A predictive energy management is presented that coordinates the integration of a plug-in hybrid electric vehicle into the energy systems of a building. System operation is optimized in terms of energy consumption and CO₂ emissions.

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.

Electric vehicles differ from conventionally powered vehicles in terms of many characteristics that are directly relevant to the customer. The most evident ones are the total driving range, which is limited by the battery capacity, and the different acceleration behavior, which is directly influenced by the electric motor's torque characteristics. Furthermore, there are many other vehicle characteristics, such as lateral dynamics, that are also strongly influenced by electrification. For all customer-relevant vehicle characteristics, it is important to know the necessary and optimal fulfillments in order to plan and evaluate new electrified vehicle concepts. Correlation functions can be used to convert values for technical characteristics to normalized customer satisfaction fulfillments. To evaluate the quality of a vehicle concept during the development process, a parametric cost function is defined.