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The following paper aims to bring the topics of connected testing and emission measurements together. It is an introduction of connected bench testing with the aim to characterize brake particle emissions with a special focus on the impact of regenerative braking by simulating the real behavior of a premium BEV SUV. Such an approach combines the advantages of a brake dynamometer including an emission testing setup and a HiL setup to allow a much more precise testing of brake particle emissions under the impact of regen braking compared to the current recommendations of the Global Technical Regulation (GTR) on brake particle emissions. It is shown for the very first time, how interactions between the vehicle motion system work. The study includes one physical front brake corner as well as one physical rear brake corner. The regen functionalities are simulated by a real ESC-ECU which is the core of the HiL test setup.

The presentation describes the aerodynamic development and optimization process of the three different new models of the Audi A6/A7 family. The body types of these three models represent the three classic aerodynamic body types squareback, notchback and fastback. A short introduction of the flow structures of these different body types is given and their effect on the vehicle aerodynamic is described. In order to achieve good aerodynamic performance, the integration into the development process of the knowledge about these flow phenomena and the breakdown of the aerodynamic resistance into its components friction- and pressure drag as well as the induced drag is very important. The presentation illustrates how this is realized within the aerodynamic development process at Audi. It describes how the results of CFD simulations are combined with wind tunnel measurements and how the information about the different flow phenomena were used to achieve an aerodynamic improvement.

The paper describes the aerodynamic development and optimization process of the three different new models of the Audi A6/A7 family. The body types of these three models represent the three classic aerodynamic body types squareback, notchback and fastback. A short introduction of the flow structures of these different body types is given and their effect on the vehicle aerodynamic is described. In order to achieve good aerodynamic performance, the integration into the development process of the knowledge about these flow phenomena and the breakdown of the aerodynamic resistance into its components friction- and pressure drag as well as the induced drag is very important. The paper illustrates how this is realized within the aerodynamic development process at Audi. It describes how the results of CFD simulations are combined with wind tunnel measurements and how the information about the different flow phenomena were used to achieve an aerodynamic improvement.

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.

The use of a newly developed approach results in a highly accurate three dimensional analysis of the occupant movement. The central point of the new method is the calculation of precise body-trajectories by fitting standard sensor-measurements to video analysis data. With the new method the accuracy of the calculated trajectories is better than 5 to 10 millimeters. These body trajectories then form the basis for a new multi-body based numerical method, which allows the three dimensional reconstruction of the dummy kinematics. In addition, forces and moments acting on every single body are determined. In principle, the body movement is reconstructed by prescribing external forces and moments to every single body requiring that it follows the measured trajectory. The newly developed approach provides additional accurate information for the development engineers. For example the motion of dummy body parts not tracked by video analysis can be determined.

To produce an appealing ambient interior lighting design, the illumination inside a car is generated by diffuse reflections at the surfaces of the interior. So the complete illumination set can be determined by using all light sources and the attributes of the surface materials of the interior geometry. Normally, the early concept phase of the car is ideally to integrate the interior lighting in the styling of the car. But in this phase it is nearly impossible to measure and optimize the interior light due to continuous changes in car interior styling. An approach of simulating the diffuse illumination situation of car interior by using a radiosity method is presented. Then the results of the radiosity calculation are prepared in order to use them in a virtual reality environment. First the physical basics and their numerical implementation are shown. Then the material attributes, which are essential for calculation and their measurement based on real materials, are presented.

The question of the proper simulation of wheel rotation has not so far been a major concern. Within the scope of an examination of the influence of wheels and tyres on aerodynamic drag it will be shown that their contribution to the overall drag value - whether they are rotating or not - is of about the same magnitude as the proportion of the rough underbody. Therefore the question of the importance of the simulation of wheel rotation is posed. This paper discusses how a measurement with a better simulation can look like and what the major changes in the flow field are. In particular a new physical quantity, which has to be determined, the so-called “fan moment” is introduced. . The problems that arise in the determination of the fan moment of the wheels and hence in the required isolation of the rolling resistance, are described in detail. This is done for a test set up with full width moving belt and measurement via internal balance and sting support.

The ridemeter is a development tool that provides a predictive value for subjectively perceived ride quality on the basis of objective measured values. After years of preliminary investigations it was possible to make the link between the subjective driving experience and objective measured data. Intensive validation of the tool known as the ridemeter enables it to obtain meaningful results, which meet with a high degree of acceptance from the development engineer. The ridemeter is capable of providing calculated assessments for different vehicle concepts on different roads. The ridemeter is used on general road tests, on test runs on the AUDI proving ground, on our test rigs and in simulation. Areas of application include benchmark investigations, optimisation steps for suspension components and systems, and the setting out of limit values and tolerance curves in specifications for future vehicles.

The improved performance of heavy-duty vehicles as transport carriers is essential for economic reasons and to fulfil new emission standards in Europe. A key parameter is the aerodynamic vehicle drag. An enormous potential still exists for fuel saving and reducing exhaust emission by aerodynamic optimisation. Engineering methods are required for developments in vehicle aerodynamics. To assess the reliability of the most common experimental testing and numerical simulation methods in the industrial design process is the objective of this article. Road tests have been performed to provide realistic results, which are compared to the results obtained by scale-model wind tunnel experiments and time-averaged computational fluid dynamics (CFD). These engineering methods are evaluated regarding their deployment in the industrial development process. The investigations focus on the separated flow region behind the vehicle rear end.

For integrating Life Cycle Assessment into the design process it is more and more necessary to generate models of single life cycle steps respectively manufacturing processes. For that reason it is indispensable to develop parametric processes. With such disposed processes the aim could only be to provide a tool where parametric environmental process models are available for a designer. With such a tool and the included models a designer will have the possibility to make an estimation of the probable energy consumption and needed additive materials for the applied manufacturing technology. Likewise if he has from the technical point of view the opportunity, he can shift the applied joining technology in the design phase by changing for instance the design.

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.

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.

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.

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 deposition behavior of brake wear particles on the surface of a wheel and the mechanisms on it have not been fully understood. In addition, the proportion of brake wear particles deposited on the wheel surface compared to the total emitted particles is almost unknown. This information is necessary to evaluate the number- and mass-related emission factors measured on the inertia dynamometer and to compare them with on-road and vehicle-related emission behaviour. The aim of this study is to clarify the deposition behavior of brake particles on the wheel surface. First, the real deposition behaviour is determined in on-road tests. For particle sampling, collection pads are adapted at different positions of a front and rear axle wheel. In addition to a Real Driving Emissions (RDE)-compliant test cycle, tests are performed in urban, rural and motorway sections to evaluate speed-dependent influences.

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 extended steady state lap time simulation combines a quasi steady state approach with a transient vehicle model. The transient states are treated as distance dependent parameters during the calculation of the optimal lap by the quasi steady state method. The quasi steady state result is used afterwards to calculate a new dynamic behavior, which induces in turn a different quasi steady state solution. This iteration between the two parts is repeated until the dynamic states have settled. An implementation of the extended quasi steady state simulation is built up to determine the capabilities of the approach. In addition to pure steady state simulation abilities, the method is able to judge the influence of the transient or time variant vehicle states on lap time. Sensitivity studies are generated to analyze the influence of basic parameters like mass, but also the influence of parameters with transient interaction like vertical damping or tire temperature.

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.

Wheels on passenger vehicles cause about 25% of the aerodynamic drag. The interference of rims and tires in combination with the rotation result in strongly turbulent wake regions with complex flow phenomena. These wake structures interact with the flow around the vehicle. To understand the wake structures of wheels and their impact on the aerodynamic drag of the vehicle, the complexity was reduced by investigating a standalone tire in the wind tunnel. The wake region behind the wheel is investigated via Particle Image Velocimetry (PIV). The average flow field behind the investigated wheels is captured with this method and offers insight into the flow field. The investigation of the wake region allows for the connection of changes in the flow field to the change of tires and rims. Due to increased calculation performance, sophisticated computational fluid dynamics (CFD) simulations can capture detailed geometries like the tire tread and the movement of the rim.