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In order to correctly predict the impact of tire dimensions and properties on ride comfort in the early phases of the vehicle development process, it is necessary to fully understand their influence on the dynamic tire behavior. The currently existing models for reproducing tire forces often need many measurements for parametrization, simplify physical properties by empiric functions, or have an insufficient simulation speed to analyze many variants in the short periods of early process phases. In the following analysis, a tire concept model is presented, which utilizes relations between the static and dynamic behavior of tires in order to efficiently predict the dynamic forces in the vertical and longitudinal direction during obstacle crossing. The model allows for efficient parametrization by minimizing the number of parameters as well as measurements and ensures a high simulation speed. To realize this, initially, a selection of tires is measured on a tire test rig.

Open jet wind tunnels are normally tuned to measure “correct” results without any modifications to the raw data. This is an important difference to closed wall wind tunnels, which usually require wind tunnel corrections. The tuning of open jet facilities is typically done experimentally using pilot tunnels and adding final adjustments in the commissioning phase of the full scale tunnel. This approach lacked theoretical background in the past. There is still a common belief outside the small group of people designing and using open jet wind tunnels, that - similar to closed wind tunnels, which generally measure too high aerodynamic forces and moments without correction - open jet wind tunnels measure coefficient too low compared to the real world. The paper will try to show that there is a solid physical foundation underlying the experimental approach and that the expectation to receive self-correcting behavior can be supported by theoretical models.

The interaction between cooling-air and external aerodynamics is known as interference. In a conventional car this interference under the hood results in additional drag. It is estimated that about 10% of the overall aerodynamic drag originates from the cooling air [1] depending on the car shape and cooling configuration. Obviously, cooling drag should be minimized for vehicles with low-drag aerodynamics. In this study cooling-air interference-effects are investigated through experimental, numerical and analytical methods with a focus on the surface pressure of the vehicle. The surface pressure of vehicles with and without interference effects is compared. Observations show that when the cooling-air inlet is opened a pressure rise occurs around the inlet, while a pressure drop appears around the outlet. This phenomenon was investigated for several vehicle shapes including a simplified bluff-body (SAE-Body) and a close-to-real quarter-scale model (aeromodel).

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.

A wide-ranging investigation into the sensitivity of the hybrid RANS-LES based OpenFOAM CFD process at Audi was undertaken. For a range of cars (A1, TT, Q3 & A4) the influence of the computational grid resolution, turbulence model formulation and spatial & temporal discretization is assessed. It is shown that SnappyHexMesh, the Cartesian-prismatic built-in OpenFOAM mesher is unable to generate low y+ grids of sufficient quality for the production Audi car geometries. For high y+ grids there was not a consistent trend of additional refinement leading to improved correlation between CFD and experimental data. Similar conclusions were found for the turbulence models and numerical schemes, where consistent improvements over the baseline setup for all aerodynamic force coefficients were in general not possible. The A1 vehicle exhibited the greatest sensitivity to methodology changes, with the TT showing the least sensitivity.

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.

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.

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.

The SCR after treatment system is already in production for passenger car engines with a single exhaust system. In this case, the exhaust system has to be designed very carefully to optimize the Ammonia distribution on the catalyst and therefore the DeNOx potential. The application to V8 engines with two turbochargers delivering the gas into two separated DOC & DPF units is an additional challenge. This paper describes the different optimization steps of such an exhaust system and the tools used during this work. After a design phase to integrate the SCR system in the exhaust geometry, a first CFD study was conducted to evaluate the performance of the basic system using one or two urea injectors. An optimization of the connection of the two tubes, directly in front of the SCR catalyst, has been designed using further CFD calculations as well as a marker gas SF6 on a cold flow bench.

E-mobility is a game changer for the automotive domain. It promises significant reduction in terms of complexity and in terms of local emissions. With falling prices and recent technological advances, the second generation of electric vehicles (EVs) that is now in production makes electromobility an affordable and viable option for more and more transport mission (people, freight). Current e-vehicle platforms still present architectural similarities with respect to combustion engine vehicle (e.g., centralized motor). Target of the European project EVC1000 is to introduce corner solutions with in-wheel motors supported by electrified chassis components (brake-by-wire, active suspension) and advanced control strategies for full potential exploitation. Especially, it is expected that this solution will provide more architectural freedom toward “design-for-purpose” vehicles built for dedicated usage models, further providing higher performances.

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.

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.

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.

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 paper describes the integration of Complexity Management into the design cycle of an Automobile Manufacturer. It explains the reasons why most Automobile Manufacturers lack effective processes of dealing with complexity issues and introduces a holistic methodology for systematic and successful avoidance and control of unnecessary complexity. The paper provides an overview on the methods and tools necessary for the successful application of the above principle and is based on the experiences made with the implementation of the concept into the Audi AG product development process.

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.

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.

In the production of brake disc pads, powder mixes containing, metal chips, filling agents, and abrasive materials, as well as phenolic resins are processed and molded to a back plate by way of pressure and temperature. These molded disc pads reach their final strength through additional thermal treatment such that the phenolic resins approach “full cure”. This production process leads to anisotropic, viscoelastic, and to a certain extent heterogeneous materials which are - like the brake system- increasingly subject to even greater demands. E.g. apart from tribological characteristics, more and more focus is placed on structure-mechanical properties to improve the braking comfort.

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.

In recent years, we see more and more ECUs integrating a huge number of application software components. This process mostly results from the increasing amount of so called in-house software in various fields like electric-drive, chassis and driver assistance systems. The software development for these systems is partially moved from the supplier to the car manufacturers. Another important trend is the introduction of new network architectures intending to meet the growing communication requirements. For such ECUs the software integration scenarios become more complicated, as more quality of service requirements with regards to timing, safety and security need to be considered [2]. Multi-core microcontrollers offer even more potential variants for integration scenarios. Understanding the interaction between the different software components, not only from a functional, but also from a timing view, is a key success factor for modern electronic systems [6,7,8,9].