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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.

Intensive R&D is currently performed worldwide on hybrid and electric vehicles. For full electric vehicles the driving range is limited by the capacity of currently available batteries. If such a vehicle shall increase its driving range some range extending backup system should be available. Such a Range Extender is a small system of combustion engine and electric generator which produces the required electricity for charging the batteries in time. Since the acoustic response of an electric motor driving the vehicle and of a combustion engine as part of a Range Extender is very different by nature an extensive acoustic tuning of the Range Extender is necessary to meet the requirements of exterior vehicle noise and passenger comfort. This paper describes the NVH (noise, vibration & harshness) development work of a range extender within the AVL approach of an electrically driven passenger car with range extender.

Future automotive systems will be connected with other vehicles and information systems for improved road safety, mobility and comfort. This new connectivity establishes data and command channels between the internal automotive system and arbitrary external entities. One significant issue of this paradigm shift is that formerly closed automotive systems now become open systems that can be maliciously influenced through their communication interfaces. This introduces a new class of security challenges for automotive design. It also indirectly impacts the safety mechanisms that rely on a closed-world assumption for the vehicle. We present a new security analysis approach that helps to identify and prioritize security issues in automotive architectures. The methodology incorporates a new threat classification for data flows in connected vehicle systems.

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.

This paper presents a model-based approach to detect unintended acceleration (UA) as well as other vehicle problems. A diagnostic system is formulated by detecting several specific vehicle events such as acceleration peaks and gear shifting. Mathematical models are created for these events based on simulation data and the final diagnostic conclusion is drawn from the voting result of all these models. The detection algorithm is validated using independent data sets obtained from Matlab/Simulink. A three dimensional vehicle model is built to implement traffic simulation. Vehicle problems and drivers' reactions are simulated and added during the process. Sensor noise is also considered and corresponding filters are designed and applied. The results show that the fault diagnostic system is successful in detecting UA.

Global warming is the driver for introduction of CO2 and fuel consumption legislation worldwide. Indian truck manufacturers are facing the introduction of Indian fuel efficiency norms. In the European Union the CO2 emission monitoring phase of the most relevant truck classes was completed in June 2020 by usage of the Vehicle Energy Consumption Calculation TOol VECTO. Indian rule makers are currently considering an adaptation of VECTO for the usage in India, too. Indian truck market has always been very cost sensitive. Introduction of Bharat Stage VI Phase I has already led to a significant cost increase for emission compliance. Therefore, it will be of vital importance to keep the additional product costs for achievement of future fuel consumption legislation as low as possible as long as the real-world operation will not be promoted by the government.

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

This paper presents calculations of engine flows by using the Partially-Averaged Navier Stokes (PANS) method (Girimaji [1]; [2]). The PANS is a scale-resolving turbulence computational approach designed to resolve large scale fluctuations and model the remainder with appropriate closures. Depending upon the prescribed cut-off length (filter width) the method adjusts seamlessly from the Reynolds-Averaged Navier-Stokes (RANS) to the Direct Numerical Solution (DNS) of the Navier-Stokes equations. The PANS method was successfully used for many applications but mainly on static geometries, e.g. Basara et al. [3]; [4]. This is due to the calculation of the cut-off control parameter which requires that the resolved kinetic energy is known and this is usually obtained by suitably averaging of the resolved field. Such averaging process is expensive and impractical for engines as it would require averaging per cycles.

Grown interest in complex modern Hybrid Electric Vehicle (HEV) concepts has raised new challenges in the field of NVH. The switch between the Internal Combustion Engine (ICE) and the Electric Motor (EM) at low speeds produces undesirable vibrations and a sudden raise of noise levels that effects the sound quality and passenger comfort achieved by the close-to-silent electric powertrain operation. Starting the ICE in the most suitable driving situation to create a seamless transition between driving modes can be the key to minimize the NVH quality impact in driver and passenger’s perception in HEVs. To integrate this important aspect in the early stages of the development and design phase, simulation technologies can be used to address the customer acceptance. By analyzing NVH measurements, the different noise components of the vehicle operation can be separated into ICE-related noise, EM-related noise and driving noise.

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 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.

Reynolds-averaged Navier-Stokes (RANS) computations of heat transfer involving wall bounded flows at elevated Prandtl numbers typically suffer from a lack of accuracy and/or increased mesh dependency. This can be often attributed to an improper near-wall turbulence modeling and the deficiency of the wall heat transfer models (based on the so called P-functions) that do not properly account for the variation of the turbulent Prandtl number in the wall proximity (y+< 5). As the conductive sub-layer gets significantly thinner than the viscous velocity sub-layer (for Pr >1), treatment of the thermal buffer layer gains importance as well. Various hybrid strategies utilize blending functions dependent on the molecular Prandtl number, which do not necessarily provide a smooth transition from the viscous/conductive sub-layer to the logarithmic region.

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.

A catalyzed ceramic filter has been used on diesel engines for diesel particulate matter emission control. A key design criteria for a diesel particulate filter is to maximize DPF performance, i.e. low back pressure and compact size as well as near continuous regeneration operation. Based upon the modeling and deep understanding of material properties, a DPF system design has been successfully applied on a high performance diesel engine exhaust system, such as the Audi R10 TDI, the first diesel racing car that won the most prestigious endurance race in the world: the 24 hours of Le Mans in both 2006 and 2007. The design concept can be used for other materials and applications

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.

Limited battery power and poor engine efficiency at cold temperature results in low plug in hybrid vehicle (PHEV) fuel economy and high emissions. Quick rise of battery temperature is not only important to mitigate lithium plating and thus preserve battery life, but also to increase the battery power limits so as to fully achieve fuel economy savings expected from a PHEV. Likewise, it is also important to raise the engine temperature so as to improve engine efficiency (therefore vehicle fuel economy) and to reduce emissions. One method of increasing the temperature of either component is to maximize their usage at cold temperatures thus increasing cumulative heat generating losses. Since both components supply energy to meet road load demand, maximizing the usage of one component would necessarily mean low usage and slow temperature rise of the other component. Thus, a natural trade-off exists between battery and engine warm-up.

The presented paper deals with a methodology to model cycle-to-cycle variations (CCV) in 0-D/1-D simulation tools. This is achieved by introducing perturbations of combustion model parameters. To enable that, crank angle resolved data of individual cycles (pressure traces) have to be available for a reasonable number of engine cycles. Either experimental data or 3-D CFD results can be applied. In the presented work, experimental data of a single-cylinder research engine were considered while predicted LES 3-D CFD results will be tested in the future. Different engine operating points were selected - both stable ones (low CCV) and unstable ones (high CCV). The proposed methodology consists of two major steps. First, individual cycle data have to be matched with the 0-D/1-D model, i.e., combustion model parameters are varied to achieve the best possible match of pressure traces - an automated optimization approach is applied to achieve that.

The rate in the electrification of vehicles has risen in recent years. With intensified development more and more attention is paid to the noise and vibration in such vehicles especially from the EDU (Electric Drive Unit). In this paper the main NVH simulation process of a high-speed E-axle up to 30,000 rpm for premium class vehicle application is presented. The high speed, high-power density and lightweight design introduces new challenges. Benchmarking of different EDUs and vehicles leads to targets which can be used at the early stage of development as subsystem targets. This paper shows the CAE methodology which can be used to verify the design and guarantee the target achievement. Using CAE both source and structure can be optimized to improve the NVH behavior.

The automotive domain has seen safety engineering at the forefront of the industry’s priorities for the last decade. Therefore, additional safety engineering efforts, design approaches, and well-established safety processes have been stipulated. Today many connected and automated vehicles are available and connectivity features and information sharing are increasingly used. This increases the attractiveness of an attack on vehicles and thus introduces new risks for vehicle cybersecurity. Thus, just as safety became a critical part of the development in the late 20th century, the automotive domain must now consider cybersecurity as an integral part of the development of modern vehicles. Aware of this fact, the automotive industry has, therefore, recently taken multiple efforts in designing and producing safe and secure connected and automated vehicles.

Fuel cell electric vehicles are a promising technology to create CO2- neutral mobility. Model-based development approaches are key to reduce costs and to raise efficiencies. A model on vehicle system level is discussed that balances the need of physical depth and computational performance. The vehicle model comprises the domains of mechanics, electrics, thermodynamics, cooling and controls. Detailed models of the fuel cell and battery are presented as a part of the system model. The models apply electrochemical approaches and spatial resolutions up to 3D. The models of both components are validated via 3D reference simulations showing a seamless parameter transfer between system level and CFD-based simulations. The validity of the vehicle model, including the electrochemical components, is demonstrated by simulating the Toyota Mirai vehicle. Simulation results of an NEDC are compared to measurements.