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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.

The BMW Group has introduced electric cars to the market with the MINI E already in 2009. The next step will be the launch of the BMW ActiveE in 2011, followed by the revolutionary Mega City Vehicle in 2013. The presentation will explain the BMW Group strategy for implementing sustainable mobility. A focus will be emobility, the use of carbon fiber and the holistic sustainability approach of BMW Group?s project i. Reference will be made to the research results of the MINI E projects in the US and in Europe. Presenter Andreas Klugescheid, BMW AG

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.

A state of the art proprietary method for aluminum-to-aluminum joining in the automotive industry is Resistance Spot Welding. However, with spot welding (1) structural performance of the joint may be degraded through heat-affected zones created by the high temperature thermal joining process, (2) achieving the double-sided access necessary for the spot welding electrodes may limit design flexibility, and (3) variability with welds leads to production inconsistencies. Self-piercing rivets have been used before; however they require different rivet/die combinations depending on the material being joined, which adds to process complexity. In recent years the introductions of screw products that combine the technologies of friction drilling and thread forming have entered the market. These types of screw products do not have these access limitations as through-part connections are formed by one-sided access using a thermo-mechanical flow screwdriving process with minimal heat.

Dedicated Short Range Communications (DSRC) for vehicle-to-vehicle (V2V) cooperative applications for advanced safety is becoming a reality. Many automotive manufactures are entering advanced research phases or even planning deployments of such applications in the near future. However, the success of most V2V applications requires full or near-full deployment of the DSRC devices in new and existing vehicles, which will take many years to accomplish. In the meantime, use of autonomous sensors in combination with V2V can augment this deployment transitional period. In this paper we propose a hybrid approach that uses autonomous sensors to rebroadcast information about unequipped neighboring vehicles. In addition to messages that a host vehicle sends about its own state (such as position, speed, and direction), additional sensing capabilities also allow sending information about neighboring vehicles. This information can be obtained from radars, cameras and other autonomous sensors.

Ablation casting is an emerging technology which combines traditional sand molding techniques with rapid cooling due to the use of a water soluble binder. High cooling rates and control of solidification direction allows for exceptional mechanical properties and complex shapes. Through the use of ablation, six different body node castings have been manufactured for the 2016 NSX aluminum space frame. The high mechanical properties allowed these castings to be integrated into the crash structure for energy absorption. Using the traditional casting alloy A356, target mechanical properties were 190 Mpa Yield Strength, 280 Mpa Tensile Strength and 12% min elongation. The high elongation was achieved due to the refined eutectic microstructure produced by high cooling rates. The eutectic microstructure produced by ablation was found to be Level 5 or 6 on the AFS scale. Light weighting could also be achieved when compared to traditional GDC castings.

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.

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

In this research, a three degree-of-freedom (DOF) rack-type electric-based power steering (EPS) model is developed. The model is coupled with a three DOF vehicle model and includes EPS maps as well as non-linear attributes such as vibration and friction characteristics of the steering system. The model is simulated using Matlab's Simulink. The vibration levels are quantified using on-vehicle straight-line test data where strain-gauge transducers are placed in the tie-rod ends. Full vehicle kinematic and compliance tests are used to verify the total steering system stiffness levels. Frequency response tests are used to adjust tire cornering stiffness levels as well as the tire dynamic characteristics such that vehicle static gain and yaw natural frequency are achieved. On-center discrete sinusoidal on-vehicle tests are used to further validate the model.

A method of predictive simulation of flow-induced noise using computational fluid dynamics has been developed. The goal for the developed method was application in the vehicle development process, and the target of the research was therefore set as balancing the realization of a practical level of predictive accuracy and a practical computation time. In order to simulate flow-induced noise, it is necessary to compute detailed eddy flows and changes in the density of the air. In the research discussed in this paper, the occurrence or non-occurrence of flow-induced noise was predicted by conducting unsteady compressible flow calculation using large eddy simulation, a type of turbulence model. The target flow-induced noise for prediction was narrow-band noise, a type of noise in which sound increases in specific frequency ranges.

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.

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.

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.

A new hydrogen fueling protocol named MC Formula Moto was developed for fuel cell motorcycles (FCM) with a smaller hydrogen storage capacity than those of light duty FC vehicles (FCV) currently covered in the SAE J2601 standard (over than 2kg storage). Building on the MC Formula based protocol from the 2016 SAE J2601 standard, numerous new techniques were developed and tested to accommodate the smaller storage capacity: an initial pressure estimation using the connection pulse, a fueling time counter which begins the main fueling time prior to the connection pulse, a pressure ramp rate fallback control, and other techniques. The MC Formula Moto fueling protocol has the potential to be implemented at current hydrogen stations intended for fueling of FCVs using protocols such as SAE J2601. This will allow FCMs to use the existing and rapidly growing hydrogen infrastructure, precluding the need for exclusive dispensers or stations.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

Good lighting is crucial for safe driving at night. Unfortunately, many parameters are contributing to the final result of the individual tolerances of car body, dynamics and headlamp: the resulting aim. The paper will analyze individual tolerance contributors from car body parameters like load, tire pressure, suspension as well as temperature parameters of chassis and plastic parts. The investigation shows that the headlight aim can fluctuate in a worst case scenario more than ±0.3°.