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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 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.

A main challenge when developing next generation architectures for automated driving ECUs is to guarantee reliable functionality. Today’s fail safe systems will not be able to handle electronic failures due to the missing “mechanical” fallback or the intervening driver. This means, fail operational based on redundancy is an essential part for improving the functional safety, especially in safety-related braking and steering systems. The 2-out-of-2 Diagnostic Fail Safe (2oo2DFS) system is a promising approach to realize redundancy with manageable costs. In this contribution, we evaluate the reliability of this concept for a symmetric and an asymmetric Electronic Power Steering (EPS) ECU. For this, we use a Markov chain model as a typical method for analyzing the reliability and Mean Time To Failure (MTTF) in majority redundancy approaches. As a basis, the failure rates of the used components and the microcontroller are considered.

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.

Computational models directly derived from data gained increased interest in recent years. Data-driven approaches have brought breakthroughs in different research areas such as image-, video- and audio-processing. Often denoted as Machine Learning (ML), today these approaches are not widely applied in the field of vehicle Noise, Vibration and Harshness (NVH). Works combining ML and NVH mainly discuss the topic with respect to psychoacoustics, traffic noise, structural health monitoring and as improvement to existing numerical simulation methods. Vehicle interior noise is a major quality criterion for today’s automotive customers. To estimate noise levels early in the development process, deterministic system descriptions are created by utilizing time-consuming measurement techniques. This paper examines whether pattern-recognizing algorithms are suitable to conduct the prediction process for a steering system.

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 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 study of oil emission is of essential interest for the engine development of modern cars, as well as for the understanding of hydrocarbon emissions especially during cold start conditions. A laser mass spectrometer has been used to measure single aromatic hydrocarbons in unconditioned exhaust gas of a H2-fueled engine at stationary and transient motor operation. These compounds represent unburned oil constituents. The measurements were accompanied by FID and GC-FID measurements of hydrocarbons which represent the burned oil constituents. The total oil consumption has been determined by measuring the oil sampled by freezing and weighing. It has been concluded that only 10 % of the oil consumption via exhaust gas has burned in the cylinders. A correlation of the emission of single oil-based components at ppb level detected with the laser mass spectrometer to the total motor oil emission has been found.

Lightweighting of cars will remain one important goal for car producers. One milestone for lightweight technologies was the Audi Space Frame ASF‚. New generations of ASF cars will follow. Only the experience from the A 8 shows, which innovative technologies for these new generations will bring us one step forward. It's the combination of alloy modifications, innovative forming and joining technologies that leads into the future.

Temperature rise in traction contact areas is one important factor that influences traction coefficient. For examining the influence of temperature rise on the traction coefficient, it is necessary to first clarify temperature rise in the traction contact area. In this article, temperature rise in the traction contact areas is discussed in three major parts. First, measured temperature distributions on the traction contact surface under conditions of high rolling speed and minute amounts of sliding and spinning, such as those which are found in a toroidal CVT, using a twin-disc test machine and thin-film platinum sensors are shown. Second, the above experimental results are compared with results from a traction analysis program (REIB99). Characteristics of calculated results were qualitatively in good agreement with measured results.

It is the beginning of a new age: multicore technology from the PC desktop market is now also hitting the automotive domain after several years of maturation. New microcontrollers with two or more main processing cores have been announced to provide the next step change in available computing power while keeping costs and power consumption at a reasonable level. These new multicore devices should not be confused with the specialized safety microcontrollers using two redundant cores to detect possible hardware failures which are already available. Nor should they be confused with the heterogeneous multicore solutions employing an additional support core to offload a single main processing core from real-time tasks (e.g. handling peripherals).

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.

With increasing levels of driving automation, the perception provided by automotive environment sensors becomes highly safety relevant. A correct assessment of the sensors’ perception reliability is therefore crucial for ensuring the safety of the automated driving functionalities. There are currently no standardized procedures or guidelines for demonstrating the perception reliability of the sensors. Engineers therefore face the challenge of setting up test procedures and plan test drive efforts. Null Hypothesis Significance Testing has been employed previously to answer this question. In this contribution, we present an alternative method based on Bayesian parameter inference, which is easy to implement and whose interpretation is more intuitive for engineers without a profound statistical education. We show how to account for different environmental conditions with an influence on sensor performance and for statistical dependence among perception errors.

Headlamp performance has changed in the last 20 years significantly. Sealed beam lamps were replaced by VHAD, VOR and VOL types, but still the optical input in terms of tungsten filament based luminous flux remained more stable. With Xenon discharge lamps and now LED the performance of a headlamp may vary strongly and thus the optical performance. Various rating systems have been developed to assess the quality of lamps and light distribution, some based on laboratory based data, some based on static or dynamic street test drives with online measurements and assessments. Basic interest is to understand the performance of the light for a real driver. This article will discuss the influence parameters on achieving a repeatable and precise rating as well as the outer influence that creates glare and varying seeing distance. Mostly mechanical headlamp and car conditioning will influence the result as well as human factors like aiming precision and aiming tolerances.

The effectiveness of ADAS addressing property damage has an increasing impact on car manufacturers, insurers and customers, as accident avoidance or mitigation can lead to loss reduction. In order to obtain benefits, it is essential that ADAS primarily address monetarily relevant accident scenarios. Furthermore, sensor technologies and algorithms have to be configured in a way that relevant accident situations can be sufficiently avoided at reasonable system costs. A new methodology is developed to identify and configure monetarily effective parameters for ADAS during parking and maneuvering. ADAS parameters e.g. relevant accident scenarios, required crash avoidance speeds and different sensor layouts are analyzed and evaluated using a real-world in-depth accident database of insurance claims provided by Allianz Center for Technology and Allianz Automotive Innovation Center. For this purpose, a sensitivity analysis is conducted to identify most monetarily effective accident scenarios.

In times when automated driving is becoming increasingly relevant, dynamic simulators present an appropriate simulation environment to faithfully reproduce driving scenarios. A realistic replication of driving dynamics is an important criterion to immerse persons in the virtual environments provided by the simulator. Motion Cueing Algorithms (MCAs) compute the simulator’s control input, based on the motions of the simulated vehicle. The technical restrictions of the simulator’s actuators form the main limitation in the execution of these input commands. Typical dynamic simulators consist of a hexapod with six degrees of freedom (DoF) to reproduce the vehicle motion in all dimensions. Since its workspace dimensions are limited, significant improvements in motion capabilities can be achieved by expanding the simulator with redundant DoF by means of additional actuators.

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.

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.

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.

The infrastructure in modern cars is a heterogeneous and historically grown network of different field buses coupling different electronic control units (ECUs) from different sources. In the past years, the amount of ECUs in the network has rapidly grown due to the mushrooming of new functions which historically were mostly implemented on a one-ECU-per-function basis resulting in up to a hundred ECUs in fully equipped luxury cars. Additionally, new functions like parking assist systems or advanced chassis control functions are getting increasingly complex and require more computing power. These two facts add up to a complex challenge in development. The current trend to host several functions in single ECUs as integration platforms is one attempt to address this challenge. This trend is supported by the increased computing power of current and upcoming multi-core microcontrollers.