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The development of highly automated driving functions (AD) recently rises the demand for so called Fail-Operational systems for native driving functions like steering and braking of vehicles. Fail-Operational systems shall guarantee the availability of driving functions even in presence of failures. This can also mean a degradation of system performance or limiting a system’s remaining operating period. In either case, the goal is independency from a human driver as a permanently situation-aware safety fallback solution to provide a certain level of autonomy. In parallel, the connectivity of modern vehicles is increasing rapidly and especially in vehicles with highly automated functions, there is a high demand for connected functions, Infotainment (web conference, Internet, Shopping) and Entertainment (Streaming, Gaming) to entertain the passengers, who should no longer occupied with driving tasks.

A reliable environment perception is a requirement for safe automated driving. For evaluating and demonstrating the reliability of the vehicle’s environment perception, field tests offer testing conditions that come closest to the vehicle’s driving environment. However, establishing a reference ground truth in field tests is time-consuming. This motivates the development of a procedure for learning the vehicle’s perception reliability from fleet data without the need for a ground truth, which would allow learning the perception reliability from fleet data. In Berk et al. (2019), a method based on Bayesian inference to determine the perception reliability of individual sensors without the need for a ground truth was proposed. The model utilizes the redundancy of sensors to learn the sensor’s perception reliability. The method was tested with simulated data.

One main goal of the automotive industry is to reduce the aerodynamic drag of passenger vehicles. Therefore, a deeper understanding of the flow field is necessary. Time-resolved data of the flow field is required to get an insight into the complex unsteady flow phenomena around passenger vehicles. This data helps to understand the temporal development of wake structures and enables the analysis of the formation of vortical structures. Numerical simulations are an efficient method to analyze the time-resolved data of the unsteady flow field. The analysis of the steady and unsteady numerical data is only relevant for aerodynamic developments in the wind tunnel, if the predicted temporal evolving structures of a passenger vehicle’s simulated flow field correspond to the structures of the flow field in the wind tunnel. In this study, time-resolved measurements of the empty wind tunnel and a notchback passenger vehicle in the wind tunnel are conducted.

The performance of environment perceiving sensors such as e.g. lidar, radar, camera and ultrasonic sensors is safety critical for automated driving vehicles. Therefore, one has to assess the sensors’ performance to assure the automated driving system’s safety. The performance of these sensors is however to some degree sensitive towards adverse weather conditions. A challenge is to quantify the effect of adverse weather conditions on the sensor’s performance early in the development of an automated driving system. This challenge is addressed in this work for lidar sensors. The lidar equation was previously employed in this context to derive estimates of a lidar’s maximum range in different weather conditions. In this work, we present a stochastic simulation framework based on a probabilistic extension of the lidar equation, to quantify the effect of adverse rainfall conditions on a lidar’s raw detection performance.

Advanced safety features and new services in connected cars depend on the security of the underlying vehicle functions. Due to the interconnection with the outside world and as a result of being an embedded system a modern vehicle is exposed to both, malicious activities as faced by traditional IT world systems as well as physical attacks. This introduces the need for utilizing hardware-assisted security measures to prevent both kinds of attacks. In this paper we present a survey of the different classes of hardware security devices and depict their different functional range and application. We demonstrate the feasibility of our approach by conducting a case study on an exemplary implementation of a function-on-demand use case. In particular, our example outlines how to apply the different hardware security approaches in practice to address real-world security topics. We conclude with an assessment of today’s hardware security devices.

Minimizing the lap time for a given race track is the main target in racecar development. In order to achieve the highest possible performance of the vehicle configuration the mutual interaction at the level of assemblies and components requires a balance between the advantages and disadvantages for each design decision. Especially the major shift in the focus of racecar powerunit development to high efficiency powertrains is driving a development of lean boosted and rightsized engines. In terms of dynamic engine behavior the time delay from requested to provided torque could influence the lap time performance. Therefore, solely maximizing the full load behavior objective is insufficient to achieve minimal lap time. By means of continuous predictive virtual methods throughout the whole development process, the influence on lap time by dynamic power lags, e.g. caused by the boost system, can be recognized efficiently even in the early concept phase.

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.

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.

Driven by the growing internet and remote connectivity of automobiles, combined with the emerging trend to automated driving, the importance of security for automotive systems is massively increasing. Although cyber security is a common part of daily routines in the traditional IT domain, necessary security mechanisms are not yet widely applied in the vehicles. At first glance, this may not appear to be a problem as there are lots of solutions from other domains, which potentially could be re-used. But substantial differences compared to an automotive environment have to be taken into account, drastically reducing the possibilities for simple reuse. Our contribution is to address automotive electronics engineers who are confronted with security requirements. Therefore, it will firstly provide some basic knowledge about IT security and subsequently present a selection of automotive specific security use cases.

The increasing complexity of automotive functions which are necessary for improved driving assistance systems and automated driving require a change of common vehicle architectures. This includes new concepts for E/E architectures such as a domain-oriented vehicle network based on powerful Domain Control Units (DCUs). These highly integrated controllers consolidate several applications on different safety levels on the same ECU. Hence, the functions depend on a strictly separated and isolated implementation to guarantee a correct behavior. This requires middleware layers which guarantee task isolation and Quality of Service (QoS) communication have to provide several new features, depending on the domain the corresponding control unit is used for. In a first step we identify requirements for a middleware in automotive DCUs. Our goal is to reuse legacy AUTOSAR based code in a multicore domain controller.

Longitudinal models are used to evaluate different vehicle-engine concepts with respect to driving behavior and emissions. The engine is generally map-based. An explicit calculation of both fluid dynamics inside the engine air path and cylinder combustion is not considered due to long computing times. Particularly for dynamic certification cycles (WLTC, US06 etc.), dynamic engine effects severely influence the quality of results. Hence, an evaluation of transient engine behavior with map-based engine models is restricted to a certain extent. The coupling of detailed 1D-engine models is an alternative, which rapidly increases the model computation time to approximately 300 times higher than that of real time. In many technical areas, the Fourier transformation (FT) method is applied, which makes it possible to represent superimposed oscillations by their sinusoidal harmonic oscillations of different orders.

The open jet wind tunnel is a widespread test section configuration for developing full scale passenger cars in the automotive industry. However, using a realizable nozzle cross section for cost effective aerodynamic development is always connected to the presence of wind tunnel effects. Wind tunnel wall interferences which are not present under open road conditions, can affect the measurement of aerodynamic forces. Thus, wind tunnel corrections may be required. This work contains the results of a CFD (Computational Fluid Dynamics) approach using unsteady Delayed Detached Eddy Simulations (DDES) to evaluate wind tunnel interferences for open jet test sections. The Full Scale DrivAer reference geometry of the Technical University of Munich (TUM) using different rear end shapes has been selected for these investigations.

Automotive engineering processes are dynamic, iterative and driven by changes. Reasons for changes on development artifacts are manifold, but the result is a new evolution step which may influence all, some, or just a single development artifact. Consequently, research on impact analysis put forth approaches to assess the adverse effects of changes. However, understanding and implementing functional changes and its consequences in the safety domain is often aggravated by dependencies between different types of development artifacts, scattered in various (tool) formats. Safety properties may change depending on the type of a modification. Thereby, connected analyses like fault trees, Failure Modes and Effects Analysis (FMEA), and safety concepts cannot be reused easily if the artifacts on which they are based on are affected by changes. In this paper we suggest a new difference analysis approach which allows a (semi-)automated comparison of safety work products based on models.

The trend towards even more sophisticated driver assistance systems and growing automation of driving sets new requirements for the robustness and availability of the involved automotive systems. In case of an error, today it is still sufficient that safety related systems just fail safe or silent to prevent safety related influence of the driving stability resulting in a functional deactivation. But the reliance on passive mechanical fallbacks in which the human driver taking over control, being inevitable in such a scenario, is expected to get more and more insufficient along with a rising degree of driving automation as the driver will be given longer reaction time. The advantage of highly or even fully automated driving is that the driver can focus on other tasks than controlling the car and monitoring it’s behavior and environment.

In this work we extended the findings from a previous study by the authors on the mechanisms and influence factors of deposit formation in urea-based selective catalytic reduction systems (SCR) [1]. A broader range of operating conditions was investigated in detail. In order to quantify the boundary conditions of deposition, a representative set of deposits was studied during formation and decomposition. A box of heat resisting glass was equipped with a surrogate mixing element to monitor solidification timescales, temperatures and deposit growth. A chemical analysis of the deposits was performed using thermogravimetry. The depletion timescales of individual deposit components were systematically investigated. A moderate temperature increase to 350 °C was deemed sufficient to trigger fast decomposition of deposits formed below 250 °C.

Recent attempts to find energy-efficient thermal management systems for electric and plug-in hybrid electric vehicles have led to secondary loop systems as an alternative approach to meet dynamic heating and cooling demands and to reduce refrigerant charge. The choice of refrigerant for the primary refrigeration cycle is an important issue regarding the overall system performance. In this work, an HFC refrigerant (R-134a) and a natural refrigerant (R-744) are evaluated regarding a potential use in secondary loop systems. To meet the demands of R-744 cycles such as higher system pressure, most components have to be redeveloped. Nonetheless the use of the environmentally friendly refrigerant has advantages such as better applicability and performance in heat pump systems under cold ambient conditions.

In ride comfort as well as driving dynamics, the behavior of the vehicle is affected by several subsystems and their properties. When analyzing the suspension, especially the characteristics of the main spring and damper but also rubber bushings are of main importance. Still, the properties of the different components are dependent on the present operating conditions. Concerning rubber bushings, several effects have already been investigated, e.g. dependencies of the transfer function of frequency, amplitude or load history. In this context influences of changes in temperature are often neglected. However, in the following research, the focus specifically lies on determination and analysis of the temperature dependency of rubber bushings. For this purpose, initially the relationship between properties of pure rubber and rubber bushings is described, which serves as a basis for correlating respective temperature dependencies.

Today, body vibration energy of passenger cars gets dissipated by linear working shock absorbers. A new approach substitutes the damper of a passenger car by a cardanic gimbaled flywheel mass. The constructive design leads to a rotary damper in which the vertical movement of the wheel carrier leads to revolution of the rotational axis of the flywheel. In this arrangement, the occurring precession moments are used to control damping moments and to store vibrational energy. Different damper characteristics are achieved by different induced precession. From almost zero torque output to high torque output, this damper has a huge spread. Next to the basic principal, in this paper an integration in the chassis, including a constructive proposal is shown. A conflict with high torque and high angular velocity leads to a special design. Moreover concepts to deal with all vehicle situations like yawing, rolling and pitching are shown.

Starting from the USA and followed by the European Union, legal requirements concerning “Tire Pressure Monitoring Systems” (TPMS) for passenger cars and light trucks will be introduced in China as well and therefore in the third of the three largest automobile markets worldwide. Changes of pressure dependent physical tire properties such as dynamic roll radius and a certain tire eigenfrequency, which are included in the ESC-wheel speed signals, indicates pressure loss in an indirect manner. Systems with corresponding working principles are called “indirect Tire Pressure Monitoring System” (iTPMS). Since the tire is a structural element with varying characteristics according to the design parameters, the roll radius and frequency behavior due to pressure loss is variable as well. As a consequence, tires have to be evaluated regarding there compatibility to iTPMS during the vehicle development process.

Structural component testing is essential for the development process to have an early knowledge of the real world behaviour of critical structural components in crash load cases. The objective of this work is to show the development for a self-sufficient structural component test bench, which can be used for different side impact crash load cases and can reflect the dynamic behaviour, which current approaches are not able. An existing basic system is used, which includes pneumatic cylinders with a controlled hydraulic brake and was developed for non-structural deformable applications only (mainly occupant assessments). The system is extended with a force-distance control. The method contains the analysis of a whole vehicle FEM simulation to develop a methodology for controlled force transmission with the pneumatic cylinders for a structural component test bench.