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In vehicle NVH development, vibroacoustic simulations with Finite Element (FE) models are a common technique. The computational costs for these calculations are steadily rising due to more detailed modelling and higher frequency ranges. At the same time, the need for multiple evaluations of the same model with different input parameters, e.g., for uncertainty quantification, optimization, or robustness investigations, is also increasing. Therefore, it is crucial to reduce the computational costs in these cases. A common technique is to use surrogate models that replace the computationally intensive FE model to perform repeated evaluations. Several different methods in this area are well established, but with the continuous advancements in the field of machine learning, interesting new methods like the Gaussian Process (GP) regression arises as a promising approach.

Electrified vehicles are particularly quiet, especially at low speeds due to the absence of combustion noises. This is why there are laws worldwide for artificial driving sounds to warn pedestrians. These sounds are generated using a so-called Acoustic Vehicle Alerting System (AVAS) which must maintain certain minimum sound pressure levels in specific frequency ranges at low speeds. The creation of the sound currently involves an iterative and sometimes time-consuming process that combines composing the sound on a computer with measuring the levels with a car on an outside noise test track. This continues until both the legal requirements and the subjective demands of vehicle manufacturers are met. To optimize this process and reduce the measurement effort on the outside noise test track, the goal is to replace the measurement with a simulation for a significant portion of the development.

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.

Battery-electric vehicles (BEVs) require new chassis components, which are realized as mechatronic systems mainly and support more and more by-wire functionality. Besides better controllability, it eases the implementation of integrated control strategies to combine different domains of vehicle dynamics. Especially powertrain layouts based on electric in-wheel machines (IWMs) require such an integrated approach to unfold their full potential. The present study describes an integrated, longitudinal vehicle dynamics control strategy for a battery electric sport utility vehicle (SUV) with an electric rear axle based on in-wheel propulsion. Especially the influence of electronic brake force distribution (EBD) and torque blending control on the overall performance are discussed and demonstrated through experiments and driving cycles on public road and benchmarked to results of previous studies derived from [1].

The technology in the automotive industry is evolving rapidly in recent times. Thus, with the development of new technologies, the challenges are also ever-increasing from an Electromagnetic Interference and Susceptibility (EMI/EMC) perspective. A lot of the latest technologies in Adaptive Driver Assistance Systems (ADAS), which include Rear Drive Assist, Blind Spot Detection (BSD), Lane Change Assist (LCA) to name a few, and other features like Anti-Braking System (ABS), Emergency Brake Assist (EBD) etc. rely heavily on different types of sensors and their detection circuitry. In addition, a lot of other internal functions in the Engine Control Unit (ECU) also depend on such sensors’ functionalities. Thus, it becomes imperative to study the potential impact of higher field emissions on the immunity behaviour of the sensors.

The following paper aims to bring the topics of connected testing and emission measurements together. It is an introduction of connected bench testing with the aim to characterize brake particle emissions with a special focus on the impact of regenerative braking by simulating the real behavior of a premium BEV SUV. Such an approach combines the advantages of a brake dynamometer including an emission testing setup and a HiL setup to allow a much more precise testing of brake particle emissions under the impact of regen braking compared to the current recommendations of the Global Technical Regulation (GTR) on brake particle emissions. It is shown for the very first time, how interactions between the vehicle motion system work. The study includes one physical front brake corner as well as one physical rear brake corner. The regen functionalities are simulated by a real ESC-ECU which is the core of the HiL test setup.

Software complexity of vehicles is constantly growing especially with additional autonomous driving features being introduced. This increases the risk for bugs in the system, when the car is delivered. According to a car manufacturer, more than 90% of availability problems corresponding to Electronic Control Unit (ECU) functionality are either caused by software bugs or they can be resolved by applying software updates to overcome hardware issues. The main concern are sporadic errors which are not caught during the development phase since their trigger condition is too unlikely to occur or is not covered by the tests. For such systems, there is a need of safe and secure infield diagnosis. In this paper we present a tool software architecture with remote access, which facilitates standard read/write access, an efficient channel interface for communication and file I/O, and continuous trace.

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.

In addition to the low and high beam functions, some modern headlamps also have the option of switching on only section of the high beam. The so-called adaptive high beam is intended to increase the detection distance of objects and through that drastically improve the road safety. At the same time, this function does not increase the glare for oncoming or preceding traffic. This is enabled through switching the different segments of the high beam on or off, depending on which and where other road users are recognized by the front camera. This massively increases the use of the high beam, thus increasing road safety. In this study, the increase in the detection distance of objects on a straight line is statically investigated with a test person study. Furthermore, the glare of each of these three light functions is observed.

This paper covers research findings on digital projections on the road. Data is provided for the root cause analysis of non-existing distraction proven by several studies. The study describes if and in which geometrical space road projections are visible to other road traffic participants. Such participants can be e.g. oncoming, passing drivers or pedestrians standing aside the road. The paper data shows where projections are recognizable and assignable to the original intention of the projection. A grid was created to identify the areas where digital projections could be understood and where the digital projections were just illegible. A dominant factor is the grazing incidence. The photons are distributed over a larger area and only the driver’s view makes a virtual compression of the illuminated area in order to make the signals legible. The results show that distraction for other road participants is unlikely for any position outside very limited areas.

It has been shown that additional light signals are beneficial in the car 2 human communication. This study addresses detection, discomfort, brightness, recognition of intention and the perception of safety, of different symbols and dynamics used for communication. Splitted in two parts, the first use case is a lane crossing situation, where the car gives instructions to the pedestrian via an angular restricted external Human Machine Interface (eHMI) in the driver’s window. Results show that a symbol which blinks first and is then statically shown leads to fast and best detection. The intention of a red stop hand and green pedestrian is clearly understood. A combination of a near road-projection and the eHMI leads to confusion. An angle of 55° to 25° has been proven to be sufficient for displaying the information. In the second use case a cyclist is approaching the automated vehicle (AV) from behind and passes on a bicycle path.

The current automotive electronic and electrical (EE) architecture has reached a scalability limit and in order to adapt to the new and upcoming requirements, novel automotive EE architectures are currently being investigated to support: a) an Ethernet backbone, b) consolidation of hardware capabilities leading to a centralized architecture from an existing distributed architecture, c) optimization of wiring to reduce cost, and d) adaptation of service-oriented software architectures. These requirements lead to the development of Zonal EE architectures as a possible solution that require appropriate adaptation of used security mechanisms and the corresponding utilized hardware trust anchors. 1 The current architecture approaches (ECU internal and in-vehicle networking) are being pushed to their limits, simultaneously, the current embedded security solutions also seem to reveal their limitations due to an increase in connectivity.

The current development of automotive lighting strives towards more and more lighting installations on vehicles. Additionally, to that, manufacturers start animating these lighting installations as coming home or leaving home greetings from the car to the driver. In a previous paper we have shown, that these additional animations are in fact not distracting to other road users and when used correctly, e.g. in a sequential turn indicator, can be beneficial to the overall traffic safety. This study then aims to investigate the potential influence of illuminated logos on road safety. European lawmakers forbid the use of illuminated advertisements on vehicles to minimize the danger of distraction for other road users and thereby negatively influencing traffic safety. As of now, active illumination of the manufacturer’s logo is considered an advertisement.

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.

1. The present work introduces an approach for the analysis of the noise propagation behavior of mechatronic brake systems in modern passenger vehicles. While on the one hand, the number of features realized through the mechatronic brake system is strongly increasing; on the other hand, a continuous reduction of the overall vehicle interior noise level can be observed. This leads to an increase of interfering noise phenomena in the vehicle interior that customers might perceive as insufficient product quality. Therefore, noise elimination always plays an important role in vehicle development. The mechatronic brake system induces interfering noise that is transferred into the vehicle interior, differing from vehicle to vehicle and maneuver to maneuver. Supposedly, a wide frequency range, numerous components, and various branched transfer paths in the physical domains of airborne, structure-borne, and fluid-borne sound are involved in the noise propagation.

Two research fields are presented in this paper covering new lighting functions. In the first part, a study is presented that evaluates distraction by light animations. 41 test subjects were involved, and a situation was constructed with several traffic participants and an animated-light vehicle parked so as to be conspicuously within the test subjects’ view. 91% of the test subjects stated they felt little or no distraction or impairment from the light display on the parked car. 29% noticed something conspicuous about the test vehicle. 22% indicated they had noticed the car’s lights flashing as its central locking system was operating. Only 7%—three of the 41 participants—noticed the animations in addition to their traffic monitoring. Of these, two said they didn’t feel disturbed at all by the animations while the third found it only very slightly distracting. Nobody said the distraction or impairment was “neutral”, “little bit” or “strong”.

This paper explains why software for efficient model-based development is needed to improve the efficiency of automakers and suppliers when implementing solutions with next generation automotive embedded systems. The resulting synergies are an important contribution for the automotive industry to develop safer, smarter, and more eco-friendly cars. To achieve this, it requires implementations of algorithms for machine learning, deep learning and model predictive control within embedded environments. The algorithms’ performance requirements often exceed the capabilities of traditional embedded systems with a homogeneous multicore architecture and, therefore, additional computing resources are introduced. The resulting embedded systems with heterogeneous computing architectures enable a next level of safe and secure real-time performance for innovative use cases in automotive applications such as domain controllers, e-mobility, and advanced driver assistance systems (ADAS).

The reduction of vehicle exhaust particle emissions is a success story of European legislation. Various particle number (PN) counters and calibration procedures serve as tools to enforce PN emission limits during vehicle type approval (VTA) or periodical technical inspection (PTI) of in-use vehicles. Although all devices and procedures apply to the same PN-metric, they were developed for different purposes, by different stakeholder groups and for different target costs and technical scopes. Furthermore, their calibration procedures were independently defined by different stakeholder communities. This frequently leads to comparability and interpretation issues. Systematic differences of stationary and mobile PN counters (PN-PEMS) are well-documented. New, low-cost PTI PN counters will aggravate this problem. Today, tools to directly compare different instruments are scarce.

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.

Recently, vehicle networks have increased complexity due to the demand for autonomous driving or connected devices. This increasing complexity requires high bandwidth. As a result, vehicle manufacturers have begun using Ethernet-based communication for high-speed links. In order to deal with the heterogeneity of such networks where legacy automotive buses have to coexist with high-speed Ethernet links vehicle manufacturers introduced a vehicle gateway system. The system uses Ethernet as a backbone between domain controllers and CAN buses for communication between internal controllers. As a central point in the vehicle, the gateway is constantly exchanging vehicle data in a heterogeneous communication environment between the existing CAN and Ethernet networks. In an in-vehicle network context where the communications are strictly time-constrained, it is necessary to measure the delay for such routing task.