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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.

Trim materials are often used for vibroacoustic energy absorption purposes within vehicles. To estimate the sound impact at a driver’s ear, the substructuring approach can be applied. Thus, transfer functions are calculated starting from the acoustic source to the car body, from the car body to the trim and, finally, from the trim to the inner cavity where the driver is located. One of the most challenging parts is the calculation of the transfer functions from the car body inner surface to the bottom trim surface. Commonly, freely laying mass-spring systems (trims) are simulated with a fixed boundary and interface phenomena such as friction, stick-slip or discontinuities are not taken into consideration. Such an approach allows for faster simulations but results in simulations strongly overestimating the energy transfer, particularly in the frequency range where the mass-spring system’s resonances take place.

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 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.

The thermal operational safety (TOS) of a vehicle ensures that no component exceeds its critical temperature during vehicle operation. To enhance the current TOS validation process, a data-driven approach is proposed to predict maximum component temperatures of a new vehicle project by leveraging the historical thermal wind tunnel data from previous vehicle projects. The approach intends to support engineers with temperature predictions in the early phase and reduce the number of wind tunnel tests in the late phase of the TOS validation process. In the early phase, all measurements of the new vehicle project are predicted. In the late phase, a percentage of measurements with the test vehicle used for the model training and the remaining tests are predicted with the trained ML model. In a first step, data from all wind tunnel tests is extracted into a joint dataset together with metadata about the vehicle and the executed load case.

The NVH-development cycle of vehicle components often requires a source characterization separated from the vehicle itself, which leads to the implementation of test bench setups. In the context of frequency based substructuring and transfer path analysis, a component can be characterized using Blocked Forces. The following paper provides a comparison of methods between an acceleration-based in-situ and a new hybrid in-situ Blocked Force determination, using measurements of an artificially excited electric power steering (EPS). Under real-life conditions on a test rig, the acceleration-based in-situ approach often shows limitations in the lower frequency range, due to relatively bad signal-to-noise ratio at the indicator sensors, while delivering accurate results in the higher spectrum. Due to considerable loads on components in operation, the stiffness of the test-rig cannot be decreased arbitrarily.

In order to predict reality as accurately as possible leads to the fact that numerical models in automotive vibroacoustic problems become increasingly high dimensional. This makes applications with a large number of model evaluations, e.g. optimization tasks or uncertainty quantification hard to solve, as they become computationally very expensive. Engineers are thus faced with the challenge of making decisions based on a limited number of model evaluations, which increases the need for data-efficient methods and reduced order models. In this contribution, variational autoencoders (VAEs) are used to reduce the dimensionality of the vibroacoustic model of a vehicle body and to find a low-dimensional latent representation of the system.

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.

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 advancing electrification of the powertrain is giving rise to new challenges in the field of acoustics. Film capacitors used in power electronics are a potential source of high-frequency interfering noise since they are exposed to voltage harmonics. These voltage harmonics are caused by semiconductor switching operations that are necessary to convert the DC voltage of the battery into three-phase alternating current for an electrical machine. In order to predict the acoustic characteristics of the DC-link capacitor at an early stage of development, a multiphysical chain of effects has to be addressed to consider electrical and mechanical influences. In this paper, a new method to evaluate the excitation amplitude of film capacitor windings is presented. The corresponding amplitudes are calculated via an analytical strain based on electromechanical couplings of the dielectric within film capacitors.

Driving cycles are valuable tools for emissions calibration at engine and powertrain test beds. While generic velocity profiles were sufficient in the past, legislative changes and increasing complexity of powertrain and exhaust aftertreatment systems require a new approach: Realistically transient cycles - which include critical driving maneuvers and can be tailored to a specific powertrain configuration - are needed to optimize the emission behavior of the said powertrain. For the generation of realistic velocity profiles, the Markov chain approach has been widely used and described in literature. However, this approach, so far, has only been used to generate cycles that are statistically representative of a large database of real driving trips, which is typically not available during the early stages of development of a new powertrain.

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.

Service-oriented architectures (SOAs) are well-established solutions in the IT industry. Their use in the automotive domain is still on the way. Up to now, the automotive domain has taken advantage of service-oriented architectures only in the area of infotainment and not for systems with hard real-time requirements. However, applying SOA to such systems has just started but is missing suitable design and verification methodologies. In this context, we target to include the notion of model-based design to address fail-operational systems. As a result, a model-based approach for the development of fail-operational systems based on dynamic reconfiguration using a service-oriented architecture is illustrated. For the evaluation, we consider an example function of an automatically controlled braking system and analyze the reconfiguration time when the function fails.

Classical decentralized architectures based on large networks of microprocessor-based Electronic Control Units (ECU), namely those used in self-driving cars and other highly-automated applications used in the automotive industry, are becoming more and more complex. These new, high computational power demand applications are constrained by limits on energy consumption, weight, and size of the embedded components. The adoption of new embedded centralized electrical/electronic (E/E) architectures based on dynamically reconfigurable hardware represents a new possibility to tackle these challenges. However, they also raise concerns and questions about their safety. Hence, an appropriate evaluation must be performed to guarantee that safety requirements resulting from an Automotive Safety Integrity Level (ASIL) according to the standard ISO 26262 are met. In this paper, a methodology for the evaluation of dynamically reconfigurable systems based on centralized architectures is presented.