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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.

The Deep Orange program is a concept vehicle development program focused on providing hands-on experience in design, engineering, prototyping and production planning as part of students’ two-year MS graduate education. Throughout this project, the team was challenged to create innovative concepts during the ideation phase as part of building the running vehicle. This paper describes the usability studies performed on two of the vehicle concepts that require driver interaction. One concept is a human machine interface (HMI) that uses a holographic companion that can act as a concierge for all functions of the vehicle. After creating a prototype using existing technologies and developing a user interface controlled by hand gestures, a usability study was completed with older adults. The results suggest the input method was not intuitive. Participants demonstrated better performance with tasks using discrete hand motions in comparison to those that required continuous motions.

A key criterion for launching autonomous vehicles on real roads is the knowledge of their capability to ensure traffic safety. In contrast to ADAS, deriving this measure of safety is difficult to achieve as the functional scope of an autonomous driving function exceeds by far the one of ADAS. As a consequence, real-world testing solely is not sufficient enough to cover the required test volume. This assessment problem imposes new requirements on a valid test concept for automated driving. A possible solution represents simulation by enabling it to generate reliable test kilometers. As a first step, we discuss in this paper the feasibility of simulation frameworks to re-simulate a real-world test in certain scenarios. We will demonstrate that even with ground truth information of the vehicle odometry and corresponding environment model an acceptable accordance of functional behavior is not guaranteed.

The analysis of the acoustic behavior of flow fields has gained importance in recent years, especially in the automotive industry. The comfort of the driver is heavily influenced by the noise levels and characteristics, especially during long distance drives. Simulation tools can help to analyze the acoustic properties of a car at an early stage of the development process. This work focuses on the low-frequency sound effects, which can be a significant noise component under certain operating conditions. As a first step in the fluid-structure interaction workflow, the flow around a series-production vehicle is simulated, including passenger cabin and underhood flow. The complexity of this model poses extensive demands on the simulation software, concerning meshing, turbulence modeling and level of parallelism. We conducted a transient simulation of the compressible fluid flow, using a hybrid RANS/LES approach.

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.

The Deep Orange program immerses automotive engineering students into the world of an OEM as part of their 2-year graduate education. In support of developing the program’s seventh vehicle concept, the students studied the sponsoring brand essence, conducted market research, and made a heuristic assessment of competitor vehicles. The upfront research lead to the definition of target customers and setting vehicle level targets that were broken down into requirements to develop various vehicle sub-systems. The powertrain team was challenged to develop a scalable propulsion concept enabled by a common vehicle architecture that allowed future customers to select (at the point of purchase) among various levels of electrification best suiting their needs and personal desires. Four different configurations were identified and developed: all-electric, two plug-in hybrid electric configurations, and an internal combustion engine only.

Highly Automated Driving (HAD) opens up new middle-term perspectives in mobility and is currently one of the main goals in the development of future vehicles. The focus is the implementation of automated driving functions for structured environments, such as on the motorway. To achieve this goal, vehicles are equipped with additional technology. This technology should not only be used for a limited number of use cases. It should also be used to improve Active Safety Systems during normal non-automated driving. In the first approach we investigate the usage of machine learning for an autonomous emergency braking system (AEB) for the active pedestrian protection safety. The idea is to use knowledge of accidents directly for the function design. Future vehicles could be able to record detailed information about an accident. If enough data from critical situations recorded by vehicles is available, it is conceivable to use it to learn the function design.

As computational methodologies become more integrated into industrial vehicle pre-development processes the potential for high transient vehicle thermal simulations is evident. This can also been seen in conjunction with the strong rise in computing power, which ultimately has supported many automotive manufactures in attempting non-steady simulation conditions. The following investigation aims at exploring an efficient means of utilizing the new rise in computing resources by resolving high time-dependent boundary conditions through a series of averaging methodologies. Through understanding the sensitivities associated with dynamic component temperature changes, optimised boundary conditions can be implemented to dampen irrelevant input frequencies whilst maintaining thermally critical velocity gradients.

Within the pre-development phase of a vehicle validation process, the role of computational simulation is becoming increasingly prominent in efforts to ensure thermal safety. This gain in popularity has resulted from the cost and time advantages that simulation has compared to experimental testing. Additionally many of these early concepts cannot be validated through experimental means due to the lack of hardware, and must be evaluated via numerical methods. The Race Track Simulation (RTS) can be considered as the final frontier for vehicle thermal management techniques, and to date no coherent method has been published which provides an efficient means of numerically modeling the temperature behavior of components without the dependency on statistical experimental data.

Aerodynamic performance assessment of automotive shapes is typically performed in wind tunnels. However, with the rapid progress in computer hardware technology and the maturity and accuracy of Computational Fluid Dynamics (CFD) software packages, evaluation of the production-level automotive shapes using a digital process has become a reality. As the time to market shrinks, automakers are adopting a digital design process for vehicle development. This has elevated the accuracy requirements on the flow simulation software, so that it can be used effectively in the production environment. Evaluation of aerodynamic performance covers prediction of the aerodynamic coefficients such as drag, lift, side force and also lift balance between the front and rear axle. Drag prediction accuracy is important for meeting fuel efficiency targets, prediction of front and rear lifts as well as side force and yawing moment are crucial for high speed handling.

Evaluation of safety benefits is an essential task during design and development of pedestrian protection systems. Comparative evaluation of different safety concepts is facilitated by a common metric taking into account the expected human benefits. Translation of physical characteristics of a collision, such as impact speed, into human benefits requires reliable and preferably evidence-based injury models. To this end, the dependence of injury severity of body regions on explanatory factors is quantified here using the US Pedestrian Crash Data Study (PCDS) for pedestrians in frontal vehicle collisions. The explanatory and causal factors include vehicle component characteristics, physiological and biomechanical variables, and crash parameters. Severe to serious injuries most often involve the head, thorax and lower extremities.

This paper presents an integrated simulation process which has been performed in order to assess the riding comfort performance of a vehicle seat system virtually. Present methods of seat comfort design rely on the extensive testing of numerous hardware prototypes. In order to overcome the limitations of this expensive and time-consuming process, and to fasten innovation, simulation-based design has to be used to predict the seat comfort performance very early in the seat design process, leading to a drastic reduction in the number of physical prototypes. The accurate prediction of the seat transfer function by numerical simulation requires a complete simulation chain, which takes into account the successive stages determining the final seat behaviour when submitted to vibrations. First the manufacturing stresses inside the cushion, resulting from the trimming process, are computed.

The trend in the previous years showed that an ideal product is not obtained as a sum of development results of several separated disciplines but rather as a result of a holistic multidisciplinary CAE approach. In the course of the whole component development process it is necessary to consider all functions of an individual component equivalent to their importance in the system as a whole, in order to achieve both a technical and a financial optimum. The predictability and the accuracy of an individual computational method have to be regarded against the background of the entire simulation process. A continuative CAE-standard and a harmonious interaction between the different computational disciplines promise more success than focusing specifically on individual topics and thereby neglecting the “bigger picture”. This awareness provided the basis for a decision to change the entire crash simulation software to ABAQUS.

As the popularity of vehicle navigation systems rises, incorporating Real Time Traffic Information (RTTI) has been shown to enhance the systems' value by helping drivers avoid traffic delays. As an innovative premium automaker, BMW has developed a testing process to acquire and analyze RTTI data in order to ensure delivery of a high quality service and to enhance the customer experience compared to audible broadcast services. With a methodology to obtain valid and repeatable RTTI data quality measurements, BMW and its service partner, Clear Channel's Total Traffic Network (TTN), can improve its offered service over time, implement corrective measures when appropriate, and confidently ensure the service meets its premium objectives. BMW has partnered with TTN and SoftSolutions GmbH to implement a traffic data quality process and software tools.

For car manufacturers, seating comfort is becoming more and more important in distinguishing themselves from their competitors. There is a simultaneous demand for shorter development times and more comfortable seats. Comfort in automobile seats is a multi-dimensional and complex problem. Many current sophisticated measuring tools were consulted, but it is unclear on which factors one should concentrate attention when measuring comfort. The goal of this paper is to find a model in order to predict the overall seating discomfort based on body area ratings. Besides micro climate, the pressure distribution appears to be the most objective measure comprising with the clearest association with the subjective ratings. Therefore an analysis with three different test series was designed, allowing the variation of pressure on the seat surface. In parallel the subjects were asked to judge the local and the overall sensation.

Being able to integrate consumer electronics (CE) devices into the automobile is an increasingly important goal. In this paper, we focus on the HMI (human machine interaction) aspects of consumer electronics in the car. We describe the requirements concerning HMI integration of consumer electronics and offer several possible solutions. One of the requirements is minimal driver distraction. A desired property in this context concerns the mental model that the user builds of the service that is to be operated: ideally, this model (i.e., appearance and interaction logic) need not change when integrating the service into the automobile, even though the operating elements differ considerably (e.g., touch screen vs. iDrive commander). A further requirement is posed by the dynamic nature of CE services: often, they are not known at design/deploy time of the HMI software of the automobile.

Comfort and well-being have always been connected with a flawless interior acoustic, free of any background noise or BSR, (buzz, squeak and rattle). BSR noises dominate the interior acoustic and represent one of the main sources for discomfort often causing considerable warranty costs. Traditionally BSR issues have been identified and rectified through extensive hardware testing, which by its nature intensifies toward the end of the car development process. In the following paper the integration of a virtual BSR validation technique in a modern development process by the use of appropriate CAE methods is presented. The goal is to shift, in compliance with the front loading concept, the development activities into the early phase. The approach is illustrated through the example of an instrument panel, from the early concept draft for single components to an assessment of the complete assembly.

Efficiency and dynamic behavior of a vehicle are strongly affected by its weight. Taking into consideration comfort, safety and emissions in modern automobiles, lightweight design is more of a challenge than ever in automotive engineering. Materials development plays an important role against this background, since significant weight decrease is made possible through the substitution of high density materials and more precise adjustment of material parameters to the functional requirements of components. Reinforced light metals, therefore, offer a promising approach due to their high strength to weight ratio. The paper gives an overview on matrix and reinforcement structures suited for the high volume output of the automotive industry. Further analytical and numerical approaches to describe the strengthening effects and the good mechanical characteristics of these composite materials are presented.

Advanced Driver Assistance systems support the driver in his driving tasks. They can be designed to enhance the driver's performance and/or to take over unpleasant tasks from the driver. An important optimization goal is to maintain the driver's activation at a moderate level, avoiding both stress and boredom. Functions requiring a situational interpretation based on the vehicle environment are associated with lower performance reliability than typical stability control systems. Thus, driver assistance systems are designed assuming that drivers will monitor the assistance function while maintaining full control over the vehicle, including the opportunity to override as required. Advanced driver assistance systems have a substantial potential to increase active safety performance of the vehicle, i.e., to mitigate or avoid traffic accidents.

Reductions of hardware costs as well as implementations of new innovative functions are the main drivers of today's automotive electronics. Indeed more and more resources are spent on adapting existing solutions to different environments. At the same time, due to the increasing number of networked components, a level of complexity has been reached which is difficult to handle using traditional development processes. The automotive industry addresses this problem through a paradigm shift from a hardware-, component-driven to a requirement- and function-driven development process, and a stringent standardization of infrastructure elements. One central standardization initiative is the AUTomotive Open System ARchitecture (AUTOSAR). AUTOSAR was founded in 2003 by major OEMs and Tier1 suppliers and now includes a large number of automotive, electronics, semiconductor, hard- and software companies.