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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.

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.

The quiet nature of hybrid and electric vehicles has triggered developments in research, vehicle manufacturing and legal requirements. Currently, three countries require fitting an Approaching Vehicle Alerting System (AVAS) to every new car capable of driving without a combustion engine. Various other geographical areas and groups are in the process of specifying new legal requirements. In this paper, the design challenges in the on-going process of designing the sound for quiet cars are discussed. A proposal is issued on how to achieve the optimum combination of safety, environmental noise, subjective sound character and technical realisation in an iterative sound design process. The proposed sound consists of two layers: the first layer contains tonal components with their pitch rising along with vehicle speed in order to ensure recognisability and an indication of speed.

Efforts in aerodynamic optimization of road vehicles have been steadily increasing in recent years, mainly focusing on the reduction of aerodynamic drag. Of a car's total drag, wheels and wheel houses account for approx. 25 percent. Consequently, the flow around automotive wheels has lately been investigated intensively. Previously, the authors studied a treaded, deformable, isolated full-scale tire rotating in contact with the ground in the wind tunnel and using the Lattice-Boltzmann solver Exa PowerFLOW. It was shown that applying a common numerical setup, with velocity boundary condition prescribed on the tread, significant errors were introduced in the simulation. The contact patch separation was exaggerated and the flow field from wind tunnel measurements could not be reproduced. This investigation carries on the work by examining sensitivities and new approaches in the setup.

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.

Over the past 30 years, the computer-aided engineering (CAE) tools have been applied extensively in the automotive industry. In order to accelerate time-to-market while coping with legal limits that have become increasingly restrictive over the last decades, CAE has become an indispensable tool covering all major fields in a modern automotive product design process. However, when tackling complex real-life engineering problems, the computational models might become rather involved and thus less efficient. Therefore, the overall trend in the automotive industry is currently heading towards combined approaches, which allow the best of the both worlds, namely the experimental measurement and numerical simulation, to be merged into one integrated scheme. In this paper, the so-called patch transfer function (PTF) approach is adopted to solve coupled vibro-acoustic problems. In the PTF scheme, the interfaces between fluid and structure are discretised in terms of patches.

According to upcoming legislative regulations in certain countries, electric and hybrid-electric vehicles (EVs and HEVs) will have to be equipped with devices to compensate for the lack of engine noise needed to warn pedestrians against the vehicles. This leads to the question of appropriate sound design which has to meet specific psychoacoustic requirements. The present paper focuses on auditory features of warning sounds to enhance pedestrians' safety with a major focus on the detectability of the exterior noise of the vehicle in an ambient noise. For the evaluation of detectability, the psychoacoustic model developed by Kerber and Fastl will be introduced allowing for the prediction of masked thresholds of the approaching vehicle. The instrumental assessment yields estimates of the distance of an approaching vehicle at the point it becomes audible to the pedestrians.

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.

This paper presents a new approach to analyzing and developing low-drag cooling systems. A relation is derived which describes cooling drag by a number of contributions. Interference drag clearly can be identified as one of them. Cooling system parameters can be assigned to different terms of the relation, so that differences due to parameter variations of the individual drag contributions can be estimated. In order to predict the interference-drag dependency on the outlet location and the local outlet mass flow, an extensive study on a standard BMW sedan has been carried out, both experimentally and by CFD. The results show the importance of providing consistent outflow conditions which take into account the outlet location and flow direction, in order to minimize cooling drag.

In the environmentally conscious world we live in, auto manufacturers are under extreme pressure to reduce tailpipe emissions from cars and trucks. The manufacturers have responded by creating clean-burning engines and exhaust treatments that mainly produce CO2 and water vapor along with trace emissions of pollutants such as CO, THC, NOx, and CH4. The trace emissions are regulated by law, and testing must be performed to show that they are below a certain level for the vehicle to be classified as road legal. Modern engine and pollution control technology has moved so quickly toward zero pollutant emissions that the testing technology is no longer able to accurately measure the trace levels of pollutants. Negative emission values are often measured for some pollutants, as shown by results from eight laboratories independently testing the same SULEV automobile.

Today digital 3D human models are widely used to support the development of future products and in planning and designing production systems. However, these virtual models are generally not sufficiently intuitive and configuring accurate and real body postures is very time consuming. Furthermore, additionally using a human model to virtually examine manual assembly operations of a vehicle is currently synonymous with increased user inputs. In most cases, the user is required to have in-depth expertise in the deployed simulation system. In view of the problems described, in terms of human-computer interaction, it is essential to research and identify the requirements for simulation with digital human models. To this end, experienced staff members gathered the requirements which were then evaluated and weighted by the potential user community. Weaknesses of the simulation software will also be detected, permitting optimisation recommendations to be identified.

AM-SC1™ is a high temperature Mg alloy that was originally developed as a sand casting alloy for automotive powertrain applications. The alloy has been selected as the engine block material for both the AVL Genios LE and the USCAR lightweight magnesium engine projects. The present work assesses the potential of this alloy for permanent-mould die cast applications. Thermo-physical and mechanical properties of AM-SC1 were determined for material derived from a permanent-mould die casting process. The mechanical properties determined included: tensile, creep, bolt load retention/relaxation and both low and high cycle fatigue. To better assess the creep performance, a comparative analysis of the normalized creep properties was carried out using the Mukherjee-Dorn parameter, which confirmed the high viscoplastic performance of AM-SC1 compared with common creep resistant high pressure die cast (HPDC) Mg-alloys.

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.

Underbody aerodynamics has become increasingly important over the last three decades because of its vital contribution to improving a vehicle's overall performance. This was the motivation for the research conducted by BMW Aerodynamics, concerning the determination of the overall pressure distribution on the underbody of a series-production vehicle. Static pressure measurements have been taken under various test conditions. Real on-road tests were carried out as well as wind tunnel experiments under application of different road simulation techniques. The analyzed vehicle configurations include wheel rim-tire and body modifications. The results presented include surface pressure data, drag and lift coefficients, ride heights, pitch and roll angles. The acquired data is used to examine the underbody flow topology and determine how the diverse attempts to represent the real on-road conditions affect its pressure distribution.

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.

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.

Knowing the wheel forces on a vehicle under various circumstances and configurations is essential for its aerodynamic development. This becomes crucial when dealing with a racing car. This was the driving force for the initial research conducted in the BMW Aerodynamics Department [1] concerning the aerodynamic forces of an isolated 1:2 racing wheel. The latter were determined for various arrangements with the use of a system equipped with pressure transducers distributed on the wheel surface. While the pressure wheel is adequate for revealing flow structures surrounding it as well as highlighting its physics, it is nevertheless insufficient for the prediction of the wheel forces with high accuracy. As will be shown, this is mainly the consequence of the absent contribution of skin friction, the mathematical method engaged in post–processing and the restricted number of pressure transducers.