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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.

In large-scale industrial simulations the numerical prediction of fracture in sheet metal forming operations as well as in crash events is still a challenging task of high social and economic relevance. Among several approaches presented in literature, the authors and their colleagues developed a model which accounts each for three different mechanisms leading finally to fracture in thin sheet metals: the local instability (necking), ductile normal fracture and ductile shear fracture. The focus of this paper is to develop and validate a new approach to improve the predictive capabilities for fracture triggered by localized necking for a wide variety of steel grades. It is well known that after the onset of a local instability additional strain is still necessary to induce fracture. In a numerical simulation using shell elements this post instability strain becomes of increasing importance when the ratio of the characteristic shell element edge length to its thickness decreases.

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.

The validity of numerical simulations is still limited by the unknown failure of materials when nonlinear load paths in successive stamping and crash processes occur. Localized necking is the main mechanism for fractures in ductile sheet metal. The classical forming limit curve (FLC) is limited to linear strain paths. To include the effects of nonlinear strain paths a theoretical model for instability (algorithm CRACH) has been used. The algorithm has been developed on the basis of the Marciniak model [8]. The calibration and validation of this approach is done by a set of multistage experiments under static and dynamic strain rates for a mild steel.

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.

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.

During early phases of interior car layout a lot of different aspects have to be considered like crashworthiness, regulations, philosophy of the company etc.. Ergonomic aspects do not always play the most important role in these cases. Since aspects of comfort in cars are getting more and more important in nowadays these aspects should be taken into account very early in the interior car layout process. This paper shows a way to design the interior layout of a car from scratch for a good postural comfort for all anthropometries with the aid of a digital human model (RAMSIS). The novelty of this approach is to use the digital human model to design the interior and not to verify or correct an existing one.

The application of crash durable structural adhesives in modern cars design, to improve the driving durability, the overall vehicle stiffness, the crash resistance and to make real light weight constructions feasible is significantly gaining in importance. 1-component systems are already introduced in the market and used in automotive industries. Usually the use of these bonds in automotive industries is limited by a relatively low wash off resistance in the pre-treatment tanks of the paint shop. If no additional actions are taken, there is a severe risk of wash off of the adhesives up to the partial loss in functionality. Respectively contamination of the pre-treatment tanks and aftereffects damage the surface of the coated cars. To avoid wash off a thermal process (oven) to pre-gel the adhesive in the flanges of the Body-In-White (BIW)- bodies before entering the pre-treatment utility is necessary. This is a save but cost intensive solution.

Software-intensive systems and functions drive innovations in cars today. OEMs and suppliers face multiple challenges to take advantage of possibilities in this area. The rapidly developing field of software-intensive systems and software-based features in the automotive domain asks for dedicated engineering approaches, models, and processes. This paper defines the characteristics of software engineering for automotive systems and discusses methodological, technological, and organizational implications. These are used to pinpoint promising research areas as well as educational ramifications.

Optimizing protection for side impact in vehicle design requires valid information about occupant behavior under lateral loading. For this reason a comparison of numerical models of dummies and human body in side impact scenarios is shown to estimate the benefits of using numerical human models in future safety design. First a well-known sled test set up was simulated to compare the two devices in a defined surrounding. After looking at the kinematics, the loads, accelerations and injury values of the occupants were derived and compared to each other. Second the occupant models were positioned in a vehicle model to compare their behavior in a more complex loading case, such as an EuroNCAP Barrier Test. Focus of this investigation was the injury mechanism occurring in the human model. The Behavior of the Dummy and H-Model is comparable and shows similar responses in a global view.

In order to protect occupants from the risk of serious injury in event of side impact, passenger vehicles are designed to fulfil specific legislative and consumer impact test requirements. These are generally different for each of the major markets of the world. The tests use different configurations and percentile dummies (anthropomorphic test devices). Aside from the problem of finding an optimal design, the reliable evaluation of the robustness, i.e. the sensitivity of unavoidable scatter of design variables due to the structural response, is becoming increasingly important. For this purpose simulation is a well established tool in the development process in the automotive industry. The integration of FE-dummies and restraint systems in side impact simulations enables the study of the effect of dummy loading. ABAQUS/Explicit is a promising new software package for gaining more accuracy in crashworthiness and occupant protection simulations.

BMW can look back on 20 years of research activities on hydrogen propulsion systems. Hydrogen fuel is the only means of offering pure driving pleasure on the basis of a sustainable energy loop. As the hydrogen era is still quite a while away the BMW Energy Strategy „Via Natural Gas to Hydrogen” has been developed. The first step was to build series-production compressed natural gas (CNG) cars back in 1995. By switching to liquefied natural gas (LNG) not only is the cruising range tripled but technologically the final stepping-stone is reached in preparing the way for liquefied hydrogen. BMW's automotive and drive technology for hydrogen is now available and ready to move out of the laboratory on to the road. At Munich Airport a BMW „Clean Energy” car is already providing shuttle services. Its fuel is supplied by the world's first public filling station for liquefied hydrogen.

Sport Activity Vehicle (SAV) share a growing market of an entirely new class of vehicles. Outstanding comfort in traditional on-road and also off-road terrain combined with leading edge technology are basic features of this concept. But in addition to that, the SAV has to offer the same overall safety features, expected by e.g. a luxury-segment sedan. A way to ensure the BMW X5 becoming one of the safest cars was the consequent use of simulation techniques in passive safety development. This paper deals with introduction of a CAE driven development process for passive safety in the BMW X5 project, focusing on examples in front and side impact.

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.

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.

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.

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.

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.