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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.

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.

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.

Laser induced fluorescence (LIF) is used to investigate oil transport mechanisms under real engine conditions. The engine oil is mixed with a dye that can be induced by a laser. The emitted light intensity from the dye correlates with the residual oil at the sensor position and the resulting oil film thicknesses can be precisely determined for each crank angle. However, the general expectation is not always achieved, e.g. an exact representation of piston ring barrel shapes. In order to investigate the responsible lubrication effects of this behavior, a new cavitation algorithm for the Reynolds equation has been developed. The solution retains the mass conservation and does not use any switch function in its mathematical approach. In contrast to common approaches, no vapor-liquid ratio is used, but one or several bigger bubbles are approximated, as have been observed in other experiments already.

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.

The study of oil emission is of essential interest for the engine development of modern cars, as well as for the understanding of hydrocarbon emissions especially during cold start conditions. A laser mass spectrometer has been used to measure single aromatic hydrocarbons in unconditioned exhaust gas of a H2-fueled engine at stationary and transient motor operation. These compounds represent unburned oil constituents. The measurements were accompanied by FID and GC-FID measurements of hydrocarbons which represent the burned oil constituents. The total oil consumption has been determined by measuring the oil sampled by freezing and weighing. It has been concluded that only 10 % of the oil consumption via exhaust gas has burned in the cylinders. A correlation of the emission of single oil-based components at ppb level detected with the laser mass spectrometer to the total motor oil emission has been found.

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.

The performance of environment perceiving sensors such as e.g. lidar, radar, camera and ultrasonic sensors is safety critical for automated driving vehicles. Therefore, one has to assess the sensors’ performance to assure the automated driving system’s safety. The performance of these sensors is however to some degree sensitive towards adverse weather conditions. A challenge is to quantify the effect of adverse weather conditions on the sensor’s performance early in the development of an automated driving system. This challenge is addressed in this work for lidar sensors. The lidar equation was previously employed in this context to derive estimates of a lidar’s maximum range in different weather conditions. In this work, we present a stochastic simulation framework based on a probabilistic extension of the lidar equation, to quantify the effect of adverse rainfall conditions on a lidar’s raw detection performance.

Virtual testing has grown to be an efficient tool in vehicle passive safety design. Most simulations currently are deterministic. Since the responses observed in real-life and standardized tests are greatly affected by scatter, a stochastic approach should be adopted in order to improve the predictability of the numerical responses with respect to the experimental data. In addition, an objective judgement of the performance of numerical models with respect to experimental data is necessary in order to improve the reliability of virtual testing. In the European VITES & ADVANCE project the software tool Adviser was developed in order to fulfil these two requirements. With Adviser, stochastic simulations can be performed and the quality of the numerical responses with respect to the experimental can be objectively rated using pre-defined and user-defined objective correlation criteria. The software Adviser was used to develop a stochastic HybridIII 50th% Madymo numerical model.

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.

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.

Advanced material technologies play a key role in automotive engineering. The main objective of the development of advanced material technologies for automotive applications is to promote the desired properties of a vehicle. It is characteristic of most materials in modern cars that they have been developed especially for automotive requirements. Requirements are not only set by the customer who expects the maximum in performance, comfort, reliability, and safety from a modern car. Existing legal regulations also have to be met, e.g., in the areas of environmental compatibility, resource preservation, and minimization of emissions. To achieve goals like weight reduction or increased engine performance permanent material developments are essential. In this paper, numerous examples chosen from body, suspension, and powertrain components show clearly how low weight technologies, better comfort, and high level of recyclability can be achieved by advanced material solutions.

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.

The importance of the automotive interior as a characteristic feature in the competition for the goodwill of the customer has increased significantly in recent years. Whilst there are established, more or less efficient CAE processes for the solution of problems in the areas of occupant safety and service strength, until now the implementation of CAE in themes such as dimensional stability, warpage and corrugation1 of plastic parts has been little investigated. The developmental support in this field is predominantly carried out by means of hardware tests. Real plastic components alter their form as a result of internal forces often during the first weeks following production. The process, known as “creep”, can continue over an extended period of time and is exacerbated by high ambient temperatures and additional external loads stemming from installation and post assembly position.

Improving fuel efficiency while meeting relevant emission limits set by emissions legislation is among the main objectives of engine development. Simultaneously the development costs and development time have to be steadily reduced. For these reasons, the high demands in terms of quality and validity of measurements at the engine test bench are continuously rising. This paper will present a new methodology for efficient testing of an industrial combustion engine in order to improve the process of decision making for combustion-relevant component setups. The methodology includes various modules for increasing measurement quality and validity. Modules like stationary point detection to determine steady state engine behavior, signal quality checks to monitor the signal quality of chosen measurement signals and plausibility checks to evaluate physical relations between several measurement signals ensure a high measurement quality over all measurements.

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.

The recent growth of available computational resources has enabled the automotive industry to utilize unsteady Computational Fluid Dynamics (CFD) for their product development on a regular basis. Over the past years, it has been confirmed that unsteady CFD can accurately simulate the transient flow field around complex geometries. Concerning the aerodynamic properties of road vehicles, the detailed analysis of the transient flow field can help to improve the driving stability. Until now, however, there haven’t been many investigations that successfully identified a specific transient phenomenon from a simulated flow field corresponding to driving stability. This is because the unsteady flow field around a vehicle consists of various time and length scales and is therefore too complex to be analyzed with the same strategies as for steady state results.

Fast and exact measurement of engine oil consumption is a very difficult task. Our aim is to achieve this measurement at a common test bed without engine modifications. We resolved this problem with a new technique using Laser Mass Spectrometry to detect appropriate tracers in the raw engine exhaust. The tracers are added to the engine oil. to the engine oil. For detection of these tracers we use a Laser Mass Spectrometer (LAMS). This is a combination of resonant laser ionization (with an all-solid-state laser) and Time-of-Flight Mass Spectrometry. Currently this is the only way to detect oil originated molecules (like our tracers) in the raw exhaust very fast (50 Hz) and sensitive (ppb-region). Thus, engine mapping of oil consumption over load and speed can be performed in 1-2 days with about 90 measurements. Even measurement during dynamic engine operation is possible, but not quantitative (due to the lack of information about dynamic exhaust gas mass flow).

Among the issues affecting the design process of a vehicle, there is the lack of multidisciplinary knowledge among the different teams involved. This often leads to the risk of loosing important key points from the initial concept idea of designers to the final vehicle package definition made by engineers. Therefore, this study builds up a method based on parameters defining exterior aesthetic priorities according to car segment to support engineers involved in the automotive design process. In particular, during the early design-engineering phase, this method should help them to understand better vehicle proportions defined by designers. This work is currently used in the course of design and simulation of road vehicles (Chair of Automotive Technology, TUM) to explain fundamentals of automotive design.

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.