Search Results

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.

Raising demands towards lightweight design paired with a loss of originally predominant engine noise pose significant challenges for NVH engineers in the automotive industry. From an aeroacoustic point of view, low frequency buffeting ranks among the most frequently encountered issues. The phenomenon typically arises due to structural transmission of aerodynamic wall pressure fluctuations and/or, as indicated in this work, through rear vent excitation. A possible workflow to simulate structure-excited buffeting contains a strongly coupled vibro-acoustic model for structure and interior cavity excited by a spatial pressure distribution obtained from a CFD simulation. In the case of rear vent buffeting no validated workflow has been published yet. While approaches have been made to simulate the problem for a real-car geometry such attempts suffer from tremendous computation costs, meshing effort and lack of flexibility.

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.

A shortcoming of widely-used integral methods for prediction of flow-induced sound emission of rotating systems is that the rotation of the impeller can be included in the calculation, but not reflections of sound from the housing, rotor blades and attached ducts. This paper introduces a finite element method that correctly maps both the sound sources rotating with the impeller and the reflections of the sound from the rigid surfaces of the components of the blower. For the prediction of flow-induced sound a hybrid approach is employed using separate CFD and acoustic simulations. It is based on a decomposition of flow (incompressible part) and acoustic (compressible part) quantities and is applicable to high-Reynolds-number and low-Mach-number flows. It features only a scalar unknown (i.e. the acoustic velocity potential), thus reducing the computational effort significantly.

To reduce noise in a HVAC system for railway application the usage of micro-perforated panels (MPP) is proposed. MPPs offer some favorable characteristics, like robustness and durability in harsh environments and the possibility to optimize absorption in desired frequency bands. The underlying acoustic mechanism can be modelled via an equivalent fluid in accordance with the Johnson-Champoux-Allard (JCA) approach, treating the MPPs as a porous material with rigid frame. This allows to conduct the necessary acoustic pre-evaluation in complex HVAC application scenarios in order for the MPPs to substitute the commonly used foam and fibrous absorber materials.

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.

Experimental studies have shown that knitted wiremesh mixers reduce the formation of solid deposits and improve ammonia homogenization in automotive SCR systems. However, their implementation in CFD models remains a major challenge due to the complex WM geometry. It was the aim of the current study to investigate droplet WM interaction. Essential processes, such as secondary droplet generation, wall film formation, and heat exchange, were analyzed in detail and a numerical model was set up. A box with heat resisting glass was used to study urea-water solution spray impingement on a WM under a wide range of operating conditions. High speed videography was used to identify the impingement regimes. Infrared thermography was applied to investigate WM cooling. In order to determine the impact of the WM on the spray characteristics, the droplet spectrum was measured both upstream and downstream of the WM using the laser diffraction method.

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.

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.

In this work we extended the findings from a previous study by the authors on the mechanisms and influence factors of deposit formation in urea-based selective catalytic reduction systems (SCR) [1]. A broader range of operating conditions was investigated in detail. In order to quantify the boundary conditions of deposition, a representative set of deposits was studied during formation and decomposition. A box of heat resisting glass was equipped with a surrogate mixing element to monitor solidification timescales, temperatures and deposit growth. A chemical analysis of the deposits was performed using thermogravimetry. The depletion timescales of individual deposit components were systematically investigated. A moderate temperature increase to 350 °C was deemed sufficient to trigger fast decomposition of deposits formed below 250 °C.

In some today's and future electronic and optoelectronic packaging systems (assemblies), including those intended for aerospace applications, the package (system's component containing active and passive devices and interconnects) is placed (sandwiched) between two substrates. In an approximate stress analysis these substrates could be considered, from the mechanical (physical) standpoint, identical. Such assemblies are certainly bow-free, provided that all the stresses are within the elastic range and remain elastic during testing and operation. Ability to remain bow-free is an important merit for many applications. This is particularly true in optical engineering, where there is always a need to maintain high coupling efficiency. The level of thermal stresses in bow-free assemblies of the type in question could be, however, rather high.

There is a concern that the continuing trend on miniaturization (Moore's law) in IC design and fabrication might have a negative impact on the device reliability. To understand and to possibly quantify the physics underlying this concern and phenomenon, it is natural to proceed from the experimental bathtub curve (BTC) - reliability “passport” of the device. This curve reflects the combined effect of two major irreversible governing processes: statistics-related mass-production process that results in a decreasing failure rate with time, and reliability-physics-related degradation (aging) process that leads to an increasing failure rate. It is the latter process that is of major concern of a device designer and manufacturer. The statistical process can be evaluated theoretically, using a rather simple predictive model.

A fast preparation of the liquid urea water solution (UWS) is necessary to ensure high conversion rates in exhaust aftertreatment systems based on Selective Catalytic Reduction (SCR). Droplet wall interaction is of major importance during this process, in particular droplet breakup and the Leidenfrost effect. A deeper understanding of the underlying mechanisms is a basic requirement to calibrate CFD models in order to improve their prediction accuracy. This paper presents a detailed literature study and discussion about the major impact factors on droplet wall interaction. Measurements of the Leidenfrost temperature were conducted and the corresponding regimes classified based on optical observations. The pre- and post-impingement spray was analysed using the laser diffraction method. Further, the validity of spray initialisation based on measurements at room temperature was verified.

One promising application in the emission control is the Selective Catalytic Reduction (SCR) system for the reduction of nitric oxides from exhaust emissions. Previous works at the institute have highlighted the importance of accurate CFD turbulence modeling with respect to the turbulent mixing of ammonia vapor [1]. With the help of Laser Doppler Anemometry (LDA) measurements it was confirmed that RANS approaches are capable of predicting the velocity field adequately. In contrast, the turbulence level was underestimated for all RANS approaches [2]. Based on this work the paper at hand presents CFD results using Large Eddy Simulation (LES). The sensitivity of the solution with respect to spatial and temporal resolution as well as the boundary conditions is demonstrated. In accordance with the Kolmogorov theory grid sizes ranging from 3.2 to 20 million cells were investigated using LES methodology.

Modern exhaust systems contain not only a piping network to transport hot gas from the engine to the atmosphere, but also functional components such as the catalytic converter and turbocharger. The turbocharger is common place in the automotive industry due to their capability to increase the specific power output of reciprocating engines. As the exhaust system is a main heat source for the under body of the vehicle and the turbocharger is located within the engine bay, it is imperative that accurate surface temperatures are achieved. A study by K. Haehndel [1] implemented a 1D fluid stream as a replacement to solving 3D fluid dynamics of the internal exhaust flow. To incorporate the 3D effects of internal fluid flow, augmented Nusselt correlations were used to produce heat transfer coefficients. It was found that the developed correlations for the exhaust system did not adequately represent the heat transfer of the turbocharger.

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 combustion of highly boosted gasoline engines is limited by knocking combustion and pre-ignition. Therefore, a comprehensive modelling approach consisting of cycle-to-cycle simulation, reactor modelling with detailed chemistry and CFD-simulation was used to predict the knock initiation and to identify the source of pre-ignition. A 4-cylinder DISI test engine was set up and operated at low engine speeds and high boost pressures in order to verify the accuracy of the numerical approach. The investigations showed that there is a correlation between the knocking combustion and the very first combustion phase. The onset of knock was simulated with a stochastic reactor model and detailed chemistry. In parallel, measurements with an optical spark plug were carried out in order to identify the location of knock onset. The simulation results were in good agreement with the measurements. Deposits and oil/fuel-droplets are possible triggers of pre-ignition.

At the rear of the vehicle an end acoustic silencer is attached to the exhaust system. This is primarily to reduce noise emissions for the benefit of passengers and bystanders. Due to the location of the end acoustic silencer conventional thermal protection methods (heat shields) through experimental means can not only be difficult to incorporate but also can be an inefficient and costly experience. Hence simulation methods may improve the development process by introducing methods of optimization in early phase vehicle design. A previous publication (Part 1) described a methodology of improving the surface temperatures prediction of general exhaust configurations. It was found in this initial study that simulation results for silencer configurations exhibited significant discrepancies in comparison to experimental data.