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Squeak and rattle (SAR) noise audible inside a passenger car causes the product quality perceived by the customer to deteriorate. The consequences are high warranty costs and a loss in brand reputation for the vehicle manufacturer in the long run. Therefore, SAR noise must be prevented. This research shows the application and experimental validation of a novel method to predict SAR noise on an actual vehicle interior component. The novel method is based on non-linear theories in the frequency domain. It uses the harmonic balance method in combination with the alternating frequency/time domain method to solve the governing dynamic equations. The simulation approach is part of a process for SAR noise prediction in vehicle interior development presented herein. In the first step, a state-of-the-art linear frequency-domain simulation estimates an empirical risk index for SAR noise emission. Critical spots prone to SAR noise generation are located and ranked.

Finite element simulation (FE) makes it possible to analyze the structural dynamic behavior of vehicle seat structures in early design phases to meet Noise-Vibration-Harshness (NVH) requirements. For this purpose, linear simulations are usually used, which neglect many nonlinear mechanical properties of the real structure. These models are trimmed to fit global vibration behavior based on the complex description of contact or jointed definitions. Targeted design is therefore only possible to a limited extent. The aim of this work is to characterize the entire seat structure and its sub-components in order to identify the main contributors using experimental and simulative data. The Lagrange Multiplier Frequency Based Substructuring (LM-FBS) method is used for this purpose. Therefore, the individual subsystems of seat frame, seat backrest and headrest are characterized under different conditions.

The thermal operational safety (TOS) of a vehicle ensures that no component exceeds its critical temperature during vehicle operation. To enhance the current TOS validation process, a data-driven approach is proposed to predict maximum component temperatures of a new vehicle project by leveraging the historical thermal wind tunnel data from previous vehicle projects. The approach intends to support engineers with temperature predictions in the early phase and reduce the number of wind tunnel tests in the late phase of the TOS validation process. In the early phase, all measurements of the new vehicle project are predicted. In the late phase, a percentage of measurements with the test vehicle used for the model training and the remaining tests are predicted with the trained ML model. In a first step, data from all wind tunnel tests is extracted into a joint dataset together with metadata about the vehicle and the executed load case.

The NVH-development cycle of vehicle components often requires a source characterization separated from the vehicle itself, which leads to the implementation of test bench setups. In the context of frequency based substructuring and transfer path analysis, a component can be characterized using Blocked Forces. The following paper provides a comparison of methods between an acceleration-based in-situ and a new hybrid in-situ Blocked Force determination, using measurements of an artificially excited electric power steering (EPS). Under real-life conditions on a test rig, the acceleration-based in-situ approach often shows limitations in the lower frequency range, due to relatively bad signal-to-noise ratio at the indicator sensors, while delivering accurate results in the higher spectrum. Due to considerable loads on components in operation, the stiffness of the test-rig cannot be decreased arbitrarily.

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.

The advancing electrification of the powertrain is giving rise to new challenges in the field of acoustics. Film capacitors used in power electronics are a potential source of high-frequency interfering noise since they are exposed to voltage harmonics. These voltage harmonics are caused by semiconductor switching operations that are necessary to convert the DC voltage of the battery into three-phase alternating current for an electrical machine. In order to predict the acoustic characteristics of the DC-link capacitor at an early stage of development, a multiphysical chain of effects has to be addressed to consider electrical and mechanical influences. In this paper, a new method to evaluate the excitation amplitude of film capacitor windings is presented. The corresponding amplitudes are calculated via an analytical strain based on electromechanical couplings of the dielectric within film capacitors.

Model Order Reduction (MOR) methods such as Component Mode Synthesis (CMS) have been used in order to simulate large linear dynamic systems for many years and have reached a considerable level of saturation. These reduction methods have many advantages such as minimizing computational costs but also have restrictions. One of their disadvantages is that material damping characteristics can only be defined in form of Rayleigh damping. Another disadvantage is that the reduced order model can only represent one state of the structure determined in the generation process of the reduced matrices. In this paper we present a way to consider material damping in reduced matrices that contain one or more materials having different damping characteristics without the disadvantages of using Rayleigh damping.

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.

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.

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.

The thermal prediction of a vehicle under-body environment is of high importance in the design, optimization and management of vehicle power systems. Within the pre-development phase of a vehicle's production process, it is important to understand and determine regions of high thermally induced stress within critical under-body components. Therefore allowing engineers to modify the design or alter component material characteristics before the manufacture of hardware. As the exhaust system is one of the primary heat sources in a vehicle's under-body environment, it is vital to predict the thermal fluctuation of surface temperatures along corresponding exhaust components in order to achieve the correct thermal representation of the overall under-body heat transfer. This paper explores a new method for achieving higher accuracy exhaust surface temperature predictions.

Despite increasingly stringent crash requirements, the body structures of future mainstream production cars need to get lighter. Carbon fiber reinforced polymer (CFRP) composites with a density 1/5th of steel and very high specific energy absorption represent a material technology where substantial mass can be saved when compared to traditional steel applications. BMW have addressed the demanding challenges of producing several hundred composite Body-in-White (BIW) assemblies a day and are committed to significant adoption of composites in future vehicle platforms, as demonstrated in the upcoming i3 and i8 models. A next step to further integrate composites into passenger cars is for primary structural members, which also perform critical roles in passive safety by absorbing large amounts of energy during a crash event.

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.

Plug-In Hybrid Electric Vehicles (PHEV) are becoming increasingly important as an intermediate step on the roadmap to Battery Electric Vehicles (BEV). Li-Ion is the most important battery technology for future hybrid and electrical vehicles. Cycle life of batteries for automotive applications is a major concern of design and development on vehicles with electrified powertrain. Cell manufacturers present various cell chemistries based on Li-Ion technology. For choosing cells with the best cycle life performance appropriate test methods and criteria must be obtained. Cells must be stressed with accelerated aging methods, which correlate with real life conditions. There is always a conflict between high accelerating factors for fast results on the one hand and best accordance with reality on the other hand. Investigations are done on three different Li-Ion cell types which are applicable in the use of PHEVs.

Unsteady aerodynamic flow phenomena are investigated in the wind tunnel by oscillating a realistic 50% scale model around its vertical axis. Thus the model is exposed to time-dependent flow conditions at realistic Reynolds and Strouhal numbers. Using this setup unsteady aerodynamic loads are observed to differ significantly from quasi-steady loads. In particular, the unsteady yaw moment exceeds the quasi-steady approximation by 80%. On the other hand, side force and roll moment are over predicted by quasi-steady approximation but exhibit a significant time delay. Using hotwire anemometry, a delayed reaction of the wake flow of Δt/T = 0.15 is observed, which is thought to be the principal cause for the differences between unsteady and quasi-steady aerodynamic loads. A schematic mechanism explaining these differences due to the delayed reaction of the wake flow is proposed.

Unsteady aerodynamic flow phenomena are investigated in a wind tunnel by oscillating a realistic 50% scale model around the vertical axis. Thus the model is exposed to time-dependent flow conditions at realistic Reynolds and Strouhal numbers. Using this setup unsteady aerodynamic loads are observed to differ significantly from quasi steady loads. In particular, the unsteady yaw moment exceeds the quasi steady approximation significantly. On the other hand, side force and roll moment are over predicted by quasi steady approximation but exhibit a significant time delay. Part 2 of this study proves that a delayed and enhanced response of the surface pressures at the rear side of the vehicle is responsible for the differences between unsteady and quasi steady loads. The pressure changes at the vehicle front, however, are shown to have similar amplitudes and almost no phase shift compared to quasi steady flow conditions.

A test center for aging analysis and characterization of Lithium-Ion batteries for automotive applications is optimized by means of a dedicated cell tester. The new power tester offers high current magnitude with fast rise time in order to generate arbitrary charge and discharge waveforms, which are identical to real power net signals in vehicles. Upcoming hybrid and electrical cars show fast current transients due to the implemented power electronics like inverter or DC/DC converter. The various test procedures consider single and coupled effects from current profile, state of charge and temperature. They are simultaneously applied on several cells in order to derive statistical significance. Comprehensive safely functions on both the hardware and the software level ensure proper operation of the complex system.

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.