Search Results

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.

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.

Transfer path analyses of vehicle bodies are widely considered as an important tool in the noise, vibration and harshness design process, as they enable the identification of the dominating transfer paths in vibration problems. It is highly beneficial to model uncertain parameters in early development stages in order to account for possible variations on the final component design. Therefore, parameter studies are conducted in order to account for the sensitivities of the transfer paths with respect to the varying input parameters of the chassis components. To date, these studies are mainly conducted by performing sampling-based finite element simulations. In the scope of a sensitivity analysis or parameter studies, however, a large amount of large-scale finite element simulations is required, which leads to extremely high computational costs and time expenses. This contribution presents a method to drastically reduce the computational burden of typical sampling-based simulations.

Uncertainties play a major role in vibroacoustics - especially in car body design in the preliminary development because of the overall spread in the production that should be covered with one simulation model. Therefore, we use uncertain input parameters to determine the stochastically distributed admittance of the car body before each part of the car is fully designed. To gain a stochastic result - the stochastically distributed admittance curve - we calculate a deterministic finite element simulation several times with sets of stochastically distributed input parameter values. To reduce simulation time and cost of the car model with many million degrees of freedom we focus on the uncertain parameters that show a significant influence on the admittance curve. It is therefore necessary to be able to accurately estimate for each parameter if its influence on the admittance of the car body plays a major role for the noise vibration harshness simulation.

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.

Substructuring approaches are helpful methods to solve and understand vibro-acoustic problems involving systems as complex as a vehicle. In that case, the whole system is split into smaller, simpler to solve, subsystems. Substructuring approaches allow mixing different modeling “solvers” (closed form solutions, numerical simulations or experiments). This permits to reach higher frequencies or to solve bigger systems. Finally, one of the most interesting features of substructuring approaches is the possibility to combine numerical and experimental descriptions of subsystems. The latter point is particularly interesting when dealing with subdomains that remain difficult to model with numerical tools (assembly, trim, sandwich panels, porous materials, etc.). The Patch Transfer Functions (PTF) method is one of these substructuring approaches. It condenses information (impedance matrix) of subsystems on their coupling surfaces.

The Noise Vibration and Harshness (NVH) characteristics and requirements of vehicles are changing as the automotive manufacturers turn their focus from developing and producing cars propelled by internal combustion engines (ICE) to electrified vehicles. This new strategic orientation enables them to offer products that are more efficient and environmentally friendly. Although electric powertrains have many advantages compared to their established predecessors they also bring new challenges that increase the difficulty of matching the high quality requirements of premium car producers especially regarding NVH. Electric motors are one of the most important sources of vibrations in electric vehicles.

Classical decentralized architectures based on large networks of microprocessor-based Electronic Control Units (ECU), namely those used in self-driving cars and other highly-automated applications used in the automotive industry, are becoming more and more complex. These new, high computational power demand applications are constrained by limits on energy consumption, weight, and size of the embedded components. The adoption of new embedded centralized electrical/electronic (E/E) architectures based on dynamically reconfigurable hardware represents a new possibility to tackle these challenges. However, they also raise concerns and questions about their safety. Hence, an appropriate evaluation must be performed to guarantee that safety requirements resulting from an Automotive Safety Integrity Level (ASIL) according to the standard ISO 26262 are met. In this paper, a methodology for the evaluation of dynamically reconfigurable systems based on centralized architectures is presented.

Windscreen wipers are an integral component of the windscreen cleaning systems of most vehicles, trains, cars, trucks, boats and some planes. Wipers are used to clear rain, snow, and dirt from the windscreen pushing the water from the wiped surface. Under certain conditions however, water which has been driven to the edge of the windscreen by the wiper can be drawn back into the driver’s field of view by aerodynamic forces introduced by the wiper motion. This is wiper drawback, an undesirable phenomenon as the water which is drawn back on to the windscreen can reduce driver’s vision and makes the wiper less effective. The phenomena of wiper drawback can be tested for in climatic tunnels using sprayer systems to wet the windscreen. However, these tests require a bespoke test property or prototype vehicle, which means that the tests are done fairly late in the development of the vehicle.

As a key part of numerical analysis, the modeling process has a tremendous influence on the quality of the results. While there is general awareness concerning uncertainties that arise during modeling, their quantity and sensitivity rarely are known. Hence, modeling quickly can become inaccurate and inefficient. The scope of the present paper is to innovate predictive modeling processes concerning the dynamics of real complex structures by means of linear modal analysis with the finite element method (FEM). The aim is to offer a transparent design catalog relating specific uncertainties to each model component in order to achieve error prevention for engineers dealing with comparable systems. A complex system is simplified and investigated for different levels of detail. Only after the model uncertainties for one level of detail are obtained, the next level of complexity is approached.

The management of surface water flows driven from the wind screen by the action of wipers and aerodynamic shear is a growing challenge for automotive manufacturers. Pressure to remove traditional vehicle features, such as A-Pillar steps for aesthetic, aeroacoustic and aerodynamic reasons increases the likelihood that surface water may be convected over the A-Pillar and onto the front side glass where it can compromise drivers’ vision. The ability to predict where and under which conditions the A-Pillar will be breached is important for making correct design decisions. The use of numerical simulation in this context is desirable, as experimental testing relies on the use of aerodynamics test properties which will not be fully representative, or late-stage prototypes, making it difficult and costly to correct issues. This paper provides an update on the ability of simulation to predict A-Pillar overflow, comparing physical and numerical results for a test vehicle.

Side window clarity and its effect on side mirror visibility plays a major role in driver comfort. Driving in inclement weather conditions such as rain can be stressful, and having optimal visibility under these conditions is ideal. However, extreme conditions can overwhelm exterior water management devices, resulting in rivulets of water flowing over the a-pillar and onto the vehicle’s side glass. Once on the side glass, these rivulets and the pooling of water they feed, can significantly impair the driver’s ability to see the side mirror and to see outwardly when in situations such as changing lanes. Designing exterior water management features of a vehicle is a challenging exercise, as traditionally, physical testing methods first require a full-scale vehicle for evaluations to be possible. Additionally, common water management devices such as grooves and channels often have undesirable aesthetic, drag, and wind noise implications.

The development of a new Dongfeng Heavy truck had very strict targets for fuel consumption. As the aerodynamic drag plays a crucial role for the fuel consumption, a low drag value had to be achieved. It was therefore essential to include evaluation and optimization of the aerodynamics in the development process. Because wind tunnel facilities were not available, the complete aerodynamics development was based on digital simulation. The major portion of the aerodynamic optimization was carried out during the styling phase where mirrors, sun visor, front bumper and aero devices were optimized for drag reduction. For optimizing corner vanes and mud guards, self-soiling from the wheel spray was included in the analysis. The aero results did also show that cooling air flow rates are sufficiently high to ensure proper cooling. During the detailed engineering phase an increase of the drag above the target required further optimization work to finally reach the target.

For the automotive industry, the quality and level of the wind noise contribution has a growing importance and therefore should be addressed as early as possible in the development process. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof broadband noise is generated by the turbulent flow developed over the roof opening. A strong shear layer and vortices impacting on the trailing edge of the sunroof are typical mechanisms related to the noise production. Sunroof designs are tested to meet broadband noise targets. Experimentally testing designs and making changes to meet these design targets typically involves high cost prototypes, expensive wind tunnel sessions and potentially late design changes.

Car manufacturers put large efforts into reducing wind noise to improve the comfort level of their cars. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof designs are tested to meet low-frequency buffeting (also known as boom) targets and broadband noise targets for the fully open sunroof with deflector and for the sunroof in vent position. Experimentally testing designs and making changes to meet these design targets typically involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process.

This paper presents an approach to numerically simulate greenhouse windnoise. The term “greenhouse windnoise” here describes the sound transferred to the interior through the glass panels of a series vehicle. Different panels, e.g. the windshield or sideglass, are contributing to the overall noise level. Attached parts as mirrors or wipers are affecting the flow around the vehicle and thus the pressure fluctuations which are acting as loads onto the panels. Especially the wiper influence and the effect of different wiper positions onto the windshield contribution is examined and set in context with the overall noise levels and other contributors. In addition, the effect of different flow yaw angles on the windnoise level in general and the wiper contributions in particular are demonstrated. As computational aeroacoustics requires accurate, highly resolved simulation of transient and compressible flow, a Lattice-Boltzmann approach is used.

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.

For most car manufacturers, wind noise from the greenhouse region has become the dominant high frequency noise contributor at highway speeds. Addressing this wind noise issue using experimental procedures involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process. Previously, a computational approach that couples an unsteady computational fluid dynamics solver (based on a Lattice Boltzmann method) to a Statistical Energy Analysis (SEA) solver had been validated for predicting the noise contribution from the side mirrors. This paper presents the use of this computational approach to predict the vehicle interior noise from the windshield wipers, so that different wiper placement options can be evaluated early in the design process before the surface is frozen.

A computational process for early stage vehicle shape assessment for automotive front window buffeting and greenhouse wind noise is presented. It is a challenging problem in an experimental process as the vehicle geometry is not always finalized. For example, the buffeting behavior typically worsens during the vehicle development process as the vehicle gets tighter, leading to expensive late counter measures. We present a solution using previously validated CFD/CAA software based on the Lattice Boltzmann Method (LBM). A CAD model with realistic automotive geometry was chosen to simultaneously study the potential of different side mirror geometries to influence the front window buffeting and greenhouse wind noise phenomena. A glass mounted mirror and a door mounted mirror were used for this comparative study. Interior noise is investigated for the two phenomena studied. The unsteady flow is visualized and changes in the buffeting and wind noise behavior are explored.

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.