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.

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.

The statistical energy analysis (SEA) is widely used to support the development of the sound package of cars. This paper will present the preparation of a model designed to investigate the sound package of the new Audi A3 and associated correlation against measurements. Special care was given during the creation of the model on the representation of the structure to enable the analysis of structure borne energy flow on top of the classical airborne analysis usually done with SEA. The sound package was also detailed in the model to allow further optimization and analysis of its performance. Two real life load cases will be presented to validate the model with measurements. First, the dominating powertrain and a second load case with dominating rolling noise. An analysis of the contribution of the different source components and a way to diagnose the weak paths of the vehicle will be presented. The focus of this investigation is the application of optimally adjusted treatment.

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.

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.

In recent years, we see more and more ECUs integrating a huge number of application software components. This process mostly results from the increasing amount of so called in-house software in various fields like electric-drive, chassis and driver assistance systems. The software development for these systems is partially moved from the supplier to the car manufacturers. Another important trend is the introduction of new network architectures intending to meet the growing communication requirements. For such ECUs the software integration scenarios become more complicated, as more quality of service requirements with regards to timing, safety and security need to be considered [2]. Multi-core microcontrollers offer even more potential variants for integration scenarios. Understanding the interaction between the different software components, not only from a functional, but also from a timing view, is a key success factor for modern electronic systems [6,7,8,9].

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.

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.

Nowadays there is an increasing need to streamline CAE processes. One such process consists of translating a Multibody Dynamics System (MBS) model into an equivalent Finite Element Analysis (FEA) model. Typically, users start with the creation of a MBS model which is set at a desired operating point by means of running simulations in the MBS domain (e.g. dynamics, statics.) The MBS model is then further translated into an equivalent FEA model which is used to perform simulations in the FEA domain (e.g. passive safety/crash, noise vibration harshness/NVH.) Currently, the translation of the MBS model into a FEA model is done either manually or by means of using a user-written script. This paper shows that a user-written script that translates a MBS model into a FEA model can not provide a high fidelity translation. In general, it is found that eigenvalues computed by the FEA code would not match eigenvalues computed by the MBS code.

A top-of-the-range car customer not only expects exceptional vehicle design and quality but also a driving experience, which is out of the ordinary. Very harmonious interaction between vehicle dynamics and the steering system is required to offer clients such a consistent driving experience through generations of vehicle models. In this paper the basic properties of a premium driving experience are explored. It is shown that outstanding handling limits are a prerequisite, although most customers never experience such driving situations. In fact, on-center behavior is most crucial in enabling clients to experience part of premium driving performance, and the steering system is the key factor in delivering appropriate feedback to the driver by means of steering torque. Development procedures are presented to achieve the goals described above.

In the production of brake disc pads, powder mixes containing, metal chips, filling agents, and abrasive materials, as well as phenolic resins are processed and molded to a back plate by way of pressure and temperature. These molded disc pads reach their final strength through additional thermal treatment such that the phenolic resins approach “full cure”. This production process leads to anisotropic, viscoelastic, and to a certain extent heterogeneous materials which are - like the brake system- increasingly subject to even greater demands. E.g. apart from tribological characteristics, more and more focus is placed on structure-mechanical properties to improve the braking comfort.

The Magnetic Forming Process is more than ever a very promising technology for light weight vehicle production. To support the development of further applications BMW Group has proven the ability of a standard FEM program to predict the process and the functional parameters of magnetically formed joints satisfactorily.