Search Results

Fully variable valve trains provide comprehensive means of adjustment in terms of variable valve timing and valve lift. The efficiency of the engine is improved in the operating range and in return, an increasing complexness of the mechanical design and control engineering must be handled. For optimization and design of these kinds of complex systems, detailed simulation models covering different physical domains, i.e. mechanics, hydraulics, electrodynamics and control are needed. Topic of this work is the variable valve train named Audi valvelift system (AVS) e.g. used in the Audi 2.8l V6 FSI engine. The idea of AVS is to use different cam lobes at different operating points. Each intake valve can be actuated by a large and a small cam. For full load, the two inlet valves are opened by the large cam profile - ideal for high charge volumes and flow speeds in the combustion chamber. Under partial load, the small cam profiles are used.

CFD has been widely used to predict the flow behavior inside 2-stroke engines over the past twenty years. Usually a mass flow profile or a simple 0D model is used for the inlet boundary condition, which replaces the complete intake geometry, such as reed valve, throttle, and air box geometries. For a CFD simulation which takes into account the exact reed valve geometry, a simulation of all above mentioned domains is required, as these domains are coupled together and thus interact. As the high speed of the engine affects the opening dynamic and closure of the reed valve, the transient data from the crank case volume and the section upstream the reed valve have an important influence on the reed petal dynamic and therewith on the sucked fresh air mass of the engine. This paper covers a methodology for the transient CFD simulation of the reed petals of a 2-stroke engine by using a 2D model.

Turbulence anisotropy has a great influence on mixture formation and flame propagation in internal combustion engines. However, the visualization of turbulence in simulations is not straightforward; traditional methods lack the ability to display the anisotropic properties in the engine geometry. Instead, they use invariant maps, and important information about the locality of the turbulence anisotropy is lost. This paper overcomes this shortcoming by visualizing the anisotropy directly in the physical domain. Componentality contours are applied to directly visualize the anisotropic properties of turbulence in the three-dimensional engine geometry. Using an RGB (red, green, blue) color map, the three limiting states of turbulence (one-component, axisymmetric two-component and isotropic turbulence) are displayed in the three-dimensional physical domain.

The absence of combustion engine noise pushes increasingly attention to the sound generation from other, even much weaker, sources in the acoustic design of electric vehicles. The present work focusses on the numerical computation of flow induced noise, typically emerging in components of flow guiding devices in electro-mobile applications. The method of Large-Eddy Simulation (LES) represents a powerful technique for capturing most part of the turbulent fluctuating motion, which qualifies this approach as a highly reliable candidate for providing a sufficiently accurate level of description of the flow induced generation of sound. Considering the generic test configuration of turbulent pipe flow, the present study investigates in particular the scope and the limits of incompressible Large-Eddy Simulation in predicting the evolution of turbulent sound sources to be supplied as source terms into the acoustic analogy of Lighthill.

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

Reynolds-averaged Navier-Stokes (RANS) computations of heat transfer involving wall bounded flows at elevated Prandtl numbers typically suffer from a lack of accuracy and/or increased mesh dependency. This can be often attributed to an improper near-wall turbulence modeling and the deficiency of the wall heat transfer models (based on the so called P-functions) that do not properly account for the variation of the turbulent Prandtl number in the wall proximity (y+< 5). As the conductive sub-layer gets significantly thinner than the viscous velocity sub-layer (for Pr >1), treatment of the thermal buffer layer gains importance as well. Various hybrid strategies utilize blending functions dependent on the molecular Prandtl number, which do not necessarily provide a smooth transition from the viscous/conductive sub-layer to the logarithmic region.

The open jet wind tunnel is a widespread test section configuration for developing full scale passenger cars in the automotive industry. However, using a realizable nozzle cross section for cost effective aerodynamic development is always connected to the presence of wind tunnel effects. Wind tunnel wall interferences which are not present under open road conditions, can affect the measurement of aerodynamic forces. Thus, wind tunnel corrections may be required. This work contains the results of a CFD (Computational Fluid Dynamics) approach using unsteady Delayed Detached Eddy Simulations (DDES) to evaluate wind tunnel interferences for open jet test sections. The Full Scale DrivAer reference geometry of the Technical University of Munich (TUM) using different rear end shapes has been selected for these investigations.

The presented paper focuses on the computation of heat transfer related to continuously variable transmissions (CVTs). High temperatures are critical for the highly loaded rubber belts and reduce their lifetime significantly. Hence, a sufficient cooling system is inevitable. A numerical tool which is capable of predicting surface heat transfer and maximum temperatures is of high importance for concept design studies. Computational Fluid Dynamics (CFD) is a suitable method to carry out this task. In this work, a time efficient and accurate simulation strategy is developed to model the complexity of a CVT. The validity of the technique used is underlined by field measurements. Tests have been carried out on a snowmobile CVT, where component temperatures, air temperatures in the CVT vicinity and engine data have been monitored. A corresponding CAD model has been created and the boundary conditions were set according to the testing conditions.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

The upstream flow conditions and the use of tractive power to accelerate a vehicle are both sources of energy loss. The vehicle speed and the upstream flow conditions result in the oncoming wind vector experienced by the moving vehicle. The aim of the present work is to show a new approach to consider the chaotic and random behavior of surrounding flow conditions and their influence on driving performance. The approach is shown for the example of motorbike racing conditions. Special interest was put on a description of the flow conditions with respect to well know turbulent flow field parameters like the turbulent length scale or the turbulence intensity. Depending on where the flow conditions are measured, stationary in the earth reference frame, or on a moving vehicle, it is quite difficult to get a robust description of the flow field parameters. These parameters are used together with the Reynolds number to predict the aerodynamic behavior by correlation functions or maps.

Aerodynamic CFD simulations in the automotive industry, which are based on the steady-state RANS (Reynolds-averaged Navier-Stokes) approach typically utilize approximate numerical methods to account for rotating wheels. In these methods, the computational mesh representing the rim geometry remains stationary, and the influence of the wheel rotation on the air flow is modelled. As the rims are considered only in one fixed rotational position (chosen arbitrarily in most cases), the effects of the rim orientation on the aerodynamic simulation results are disregarded and remain unquantified. This paper presents a numerical sensitivity study to examine the impact of the rim orientation position on the aerodynamic parameters of a detailed production vehicle. The simulations are based on the steady-state RANS approach.

Hydrogen nowadays is considered one promising energy carrier for future mobility scenarios. Its application as a fuel in ICEs greatly benefits from Direct Injection (DI) strategies, which help to reduce the disadvantages of PFI systems such as air displacement effects, knocking, backfiring and low power density. In SI-engines one appropriate way to increase efficiency is the reduction of wall heat losses by jet- and/or wall-guided mixture formation systems. In theory, Compression Ignition (CI) systems employing a diffusion type of combustion allow for a significant raise in compression ratio and, thus, are likely to excel the SI concept in terms of efficiency. The following paper deals with results obtained from investigations on H2 Compression-Ignition (H2-CI) combustion systems by employing both thermodynamic research engines and 3D CFD simulation.

This study deals with the experimental investigation of the mechanical properties of a lithium-ion pouch cell and its modelling in an explicit finite element simulation code. One can distinguish between ‘macroscopic’ and ‘microscopic’ modelling approaches. In the ‘macroscopic’ approach, one material model approximates the behaviour of multiple inner cell layers. In the ‘microscopic’ approach, which is used in the present study, all layers and their interactions are modelled separately. The cell under study is a pouch-type lithium-ion cell with a liquid electrolyte. With its cell chemistry, design, size and capacity it is usable for automotive applications and can be assembled into traction batteries. One cell sample was fully discharged and disassembled, and its components (anode, cathode, separator and pouch) were examined and measured by electron microscopy. Components were also tensile tested.

The continuously decreasing emission limits lead to a growing importance of exhaust aftertreatment in Diesel engines. Hence, methods for achieving a rapid catalyst light-off after engine cold start and for maintaining the catalyst temperature during low load operation will become more and more necessary. The present work evaluates several valve timing strategies concerning their ability for doing so. For this purpose, simulations as well as experimental investigations were conducted. A special focus of simulation was on pointing out the relevance of exhaust temperature, mass flow and enthalpy for these thermomanagement tasks. An increase of exhaust temperature is beneficial for both catalyst heat-up and maintaining catalyst temperature. In case of the exhaust mass flow, high values are advantageous only in case of a catalyst heat-up process, while maintaining catalyst temperature is supported by a low mass flow.

The mathematical thermal design of the vehicle brakes will lead to success if all influence parameters such as friction (fading effect), car geometry and inertia, brake amplifier, tire, convective heat flow, heat conductance and heat radiation are taken into consideration. In addition to a lot of design criteria, the thermal stability of the vehicle brake is becoming more and more important because of permanently increasing engine powers and weight of the vehicles. This requires both stable friction behavior in the contact zone between brake lining and brake disk and a sufficient transfer of the friction energy by means of convective heat flow. In order to accomplish these two tasks, considerable expense on a brake test bed and innumerable brake trials are necessary. It must be guarantied at the end of the brake design process that the vehicle reaches the required braking distance and the thermal stability of the brake, e.g. after several freeway braking sequences.

When vehicle to vehicle collisions are analyzed using a discrete kinetic time forward simulation, several simulation runs have to be performed, to find a solution, where post impact trajectories and rest positions correspond with the real accident. This paper describes in detail a method to vary the pre-impact parameters automatically and to evaluate the simulation results. In a first step the different pre-impact parameters are discussed. Their influence on the impact and the post impact movement is shown. Furthermore the necessary specifications to define the post crash movement are presented. The necessity to define tire marks and rest positions of the vehicles involved is outlined. An effective evaluation criteria is derived, which is used to calculate a simulation error. This error is then used as a target function to control the optimization process. Two different optimization strategies are presented.

In the present work we investigated experimentally and computationally the unsteady flow around a BMW car model including wheels*. This simulation yields mean flow and turbulence fields, enabling the study aerodynamic coefficients (drag and lift coefficients, three-dimensional/spatial wall-pressure distribution) as well as some unsteady flow phenomena in the car wake (analysis of the vortex shedding frequency). Comparisons with experimental findings are presented. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (TRANS) equations. Special attention is devoted to turbulence modelling and the near-wall treatment of turbulence. The flow calculations were performed using a robust, eddy-viscosity-based ζ - ƒ turbulence model in the framework of the elliptic relaxation concept and in conjunction with the universal wall treatment, combining integration up to the wall and wall functions.

More and more high-level algorithms are emerging to improve the existing systems in a car. Often these algorithms only need a platform with a bus connection and some resources such as CPU time and memory space. These functions can easily be integrated into existing systems that have free resources. This paper describes some encapsulation techniques and mechanisms that can be used in the automotive domain. The discussion also takes into account the additional resources consumed on the microcontroller to meet these requirements and by the software to implement the encapsulation mechanisms. Overviews of some general concepts of software-architectures that provide encapsulation are also shown.