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Under city driving conditions, the powertrain represents one of the major vehicle exterior noise sources. Especially at idle and during full load acceleration, the oil pan contributes significantly to the overall powertrain sound emission. The engine oilpan can be a significant contributor to the powertrain radiated sound levels. Passive optimization measures, such as structural optimization and acoustic shielding, can be limited by e.g. light-weight design, package and thermal constraints. Therefore, the potential of the Active Structure Acoustic Control (ASAC) method for noise reduction was investigated within the EU-sponsored project InMAR. The method has proven to have significant noise reduction potential with respect to oil pan vibration induced noise. The paper reports on activities within the InMAR project with regard to a passenger car oil pan application of an ASAC system based on piezo-ceramic foil technology.

This paper describes the development and achievement of a target engine sound for a V6 SUV in consideration of the sound quality preferences of customers in the U.S. First, a simple definition for engine sound under acceleration was found using order arrangement, frequency balance, and linearity. These elements are the product of commonly used characteristics in conventional development and can be applied simply when setting component targets. The development focused on order arrangement as the most important of these elements, and sounds with and without integer orders were selected as target candidates. Next, subjective auditory evaluations were performed in the U.S. using digitally processed sounds and an evaluation panel comprising roughly 40 subjects. The target sound was determined after classifying the results of this evaluation using cluster analysis.

Design of cylinder heads involves complex constraints that must satisfy thermal, strength, performance, and manufacturing requirements which present a great challenge for successful development. During development of a new highly loaded cylinder head, CAE methods predicted unacceptable fatigue safety factors for the initial prototype design. Hydropulsator component testing was undertaken and the results were correlated with the analysis predictions using a statistical method to calculate failure probability. Shape optimization was undertaken to improve high cycle fatigue safety in vulnerable regions of the cylinder head water jacket for the subsequent design release. The optimization process provided more efficient design guidance than previously discovered through a traditional iterative approach. Follow-on investigations examined other shape optimization software for fatigue improvement in the cylinder head.

The present contribution gives an overview of the use of different simulation tools for the optimization of injection parameters of a diesel engine. With a one-dimensional tool, the behavior of the mechanics and fluid dynamics of the entire injection system is calculated. This simulation provides information on the dynamic needle lift, injection rates, pressures, etc. The flow within the injector is simulated using a three-dimensional CFD tool. By use of a two-phase model, it is possible to analyze the cavitating flow inside the injector and to calculate the effective nozzle hole area as well as the exit flow characteristics. Mixture formation, combustion and pollutant formation simulation is performed adopting three-dimensional CFD. In order to provide the initial and boundary conditions for the engine CFD simulation and to optimize the engine cycle performance a one-dimensional tool is adopted.

A TGDI (turbocharged gasoline direct injection) engine is developed to realize both excellent fuel economy and high dynamic performance to guarantee fun-to-drive. In order to achieve this target, it is of great importance to develop a superior combustion system for the target engine. In this study, CFD simulation analysis, steady flow test and transparent engine test investigation are extensively conducted to ensure efficient and effective design. One dimensional thermodynamic simulation is firstly conducted to optimize controlling parameters for each representative engine operating condition, and the results serve as the input and boundary condition for the subsequent Three-dimensional CFD simulation. 3D CFD simulation is carried out to guide intake port design, which is then measured and verified on steady flow test bench.

Alternative fuels, especially fuels based on biological matter, are gaining more and more attention. Not only as a pure substitute of oil but also in terms of a possibility for further reduction in emission and as an option to improve the global CO2 balance. For improving the engine performance (emissions, fuel consumption, torque and drivability) the adjustment of fuel injection, the fuel evaporation process and the combustion process itself is paramount. In order to exploit the full potential of alternative fuels excellent knowledge of the fuel properties, including the impact on ignition and flame propagation, is required. This needs suitable tools for analysis of the fuel injection and combustion process. These tools have to support the optimization of the combustion system and the dynamic engine calibration for lowest emissions and most efficient use of fuel. As the term “Alternative Fuels” covers a very wide area a brief overview on available fuel types will be made.

Meeting the stringent efficiency demands of next generation direct injection engines requires not only optimization of the injection system and combustion chamber, but also an optimal in-cylinder swirling charge flow. This charge motion is largely determined by the shape of the intake port arm geometry and the valve position. In this paper, we outline an extensible methodology implemented in OPENFOAM® for multi-objective geometry optimization based on the continuous adjoint. The adjoint method has a large advantage over traditional optimization approaches in that its cost is not dependent upon the number of parameters being optimized. This characteristic can be used to treat every cell in the computational domain as a tunable parameter - effectively switching cells "on" or "off" depending on whether this action will help improve the objectives.

A calibration and validation workflow will be presented in this paper, which utilizes common static global models for fuel consumption, NOx and soot. Due to the applicability for warm-up tests, e.g. New European Driving Cycle (NEDC), the models need to predict the temperature influence and will be fitted with measuring data from a conditioned engine test bed. The applied model structure consisting of a number of global data-based sub-models is configured especially for the requirements of multi-injection strategies of common rail systems. Additionally common global models for several constant coolant water temperature levels are generated and the workflow tool supports the combination and segmentation of global nominal map with temperature correction maps for seamless and direct ECU setting.

The rapidly growing complexity and the growing cross linking of powertrain components leads to longer development times, especially in the vehicle calibration process. The number of systems which need to be fitted to each other and the number of parameters to be calibrated in the particular systems are increasing tremendously. The extensive use of simulation promises to reduce the calibration effort by providing pre-optimized parameter sets. This paper describes a new simulation methodology by the interlinking of advanced vehicle simulation and evaluation tools, in particular the AVL-tools CRUISE, VSM and DRIVE. This methodology allows to semi automatically pre-optimize powertrain and vehicle parameters before hardware is involved. So far the pre-calibration of vehicle and powertrain parameters by simulation was not satisfying because of the missing of a reliable evaluation tool for the produced simulation results.

The de-icing process of the windscreen is a demanding problem in car climatization. In the first stages of the development procedure of air ducts, the numerical simulation plays an important role due to economy of time and money. Unfortunately, the available numerical methods for the generation of the computational grid and the simulation of the de-icing process are very time consuming and are complicated in handling. Therefore normally the quality of the de-icing process is evaluated with simplified simulation procedures or even with measurements late in the design process and necessary modifications are again time and cost consuming. The aim of this paper is to describe new methods for the de-icing simulation that will reduce meshing and calculation time by showing accurate results.

A uniform flow distribution at converter inlet is one of the fundamental requirements to meet high catalytic efficiency. Commonly used tools for optimization of the inlet flow distribution are flow measurements as well as CFD analysis. This paper puts emphasis on the experimental procedures and results. The interaction of flow measurements and CFD is outlined. The exhaust gas flow is transient, compressible and hot, making in-situ flow measurements very complex. On the other hand, to utilize the advantages of flow testing at steady-state and cold conditions the significance of these results has to be verified first. CFD analysis under different boundary conditions prove that - in a first approach - the flow situation can be regarded as a sequence of successive, steady-state situations. Using the Reynolds analogy a formula for the steady-state, cold test mass flow is derived, taking into account the cylinder displacement and the rated speed.

To meet the future demands on internal combustion engines regarding efficiency emissions and durability all design parameters must be optimized together. As a result of progress in material engineering fuel injection technology turbo charging technology exhaust gas after treatment there arise a multiplicity of possible parameters, such as: design parameters (compression ratio, dimensioning depending on peak firing pressure and mean effective pressure), injection system (rate shaping, split injection, injection pressure, hole diameter), air management (turbo charging with or without VTG, EGR rate) combustion optimization (timing, air access ratio). The interaction of all these parameters can not be over-looked without simulation and optimization tools. This is valid for the concept layout, the optimization and the application process later on.

For the development of complex control algorithms and strategies the engine and powertrain test bed offers a number of advantages over the development in the prototype vehicle. The paper discusses how state-of-the-art simulation techniques can contribute to a continuous development process, which is based upon offline simulation using hardware in the loop, the utilization of modern test bed technology up to vehicle adjustment. The integration of hardware-in-the-loop testing together with vehicle and transmission simulation on the testbed allows to speed up the optimization of fuel consumption, emissions and driveability in an early stage in the development process. The available software tools are presented and application examples are given.

Increasing powertrain complexity and the growing number of vehicle variants are putting a strain on current calibration development processes. This is particularly challenging for vehicle drivability calibration, which is traditionally completed late in the development cycle, only after mature vehicle hardware is available. Model-based calibration enables a shift in development tasks from the real world to the virtual world, allowing for increased system robustness while reducing development costs and time. A unique approach for drivability calibration was developed by incorporating drivability analysis software with online optimization software into a virtual engine test cell environment. Real-time, physics-based engine and vehicle simulation models were coupled with real engine controller hardware and software to execute automated drivability calibration within this environment.

Precise three-dimensional dummy head trajectories during crash tests are very important for vehicle safety development. To determine precise trajectories with a standard deviation of approximately 5 millimeters, three-dimensional video analysis is an approved method. Therefore the tracked body is to be seen on at least two cameras during the whole crash term, which is often not given (e.g. head dips into the airbag). This non-continuity problem of video analysis is surmounted by numerical integration of differential un-interrupted electrical rotation and acceleration sensor signals mounted into the tracked body. Problems of this approach are unknown sensor calibration errors and unknown initial conditions, which result in trajectory deviations above 10 centimeters.

This paper gives insights in the theoretical measurement uncertainty of E-Drive rotor position dependent results, like Id and Iq calculations, done by a modern propulsion power analyzer (PA). The calculation of Id and Iqis fundamental to perform control optimization and application tasks for an E-Drive system. To optimize the E-Drive system application towards e.g., best efficiency, best performance, or improved NVH the importance of the testing toolchain is described: a power analyzer delivering the required results, an automation system, and a Design of Experiment tool to set improved target values. Consequently, inverters applications featuring field-oriented control (FOC) with permanent magnet synchronous machines (PMSM) are updated with a chosen control strategy. For achieving a certain behavior of an E-Drive, different degrees of freedom in the Inverter Control Unit are available; Lookup tables Id and Iq represent two fundamental application labels to be considered.

The aerodynamic optimization of an AUDI Q5 vehicle is presented using the continuous adjoint approach within the OpenFOAM framework. All calculations are performed on an unstructured automatically generated mesh. The primal flow, which serves as input for the adjoint method, is calculated using the standard CFD process at AUDI. It is based on DES calculations using a Spalart-Allmaras turbulence model. The transient results of the primal solution are time averaged and fed to a stationary adjoint solver using a frozen turbulence assumption. From the adjoint model, drag sensitivity maps are computed and measures for drag reduction are derived. The predicted measures are compared to CFD simulations and to wind tunnel experiments at 1:4 model scale. In this context, general challenges, such as convergence and accuracy of the adjoint method are discussed and best practice guidelines are demonstrated.