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In the virtual development process validated simulation models are requested to accurately predict power train vibration and comfort phenomena. Conclusions from refined parameter studies enable to avoid costly tests on rigs and on the road. Thereby, an appropriate modeling approach for specific phenomena has to be chosen to ensure high quality results. But then, parameters for characterizing the dynamic properties of components are often insufficient and have to be roughly estimated in this development stage. This results in a imprecise prediction of power train resonances and in a less conclusive understanding of the considered phenomena. Conclusions for improvements remain uncertain. This paper deals with the two different aspects of model refinement and parameter updating. First an existing power train model (predecessor power train) is analyzed whether the underlying modeling approach can reproduce the physical behavior of the power train dynamics adequately.

The need for significant reduction of fuel consumption and CO₂ emissions has become the major driver for development of new vehicle powertrains today. For the medium term, the majority of new vehicles will retain an internal combustion engine (ICE) in some form. The ICE may be the sole prime mover, part of a hybrid powertrain or even a range extender; in every case potential still exists for improvement in mechanical efficiency of the engine itself, through reduction of friction and of parasitic losses for auxiliary components. A comprehensive approach to mechanical efficiency starts with an analysis of the main contributions to engine friction, based on a measurement database of a wide range of production engines. Thus the areas with the highest potential for improvement are identified. For each area, different measures for friction reduction may be applicable with differing benefits.

This works presents a real-time capable simulation model for dual fuel operated engines. The computational performance is reached by an optimized filling and emptying modeling approach applying tailored models for in-cylinder combustion and species transport in the gas path. The highly complex phenomena taking place during Diesel and gasoline type combustion are covered by explicit approaches supported by testbed data. The impact of the thermodynamic characteristics induced by the different fuels is described by an appropriate set of transport equations in combination with specifically prepared property databases. A thermodynamic highly accurate 6-species approach is presented. Additionally, a 3-species and a 1-species transport approach relying on the assumption of a lumped fuel are investigated regarding accuracy and computational performance. The comparison of measured and simulated pressure and temperature traces shows very good agreement.

To promote advanced combustion strategies complying with stringent emission regulations of CI engines, computational models have to accurately predict the injector inner flow and cavitation development in the nozzle. This paper describes a coupled 1D/2D/3D modeling technique for the simulation of fuel flow and nozzle cavitation in diesel injection systems. The new technique comprises 1D fuel flow, 2D multi-body dynamics and 3D modeling of nozzle inner flow using a multi-fluid method. The 1D/2D model of the common rail injector is created with AVL software Boost-Hydsim. The computational mesh including the nozzle sac with spray holes is generated with AVL meshing tool Fame. 3D multi-phase calculations are performed with AVL software FIRE. The co-simulation procedure is controlled by Boost-Hydsim. Initially Hydsim performs a standalone 1D simulation until the needle lift reaches a prescribed tolerance (typically 2 to 5 μm).

One of the most important safety issues for automotive engineering is to avoid any fire due to the ignition of flammable liquids, which may result from leaks. Fire risk is a combination of hot temperature, fast vaporisation and accumulation of vapor in a cavity. In IC engines, potentially flammable liquids are fuel and oil. To guarantee safety, flammable liquids must not come into contact with hot parts of the engine. Consequently, shields are designed to guide the flow path of possible leakages and to take any flammable liquid out of the hot areas. Simulation is a great help to optimize the shape of the shield by investigating a large number of possible leakages rapidly. Recent breakthroughs in numerical methods make it possible to apply simulations to industrial design concepts. The employed approach is based on the Lagrangian Smoothed Particle Hydrodynamics (SPH) method.

This paper describes the simulation tool chain serving to design and optimize the transmission of an electric axle drive from concept to final design with respect to NVH. A two-stage transmission of an eAxle is designed from scratch by the initial layout of gears and shafts, including the optimization of gear micro geometry. After the shaft system and bearings are defined, the concept design of the transmission housing is evaluated with the help of a basic topology optimization regarding stiffness and certain eigenfrequencies. In the next step a fully flexible multi-body dynamic (MBD) and acoustic analysis of the transmission is performed using internally calculated excitations due to gear contact and bearing interaction with shaft and gear dynamics for the entire speed and load range. Critical operating conditions in terms of shaft dynamics, structure borne noise and noise radiation are evaluated and selected as target for optimization in the following steps.

Beside hard facts as performance, emissions and fuel consumption especially the brand specific attributes such as styling and sound are very emotional, unique selling prepositions. To develop these emotional characters, within the given boundary conditions of the future pass-by regulation, it is necessary to define them at the very beginning of the project and to follow a consequent development process. The following paper shows examples of motorcycle NVH development work on noise cleaning and sound engineering using a hybrid development process combining front loading, simulation and testing. One of the discussed solutions is the investigation of a piston pin offset in combination with a crankshaft offset for the reduction of friction. The optimization of piston slap noise as a result of the piston secondary motion was performed by simulation. As another example a simulation based development was performed for the exhaust system layout.

Today's powertrains are becoming more and more complex due to the increasing number of gear box types requiring gearshift patterns like conventional (equipped with GSI) and automatic-manual transmissions (AT, AMT), double clutch and continuous variable transmissions (DCT, CVT). This increasing variety of gear boxes requires a higher effort for the overall optimization of the powertrain. At the same time, it is necessary to assess the impact of different powertrains and control strategies on CO₂ emissions very early in the development process. The optimization of Gear Shift Patterns (G.S.P.) has to fulfill multiple constraints in terms of objective customers' requirements, like driveability, NVH, performance, emissions and fuel consumption. For these reasons, RENAULT and AVL entered an engineering collaboration in order to develop a dedicated simulation tool: CRUISE GSP.

The presented paper deals with a methodology to model cycle-to-cycle variations (CCV) in 0-D/1-D simulation tools. This is achieved by introducing perturbations of combustion model parameters. To enable that, crank angle resolved data of individual cycles (pressure traces) have to be available for a reasonable number of engine cycles. Either experimental data or 3-D CFD results can be applied. In the presented work, experimental data of a single-cylinder research engine were considered while predicted LES 3-D CFD results will be tested in the future. Different engine operating points were selected - both stable ones (low CCV) and unstable ones (high CCV). The proposed methodology consists of two major steps. First, individual cycle data have to be matched with the 0-D/1-D model, i.e., combustion model parameters are varied to achieve the best possible match of pressure traces - an automated optimization approach is applied to achieve that.

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 new generation of automatic transmissions is characterized by a compact and highly efficient design. By the use of a higher overall gear ratio and lightweight components combined with optimal gear set concepts it is possible to improve significantly fuel consumption and driving dynamics. Precise and efficient real time models of the whole power train including models for complex subsystems like the automatic transmission are needed to combine real hardware with virtual models on XiL test rigs. Thereby it's possible to achieve a more efficient product development process optimized towards low development costs by less needed prototypes and shorter development times by pushing front loading in the process. In this paper a new real time model for automatic transmissions including approved models for the torque converter, the lock-up clutch and the torsional damper are introduced. At the current development stage the model can be used for comfort analysis and drivability assessment.

Efficient integration of mechanics and microelectronics components is nowadays a must within the automotive industry in order to minimize integration risks and support optimization of the entire system. We propose in this work a cross domain co-simulation platform for the efficient analysis of mechatronic systems. The interfacing of two state-of-the-art simulation platforms provides a direct link between the two domains at an early development stage, thus enabling the validation and optimization of the system already during modeling phase. The proposed cross-domain co-simulation is used within our TEODACS project for the analysis of the FlexRay technology. We illustrate using a drive-by-wire use case how the different architecture choices may influence the system.

Future demands regarding emissions, fuel consumption and driveability lead to complex engine and power train control systems. The calibration of the increasing number of free parameters in the ECU's contradicts the demand for reduced time in the power train development cycle. This paper will focus on the automatic, unmanned closed loop optimization of driveability quality on a high dynamic engine test bed. The collaboration of three advanced methods will be presented: Objective real time driveability assessment, to predict the expected feelings of the buyers of the car Automatic computer assisted variation of ECU parameters on the basis of statistical methods like design of experiments (DoE). Thus data are measured in an automated process allowing an optimization based on models (e.g. neural networks).

Apart of other aspects, the interior sound of a passenger car brand has to meet customer expectations. For optimizing the sound of a passenger car, target sounds have first to be established via the operating range of the vehicle. For an effective sound engineering approach an objective description and evaluation of vehicle interior sound is beneficial. Such an objective description guarantees the effective and reproducible implementation of the required brand sound in the vehicle development process. In such a process it is necessary to reduce on the one hand annoying undesired noise aspects and to create on the other hand the relevant and necessary noise parameters to meet the target sounds head on.

The use of state of the art simulation tools for effective front-loading of the calibration process is essential to support the additional efforts required by the new Real Driving Emission (RDE) legislation. The process needs a critical model validation where the correlation in dynamic conditions is used as a preliminary insight into the bounds of the representation domain of engine mean values. This paper focuses on the methodologies for correlating dynamic simulations with emissions data measured during dynamic vehicle operation (fundamental engine parameters and gaseous emissions) obtained using dedicated instrumentation on a diesel vehicle, with a particular attention for oxides of nitrogen NOx specie. This correlation is performed using simulated tests run within AVL’s mean value engine and engine aftertreatment (EAS) model MoBEO (Model Based Engine Optimization).

The paper is devoted to the coupled 1D-3D modeling technology of injector flow and cavitation in diesel injections systems. The technology is based on the 1D simulation of the injector with the AVL software BOOST-HYDSIM and 3D modeling of the nozzle flow with AVL FIRE. The nozzle mesh with spray holes and certain part of the nozzle chamber is created with the FIRE preprocessor. The border between the 1D and 3D simulation regions can be chosen inside the nozzle chamber at any position along the needle shaft. Actual coupling version of both software tools considers only one-dimensional (longitudinal) needle motion. Forthcoming version already includes the two-dimensional motion of the needle. Furthermore, special models for the needle tip contact with the nozzle seat and needle guide contact with the nozzle wall are developed in HYDSIM. The co-simulation technology is applied for different common rail injectors in several projects.

The paper focuses on an optimization methodology, which uses Design of Experiments (DoE) methods to define component parameters of parallel hybrid powertrains such as number of gears, transmission spread, gear ratios, progression factor, electric motor power, electric motor nominal speed, battery voltage and cell capacity. Target is to find the optimal configuration based on specific customer targets (e.g. fuel consumption, performance targets). In the method developed here, the hybrid drive train configuration and the combustion engine are considered as fixed components. The introduced methodology is able to reduce development time and to increase output quality of the early system definition phase. The output parameters are used as a first hint for subsequently performed detailed component development. The methodology integrates existing software tools like AVL CRUISE [5] and AVL CAMEO [1].

In spark-ignition engines, fluctuations of the in-cylinder pressure trace and the apparent rate of heat release are usually observed from one cycle to another. These Cycle-to-Cycle Variations (CCV) are affected by the early flame development and the subsequent flame front propagation. The CCV are responsible for engine performance (e.g. fuel consumption) and the knock behavior. The occurrence of the phenomena is unpredictable and the stochastic nature offers challenges in the optimization of engine control strategies. In the present work, CCV are analyzed in terms of their impact on the engine knock behavior and the related efficiency. Target is to estimate the possible fuel consumption savings in steady-state operation and in the drivecycle, when CCV are reduced. Since CCV are immanent on real engines, such a study can only be done by means of simulation.

Dynamometer (dyno) durability testing plays a significant role in reliability and durability assessment of commercial engines. Frequently, durability test procedures are based on warranty history and corresponding component failure modes. Evolution of engine designs, operating conditions, electronic control features, and diagnostic limits have created challenges to historical-based testing approaches. A physics-based methodology, known as Load Matrix, is described to counteract these challenges. The technique, developed by AVL, is based on damage factor models for subsystem and component failure modes (e.g. fatigue, wear, degradation, deposits) and knowledge of customer duty cycles. By correlating dyno test to field conditions in quantifiable terms, such as customer equivalent miles, more effective and efficient durability test suites and test procedures can be utilized. To this end, application of Load Matrix to a heavy-duty diesel engine is presented.

Due to increasing complexity of engine electronic systems, there is a demand to handle the often more than 10,000 calibration data automatically. Establishing optimized start of injection and EGR tables of a TC DI Diesel engine by conventional methods takes about two weeks of intensive calibration work. By automatic map calibration, this task can be handled in less than 20 hours automatically, with no staff required during optimization. The benefits of automatic calibration therefore are reduced costs and faster response to any changes in parameters, even with complex multidimensional engine calibration problems. The paper describes the optimization method as well as the experimental work on the test stand that produces the results.