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Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

Engine simulation can be performed using model approaches of different depths in capturing physical effects. The present paper presents a comprehensive comparison study on seven different engine models. The models range from transient 1D cycle resolved approaches to steady-state non-dimensional maps. The models are discussed in the light of key features, amount and kind of required input data, model calibration effort and predictability and application areas. The computational performance of the different models and their capabilities to capture different transient effects is investigated together with a vehicle model under real-life driving conditions. In the trade-off field of model predictability and computational performance an innovative approach on crank-angle resolved cylinder modeling turned out to be most beneficial.

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.

In the present work, a scalable simulation methodology is presented that enables the assessment of the impact of SI-engine cycle-to-cycle combustion variations on fuel consumption and hence CO2 emissions on three different levels of modeling depth: in-cylinder, steady-state engine and transient engine and vehicle simulation. On the detailed engine combustion chamber level, a 3D-CFD approach is used to study the impact of the turbulent in-cylinder flow on the cycle-resolved flame propagation characteristics. On engine level, cycle-to-cycle combustion variations are assessed regarding their impact on indicated mean effective pressure, aiming at estimating the possible fuel consumption savings when cyclic variations are minimized. Finally, on the vehicle system level, a combined real-time engine approach with crank-angle resolved cylinder is used to assess the potential fuel consumption savings for different vehicle drivecycle conditions.

In order to meet current and future emission and CO2 targets, an efficient vehicle thermal management system is one of the key factors in conventional as well as in electrified powertrains. Global vehicle simulation is already a well-established tool to support the vehicle development process. In contrast to conventional vehicles, electrified powertrains offer an additional challenge to the thermal conditioning: the durability of E-components is not only influenced by temperature peaks but also by the duration and amplitude of temperature swings as well as temperature gradients within the components during their lifetime. Keeping all components always at the preferred lowest temperature level to avoid ageing under any conditions (driving, parking, etc.) will result in very high energy consumption which is in contradiction to the efficiency targets.

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).

Approaching engineering limits for the thermal design of battery modules requires virtual prototyping and appropriate models with respect to physical depth and computational effort. A multi-scale and multi-domain model describes the electrochemical behavior of a single battery unit cell in 1D+1D at the level of intra-cell phenomena, and it applies a 3D thermal model at module level. Both models are connected within a common vehicle simulation platform. The models are discussed with special emphasis on battery degradation such as solid electrolyte interphase layer formation, decomposition and lithium plating. The performance of the electrochemical model is assessed by discharge cycles and repeated charge/discharge simulations. The thermal module model is compared to CFD reference data and studied with respect to its grid sensitivity.

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.

The present works presents a real-time capable engine model with physical based description of the fuel injection and the combustion process. The model uses a crank-angle resolved cylinder model and a filling and emptying approach for cylinder and gas-path interaction. A common rail injection system model is developed and implemented into the real-time engine framework. The injection model calculates injection quantity and injection rate profile from the input of the ECU signals target injection pressure and injection timing. The model accounts for pressure oscillations in the injection system. A phenomenological combustion model for Diesel engines is implemented, which is based on the mixing controlled combustion modeling approach. The combustion model calculates the rate of heat release from the injection rate given by the injection model. The injection and combustion model are validated in detail against steady-state measurement data for two different passenger car sized engines.

The present work introduces an innovative mechanistically based 0D spray model which is coupled to a combustion model on the basis of an advanced mixture controlled combustion approach. The model calculates the rate of heat release based on the injection rate profile and the in-cylinder state. The air/fuel distribution in the spray is predicted based on momentum conservation by applying first principles. On the basis of the 2-zone cylinder framework, NOx emissions are calculated by the Zeldovich mechanism. The combustion and emission models are calibrated and validated with a series of dedicated test bed data specifically revealing its capability of describing the impact of variations of EGR, injection timing, and injection pressure. A model based optimization is carried out, aiming at an optimum trade-off between fuel consumption and engine-out emissions. The findings serve to estimate an economic optimum point in the NOx/BSFC trade-off.

The present work introduces a fully integrated real-time (RT) capable engine and vehicle model. The gas path and drive line are described in the time domain of seconds whereas the reciprocating characteristics of an IC engine are reflected by a crank angle resolved cylinder model. The RT engine model is derived from a high fidelity 1D cycle simulation and gas exchange model to support an efficient and consistent transfer of model data like geometries, heat transfer or combustion. The workflow of model calibration and application is outlined and base ECU functionalities for boost pressure, EGR, smoke and idle speed control are applied for transient engine operation. Steady state results of the RT engine model are compared to experimental data and 1D high fidelity simulations for 19 different engine load points. In addition an NEDC (New European Drive Cycle) is simulated and results are evaluated with data from chassis dynamometer measurements.

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 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.

Two thread forming processes, rolling and cutting, were studied for their effects on fatigue in cast aluminum 319-T7. Material was excised from cylinder blocks and tested in rotating-bending fatigue in the form of unnotched and notched specimens. The notched specimens were prepared by either rolling or cutting to replicate threads in production-intent parts. Cut threads exhibited conventional notch behavior for notch sensitive materials. In contrast, plastic deformation induced by rolling created residual compressive stresses in the notch root and significantly improved fatigue strength to the point that most of the rolled specimens broke outside the notch. Fractographic and metallographic investigation showed that cracks at the root of rolled notches were deflected upon initiation. This lengthened their incubation period, which effectively increased fatigue resistance.

In this paper, a recently improved Computational Fluid Dynamics (CFD) methodology for virtual prototyping of the heat treatment of cast aluminum parts, above most of cylinder heads of internal combustion engines (ICE), is presented. The comparison between measurement data and numerical results has been carried out to simulate the real time immersion quenching cooling process of realistic cylinder head structure using the commercial CFD code AVL FIRE®. The Eulerian multi-fluid modeling approach is used to handle the boiling flow and the heat transfer between the heated structure and the sub-cooled liquid. While for the fluid region governing equations are solved for each phase separately, only the energy equation is solved in the solid region. Heat transfer coefficients depend on the boiling regimes which are separated by the Leidenfrost temperature.

Fuel consumption is the most important contributor to the total cost of ownership for mass produced motorcycles. Therefore, best fuel economy is one main influencing criteria for a decision to purchase motorcycles. Furthermore, increasingly stringent emission legislations limit and additional OBD requirements must be fulfilled. A new combined test approach has been developed that minimizes accuracy losses in the development process which compensates for the variability of driving behavior in the chassis dyno environment. An engine testbed combined with a belt drive transmission enables operation in single engine or in Powerpack (i.e. internal combustion engine including transmission) configuration as well as under steady state or dynamic operating mode. Since the belt drive transmission is integrated in the test rig, realistic inertia situation for the single engine operating test configuration is ensured.

In recent years concern has arisen over a new combustion anomaly, which was not commonly associated with naturally aspirated engines. This phenomenon referred to as Low-Speed Pre-Ignition (LSPI), which often leads to potentially damaging peak cylinder pressures, is the most important factor limiting further downsizing and the potential CO2 benefits that it could bring. Previous studies have identified several potential triggers for pre-ignition where engine oil seems to have an important influence. Many studies [1], [2] have reported that detached oil droplets from the piston crevice volume lead to auto-ignition prior to spark ignition. Furthermore, wall wetting and subsequently oil dilution [3] and changes in the oil properties by impinging fuel on the cylinder wall seem to have a significant influence in terms of accumulation and detachment of oil-fuel droplets in the combustion chamber.

Due to future directives of the European Union regarding fuel consumption and CO2 emissions the automotive industry is forced to develop new and unconventional technologies. These include for example stop-start-systems, cylinder deactivation or even reduction of the number of cylinders which however lead to unusual acoustical perceptions and customer complaints. Therefore, it is necessary to evaluate the sound character of engines with low numbers of cylinders (2 and 3 cylinders) and also the differences to the character of the more common 4-cylinder engines. Psychoacoustic parameters are used to describe and understand the differences. Based on the gained knowledge possible potentials for improvement can be derived in the future. The used data base consists of artificial head recordings of car interior noise according to defined driving conditions measured on the AVL test track. Naturally, there are more recordings available for 4-cylinder engines than for 2- and 3-cylinder engines.

The further increase in the efficiency of heavy-duty engines is essential in order to reduce CO2 emissions in the transport sector. This is also valid for the future use of alternative fuels, which can be CO2-neutral, but can cause higher total costs of ownership due to higher prices and limited availability. In addition to thermodynamic optimization, the reduction of mechanical losses is of great importance. In particular, there is a high potential in the piston bore interface, since continuously increasing cylinder pressures have a strong influence on the frictional and lateral piston forces. To meet these future challenges of increasing heavy-duty engine efficiency, AVL has developed a floating liner engine for heavy-duty applications based on its tried and tested passenger car floating liner concept.

This work presents a physical model that calculates the efficiency maps of the inverter-fed Permanent Magnet Synchronous Machine (PMSM) drive. The corresponding electrical machine and its controller are implemented based on the two-phase (d-q) equivalent circuits that take into account the copper loss as well as the iron loss of the PMSM. A control strategy that optimizes the machine efficiency is applied in the controller to maximize the possible output torque. In addition, the model applies an analytical method to predict the losses of the voltage source inverter. Consequently, the efficiency maps within the entire operating region of the PMSM drive can be derived from the simulation results, and they are used to represent electric drives in the system simulation model of electric vehicles (EVs).