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Due to the contradiction of the market demands and legal issues OEMs are forced to invest in finding concepts that assure high fuel economy, low exhaust emissions and high specific power at the same time. Since mechanical losses may amount up to 10 % of the fuel energy, a key to realise such customer/government specific demands is the improvement of the mechanical performance of the engines, which comprises mainly friction decrease and lightweight design of the engine parts. In order to achieve the mentioned objectives, it has to be checked carefully for each component whether the design potentials are utilized. Many experimental studies show that there is still room for optimization of the cranktrain parts, especially for the crankshaft. A total exploitation of the crankshaft potentials is only possible with advanced calculation approaches that ensure the component layout within design limits.

Downsizing is an effective way to further improve the efficiency of SI engines. To make most of this concept, the compression ratio has to be adjusted during engine operation. Thus, the efficiency disadvantages during part load can be eliminated. A fuel consumption reduction of up to 30% can be realized compared to naturally aspirated engines of the same power. After the assessment of several known concepts it turned out that the eccentric crankshaft positioning represents an appropriate solution which meets the requirements of good adjustability, unaltered inertia forces, low power demand of the positioning device and reasonable design effort. The basic challenges posed by the eccentric crankshaft positioning have been tackled, namely the crankshaft bearing and the integration of the newly developed power take-offs which have almost no influence on the base design.

During a thermal regeneration of a Diesel particulate filter (DPF) the temperature inside the DPF may raise above critical thresholds in an uncontrolled way (thermal shock). Especially driving conditions with a comparable low exhaust gas mass flow and high oxygen content like idle speed may create a thermal shock. This paper presents a concept for an ECU software structure to prevent the DPF from reaching improper temperatures and the methodology in order to calibrate this ECU structure. The concept deals in general with a closed-loop control of the exhaust gas air-fuel-ratio during the critical engine operation phases. Those critical operation phases are identified at the engine test bench during “Drop-to-Idle” and “Drop-to-Overrun” experiments. The experiments show that those phases are critical having on the one hand a low exhaust gas mass flow and on the other hand a high oxygen percentage in the exhaust gas.

A new index to evaluate the inherent soot reduction in a diesel-like spray plume is proposed in this study. The index is named “Oxidation Potential Number” and was derived with the help of a computational fluid dynamics (CFD) software. C8 - C16 n-alkanes, 1-alcohols and di-n-ethers were studied with the help of this index over four part load engine operating conditions, representative of a C-class diesel vehicle. The CFD modelling results have shown that C8 molecules feature a higher potentiality to reduce the soot. Thus, C8 molecules were tested in a single cylinder diesel engine over the same operating conditions. In conclusion, the proposed index is compared with the soot engine out emission.

A fuel cell based Auxiliary Power Unit (APU) represents a rather complex technical system consisting of different subsystems, components and low-level controllers. Particularly in the case of gasoline-fueled systems, a sophisticated supervisory control is needed to manage the sequential control and to achieve fault tolerant and fail-safe operation. In this paper, a state machine-based APU control concept is presented, offering a transparent and modular structure. In addition to a superior control system (top level supervisor) that manages the overall strategies and the interaction of all subsystems, each subsystem is equipped with its own subsystem control (second level supervisor). This controller is responsible for all subsystem specific issues. The APU control concept was implemented using Matlab®/Simulink® and applied on a rapid prototyping controller unit.

This paper focuses on start-up technology for fuel processing systems with special emphasis on gasoline fueled burners. Initially two different fuel processing systems, an autothermal reformer with preferential oxidation and a steam reformer with membrane, are introduced and their possible starting strategies are discussed. Energy consumption for preheating up to light-off temperature and the start-up time is estimated. Subsequently electrical preheating is compared with start-up burners and the different types of heat generation are rated with respect to the requirements on start-up systems. Preheating power for fuel cell propulsion systems necessarily reaches up to the magnitude of the electrical fuel cell power output. A gasoline fueled burner with thermal combustion has been build-up, which covers the required preheating power.

This article discusses highly flexible and accurate physics-based mean value modeling (MVM) for internal combustion engines and its wide applicability towards virtual vehicle calibration. The requirement to fulfill the challenging Real Driving Emissions (RDE) standards has significantly increased the demand for precise engine models, especially models regarding pollutant emissions and fuel economy. This has led to a large increase in effort required for precise engine modeling and robust model calibration. Two best-practice engine modeling approaches will be introduced here to satisfy these requirements. These are the exclusive MVM approach, and a combination of MVM and a Design of Experiments (DOE) model for heterogeneous multi-domain engine systems.

Knock control is one of the most vital functions for safe and fuel-efficient operation of gasoline engines. However, all knock control strategies rely on accurate knock detection to operate the engine close to the optimal set point. Knock detection is usually calibrated on the engine test bench, requiring the engine to run with knocking combustion in a time-consuming multi-stage campaign. Model-based calibration significantly reduces calibration loops on the test bench. However, this method requires a large effort in building and validating the model, which is often limited by the lack of function documentation, available measurements or hardware representation. As the software models are often not available, function structures vary between manufacturers and sub model functions are often documented as black boxes. Hence, using the model-based approach is not always possible.

In this paper a new approach is presented to evaluate the combustion behaviour of homogeneous gasoline engines by predicting burn delay and -duration in a way which can be obtained under the time constraints of the development process. This is accomplished by means of pure in-cylinder flow simulations without a classical combustion model. The burn delay model is based on the local distribution of the turbulent flow near the spark plug. It features also a methodology to compare different designs regarding combustion stability. The correlation for burn duration uses a turbulent characteristic number that is obtained from the turbulent flow in the combustion chamber together with a model for the turbulent burning velocity. The results show good agreement with the combustion process of the analyzed engines.

The loads on the plain bearings of modern combustion engines increase continuously. Reasons for this development are increasing engine speeds on gasoline engines, growing cylinder peak pressures at diesel engines and both combined with the steady trend toward light weight concepts. The still significantly increasing power output of modern engines has to be combined with actions reducing the engine friction losses, as for example smaller bearing dimensions or lower engine oil viscosities. At the same time the comfort, lifetime and engine service interval targets are aggravating boundary conditions. This development leads to the point, where former approaches toward plain bearing layout reach their systematic limitations - a first indication are bearing failures, which occur even though all conventional layout criteria's are fulfilled. Further effects need to be considered to simulate the behavior of the plain bearing under the boundary conditions of a fired combustion engine.

Due to the complex powertrain layout in hybrid vehicles, different configurations concerning internal combustion engine, electric motor and transmission can be combined - as is demonstrated by currently produced hybrid vehicles ([1], [2]). At the Institute for Combustion Engines (VKA) at RWTH Aachen University a combination of simulation, Design of Experiments (DoE) and numerical optimization methods was used to optimize the combustion engine, the powertrain configuration and the operation strategy in hybrid powertrains. A parametric description allows a variation of the main hybrid parameters. Parallel as well as power-split hybrid powertrain configurations were optimized with regard to minimum fuel consumption in the New European Driving Cycle (NEDC). Besides the definition of the optimum configuration for engine, powertrain and operation strategy this approach offers the possibility to predict the fuel consumption for any modifications of the hybrid powertrains.

Sustainable and energy-efficient consumption is a main concern in contemporary society. Driven by more stringent international requirements, automobile manufacturers have shifted the focus of development into new technologies such as Hybrid Electric Vehicles (HEVs). These powertrains offer significant improvements in the efficiency of the propulsion system compared to conventional vehicles, but they also lead to higher complexities in the design process and in the control strategy. In order to obtain an optimum powertrain configuration, each component has to be laid out considering the best powertrain efficiency. With such a perspective, a simulation study was performed for the purpose of minimizing well-to-wheel CO2 emissions of a city car through electrification. Three different innovative systems, a Series Hybrid Electric Vehicle (SHEV), a Mixed Hybrid Electric Vehicle (MHEV) and a Battery Electric Vehicle (BEV) were compared to a conventional one.

The current and future restrictions on pollutant emissions from internal combustion engines require a holistic investigation of the abilities of alternative fuels to optimize the combustion process and ensure cleaner combustion. In this regard, the Tailor-made Fuels from Biomass (TMFB) Cluster at Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen University aims at designing production processes for biofuels as well as fuels optimal for use in internal combustion engines. The TMFB Cluster's scientific approach considers the molecular structure of the fuels as an additional degree of freedom for the optimization of both the production pathways and the combustion process of such novel biofuels. Thus, the model-based specification of target parameters is of the utmost importance to improve engine combustion performance and to send feedback information to the biofuel production process.

The growing number of passenger car variants and derivatives in all global markets, their high degree of software differentiability caused by regionally different legislative regulations, as well as pronounced market-specific customer expectations require a continuous optimization of the entire vehicle development process. In addition, ever stricter emission standards lead to a considerable increase in powertrain hardware and control complexity. Also, efforts to achieve market and brand specific multistep adjustable drivability characteristics as unique selling proposition, rapidly extend the scope for calibration and testing tasks during the development of powertrain control units. The resulting extent of interdependencies between the drivability calibration and other development and calibration tasks requires frontloading of development tasks.

To achieve global market and brand specific drivability characteristics as unique selling proposition for the increasing number of passenger car derivatives, an objectified evaluation approach for the drivability capabilities of the various cars is required. Thereto, it is necessary to evaluate the influence of different engine concepts in various complex and interlinked powertrain topologies during engine load change maneuvers based on physical criteria. Such an objectification approach enables frontloading of drivability related engineering tasks by the execution of drivability development and calibration work within vehicle subcomponent-specific closed-loop real-time co-simulation environments in early phases of a vehicle development program. So far, drivability functionalities could be developed and calibrated only towards the end of a vehicle development program, when test vehicles with a sufficient level of product maturity became available.

Numerical analyses of the liquid fuel injection and subsequent fuel-air mixing for a high-tumble direct injection engine with an active pre-chamber ignition system at operation conditions of 2000 RPM are presented. The Navier-Stokes equations for compressible in-cylinder flow are solved numerically using a hierarchical Cartesian mesh based finite-volume method. To determine the fuel vapor before ignition large-eddy flow simulations are two-way coupled with the spray droplets in a Lagrangian Particle Tracking (LPT) formulation. The combined hierarchical Cartesian mesh ensures efficient usage of high performance computing systems through solution adaptive refinement and dynamic load balancing. Computational meshes with approximately 170 million cells and 1.0 million spray parcels are used for the simulations.

The calibration of Engine Control Units (ECUs) for road vehicles is challenged by stringent legal and environmental regulations, coupled with short development cycles. The growing number of vehicle variants, although sharing similar engines and control algorithms, requires different calibrations. Additionally, modern engines feature increasingly number of adjustment variables, along with complex parallel and nested conditions within the software, demanding a significant amount of measurement data during development. The current state-of-the-art (White Box) model-based ECU calibration proves effective but involves considerable effort for model construction and validation. This is often hindered by limited function documentation, available measurements, and hardware representation capabilities. This article introduces a model-based calibration approach using Neural Networks (Black Box) for two distinct ECU functional structures with minimal software documentation.

Current simulation tools for the investigation of the dynamic system response as well as for the component stresses on the basis of multi-body and finite-element techniques are integral part of today's powertrain development efforts. These tools are typical used for the analysis and optimization of shafts, clutches, chain/belt drives, bearings, levers, brackets, housings and many other components. An exception is made by gears which today are still frequently investigated by the help of semi-empirical methods based on DIN, ISO, AGMA and the specific knowledge base of well experienced developers. The main difficulty is that the gears are rolling off via large contact surfaces with complex nonlinear mechanical contact properties. Within the scope of research work FEV developed a new method for the analysis and optimization of gear drives based on comercial multi-body and finite-element software platforms.

In this work, a transport and mixing model that calculates mixing in thermodynamic phase space was derived and validated. The mixing in thermodynamic multizone space is consistent to the one in the spatially resolved physical space. The model is developed using a turbulent channel flow as simplified domain. This physical domain of a direct numerical simulation (DNS) is divided into zones based on the quantitative value of transported scalars. Fluxes between the zones are introduced to describe mixing from the transport equation of the probability density function based on the mixing process in physical space. The mixing process of further scalars can then be carried out with these fluxes instead of solving additional transport equations. The relationship between the exchange flux in phase space and the concept of scalar dissipation are shown and validated by comparison to DNS results.

Combustion and pollutant formation in a DI-Diesel engine are numerically investigated using the Eulerian Particle Flamelet Model (EPFM). A baseline case for part load operating conditions is considered as well as an EGR variation. The surrogate fuel consisting of n-decane (70% liquid volume fraction) and α-methylnaphthalene (30% liquid volume fraction) is used in the simulation. Results are compared to experimental data that has been obtained using real diesel fuel. The effect of multiple flamelets on the simulation of the auto-ignition process and the pollutant formation is discussed and a converging behavior of the model with respect to the number of flamelets is found. The effect of homogenization of the three-dimensional mixture field is investigated and it has been included in the formulation of the scalar dissipation rate.