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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.

Fuels derived from biomass will most likely contain oxygen due to the high amount of hydrogen needed to remove oxygen in the production process. Today, alcohol fuels (e. g. ethanol) are well understood for spark ignition engines. The Institute for Combustion Engines at RWTH Aachen University carried out a fuel investigation program to explore the potential of alcohol fuels as candidates for future compression ignition engines to reduce engine-out emissions while maintaining engine efficiency and an acceptable noise level. The soot formation and oxidation process when using alcohol fuels in diesel engines is not yet sufficiently understood. Depending on the chain length, alcohol fuels vary in cetane number and boiling temperature. Decanol possesses a diesel-like cetane number and a boiling point in the range of the diesel boiling curve. Thus, decanol was selected as an alcohol representative to investigate the influence of the oxygen content of an alcohol on the combustion performance.

The finite nature and instability of fossil fuel supply has led to an increasing and enduring investigation demand of alternative and regenerative fuels. The Institute for Combustion Engines at the RWTH Aachen University carried out an investigation program to explore the potential of tailor made fuels to reduce engine-out emissions while maintaining engine efficiency and an acceptable noise level. To enable optimum engine performance a range of different hydrocarbons having different fuel properties like cetane number, boiling temperature and different molecular compositions have been investigated. Paraffines and naphthenes were selected in order to better understand the effects of molecular composition and chain length on emissions and performance of an engine that was already optimized for advanced combustion performance. The diesel single-cylinder research engine used in this study will be used to meet Euro 6 emissions limits and beyond.

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.

The use of pistons made of fine grain carbon was investigated in a spark-ignition engine within a European Community funded research project (TPRO-CT92-0008). Pistons were designed and manufactured and then tested in a single cylinder engine. Due to the carbon material's lower coefficient of thermal expansion the top land clearance between piston and cylinder can be reduced by a factor of three in comparison to standard aluminium designs. Under steady-state part-load operating conditions the emission of unburned hydrocarbons can be reduced by more than 15% compared to aluminium pistons, without significant penalties in NOx-emissions. Simultaneously, a small improvement in fuel economy of about 2% is observed. At full-load blow-by leakage flow is reduced by more than 50%. The piston crown temperature is about 30°C higher with the carbon piston than with the standard aluminium piston, due to the lower thermal conductivity of the carbon material.

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.

Pre-ignition in a boosted spark-ignition engine can be triggered by several mechanisms, including oil-fuel droplets, deposits, overheated engine components and gas-phase autoignition of the fuel-air mixture. A high pre-ignition resistance of the fuel used mitigates the risk of engine damage, since pre-ignition can evolve into super-knock. This paper presents the pre-ignition propensities of 11 RON 89-100+ gasoline fuel blends in a single-cylinder research engine. Albeit the addition of two high-octane components (methanol and reformate) to a toluene primary reference fuel improved the pre-ignition resistance, one high-RON fuel experienced runaway pre-ignition at relatively low boost pressure levels. A comparison of RON 96 blends showed that the fuel composition can affect pre-ignition resistance at constant RON.

Lignocellulosic biomass consists of (hemi-) cellulose and lignin. Accordingly, an integrated biorefinery will seek to valorize both streams into higher value fuels and chemicals. To this end, this study evaluated the overall combustion performance of both cellulose- and lignin derivatives, namely the high cetane number (CN) di-n-butyl ether (DnBE) and low CN anisole, respectively. Said compounds were blended both separately and together with EN590 diesel. Experiments were conducted in a single cylinder compression ignition engine, which has been optimized for improved combustion characteristics with respect to low emission levels and at the same time high fuel efficiency. The selected operating conditions have been adopted from previous “Tailor-Made Fuels from Biomass (TMFB)” work.

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.

Downsizing of highly-boosted spark-ignition (SI) engines is limited by pre-ignition, which may lead to extremely strong knocking and severe engine damage. Unfortunately, the concerning mechanisms are generally not yet fully understood, although several possible reasons have been suggested in previous research. The primary objective of the present paper is to investigate the influence of molecular bio-fuel structure on the locations of pre-ignition in a realistic, highly-charged SI engine at low speed by state-of-the-art optical measurements. The latter are conducted by using a high-sensitivity UV endoscope and an intensified high-speed camera. Two recently tested bio-fuels, namely tetrahydro-2-methylfuran (2-MTHF) and 2-methylfuran (2-MF), are investigated. Compared to conventional fuels, they have potential advantages in the well-to-tank balance. In addition, both neat ethanol and conventional gasoline are used as fuels.

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.

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.

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.

With increasing interest in new biofuel candidates, 1-octanol and di-n-butylether (DNBE) were presented in recent studies. Although these molecular species are isomers, their properties are substantially different. In contrast to DNBE, 1-octanol is almost a gasoline-type fuel in terms of its auto-ignition quality. Thus, there are problems associated with engine start-up for neat 1-octanol. In order to find a suitable glow-plug position, mixture formation is studied in the cylinder under almost idle operating conditions in the present work. This is conducted by planar laser-induced fluorescence in a high-speed direct-injection optical diesel engine. The investigated C8-oxygenates are also significantly different in terms of their evaporation characteristics. Thus, in-cylinder mixture formation of these two species is compared in this work, allowing conclusions on combustion behavior and exhaust emissions.

The modern engine development process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. It is expected that predictive simulation tools that encompass the entire powertrain can potentially improve the efficiency of the calibration process. The testing of an ECU using a HiL system requires a real-time model. Additionally, if the initial parameters of the ECU are to be defined and tested, the model has to be more accurate than is typical for ECU functional testing. It is possible to enhance the generalization capability of the simulation, with neuronal network sub-models embedded into the architecture of a physical model, while still maintaining real-time execution. This paper emphasizes the experimental investigation and physical modeling of the port fuel injected SI engine.

Partly competing objectives, as low fuel consumption, low friction, long oil maintenance rate, and at the same time lowest exhaust emissions have to be fulfilled. Diminishing resources, continuously reduced development periods, and shortened product cycles yield detailed knowledge about oil consumption mechanisms in combustion engines to be essential. There are different ways for the lubricating oil to enter the combustion chamber: for example as blow-by gas, leakage past valve stem seals, piston rings (reverse blow-by) and evaporation from the cylinder liner wall and the combustion chamber. For a further reduction of oil consumption the investigation of these mechanisms has become more and more important. In this paper the influence of the mixture formation and the resulting fuel content in the cylinder liner wall film on the lubricant oil emission was examined.

The demand for lower CO2 emissions requires not just the optimization of every single component but the complete system. For a transmission system, it is important to optimize the transmission hardware as we well as the interaction of powertrain components. For automatic transmission with wide ratio spreads, the main losses are caused by the actuation system, which can be reduced with use of ondemand actuation systems. In this paper, a new on-demand electromechanical actuation system with validation results on a clutch test bench is presented. The electro-mechanical actuator shows an increase in the efficiency of 4.1 % compared to the conventional hydraulic actuation in a simulated NEDC (New European Driving Cycle) cycle. This increase is based on the powerless end positions of the actuator (engaged and disengaged clutch). The thermal tension and wear are compensated with a disk spring. This allows a stable control over service life.

A main focus of development in modern SI engine technology is variable valve timing, which implies a high potential of improvement regarding fuel consumption and emissions. Variable opening, period and lift of inlet and outlet valves enable numerous possibilities to alter gas exchange and combustion. However, this additional variability generates special demands on the calibration process of specific engine control devices, particularly under cold start and warm-up conditions. This paper presents procedures, based on Hardware-in-the-Loop (HiL) simulation, to support the classical calibration task efficiently. An existing approach is extended, such that a virtual combustion engine is available including additional valve timing variability. Engine models based purely on physical first principles are often not capable of real time execution. However, the definition of initial parameters for the ECU requires a model with both real time capability and sufficient accuracy.