Search Results

In the context of the energy transition, CO2-neutral solutions are of enormous importance for all sectors, but especially for the mobility sector. Hydrogen as an energy carrier has therefore been the focus of research and development for some time. However, the development of hydrogen combustion engines is in many respects still in the conception phase. Automotive system providers and engineering companies in the field of software development and simulation are showing great interest in the topic. In a joint project with the industrial partners Robert Bosch GmbH and AVL Germany, combustion in a H2-DI-engine for use in light-duty vehicles was methodically investigated using the CFD tool AVL FIRE®. The collaboration between Robert Bosch GmbH and the Institute for Mobile Systems (IMS) at Otto von Guericke University Magdeburg has produced a model study in which model approaches for the combustion of hydrogen can be analyzed.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.

A study of n-dodecane atomization, following the prescribed unseating of the needle tip, is presented for a high-pressure, non-cavitating Bosch Diesel injector (“Spray A”, in the Engine Combustion Network denomination). In the two simulations discussed here, the internal and external multiphase flows are seamlessly calculated across the injection orifice using an interface-capturing approach (for the liquid fuel surface) together with an embedded boundary formulation (for the injector's walls). This setting makes it possible to directly relate the liquid jet spray characteristics (under the assumption of sub-critical flow and with a grid resolution of 3 µm, or 1/30 of the orifice diameter) to the moving internal geometry of the injector. Another novelty is the capability of modeling the compressibility of the liquid and the gas phase while maintaining a sharp interface between the two.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

The fuel spray process is of utmost importance to internal combustion engine design as it dominates engine performance and emissions characteristics. While designers rely on computational fluid dynamics (CFD) modeling for understanding of the air-fuel mixing process, there are recognized shortcomings in current CFD spray predictions, particularly under super-critical or flash-boiling conditions. In contrast, time-resolved optical spray experiments have now produced datasets for the three-dimensional liquid distribution for a wide range of operating conditions and fuels. By utilizing such a large amount of detailed experimental data, the machine learning (ML) techniques have opened new pathways for the prediction of fuel sprays under various engine-like conditions.

Tapping of one or more torques (ranges 10 Nm and 60 Nm) on the steering column for the purpose of servo control must satisfy high accuracy requirements on the one hand and high safety requirements on the other hand. A suggestion for developing a low-cost solution to this problem is described below: Strain gages optimally satisfy both these requirements: However, for cost reasons, these are not applied directly to the steering column but to a prefabricated, flat steel rod which is laser welded to the torque rod of the steering column. The measuring direction of the strain gages is under 45° to the steering column axis. The strain gages are either vacuum metallized onto the support rod as a thin film or laminated in a particularly low-cost way by means of a foil-type intermediate carrier.

The emission of particulate matter from future GDI engines has to be optimized, to comply with more stringent emission standards such as EU6. Therefore, the mechanisms responsible for the formation of particles have to be analyzed in detail. The understanding of the in-cylinder processes, necessary for this purpose, can only be achieved by a complementary use of optically accessible single-cylinder engines as well as the numerical simulation. This however leads to great demands on the 3D flow simulation. In this paper the complete CFD approach, incorporating a detailed description of the entire underlying model chain is shown. Particularly the wall surface temperature and the temperature drop due to the interaction with liquid fuel spray were identified as important parameters influencing the spray-wall interaction and thus also the particulate emissions. Nevertheless, in conventional CFD models, the spray cooling cannot be captured because of an assumed constant wall temperature.

Pre-chamber ignition has demonstrated capability to increase internal combustion engine in-cylinder burn rates and enable the use of low engine-out pollutant emission combustion strategies. In the present study, newly designed passive pre-chambers with different nozzle-hole patterns - that featured combinations of radial and axial nozzles - were experimentally investigated in an optically accessible, single-cylinder research engine. The pre-chambers analyzed had a narrow throat geometry to increase the velocity of the ejected jets. In addition to a conventional inductive spark igniter, a nanosecond spark ignition system that promotes faster early burn rates was also investigated. Time-resolved visualization of ignition and combustion processes was accomplished through high-speed hydroxyl radical (OH*) chemiluminescence imaging. Pressure was measured during the engine cycle in both the main chamber and pre-chamber to monitor respective combustion progress.

A process to recover carbon fibers from obsolete polymer matrix composite (PMC) materials has been developed. Carbon fibers have been recovered from samples containing urethane-based or epoxy-based substrates. An experimental parametric study conducted on both the bench-scale and the pilot-scale has been done to determine the least-cost process conditions. Based on this study, we have evaluated process economics that suggested a payback of about one year. This process is also applicable to polymer matrix composite materials made with thermoplastic substrates. This paper presents the results of the experimental testing campaign and the results of the process economic analysis.

Filtration of diesel and gasoline fuel in automotive applications is affected by many external and internal parameters, e.g. vibration, temperature, pressure, flow pulsation, and engine start-stop. Current test procedures for automotive fuel filters, proposed by most of the researchers and organizations including Society for Automotive Engineers (SAE) and International Organization for Standardization (ISO), do not apply the previously mentioned real-world-conditions. These operating conditions, which are typical for an automotive fueling system, have a significant effect on fuel filtration and need to be considered for the accurate assessment of the filter. This requires the development of improved testing procedures that will simulate the operating conditions in a fuel system as encountered in the real world.

This work presents a simple fan model that is based on the actuator disk approximation, and the blade element and vortex theory of a propeller. A set of equations are derived that require as input the rotational speed of the fan, geometric fan data, and the lift and drag coefficients of the blades. These equations are solved iteratively to obtain the body forces generated by the fan in the axial and circumferential directions. These forces are used as momentum sources in a CFD code to simulate the effect of the fan in an underhood thermal management simulation. To validate this fan model, a fan experiment was simulated. The model was incorporated into the CFD code STAR-CD and predictions were generated for axial and circumferential air velocities at different radial positions and at different planes downstream of the fan. The agreement between experimental measurements and predictions is good.

In recognition of safety considerations, modern fuel tanks are frequently extremely irregular in shape. This places limits on the application of conventional potentiometric sensors. Required are more universal sensors without mechanically-moving parts. These sensors should also be characterized by especially good resolution and precision in the residual-quantity range, that is, the zero point precision should be of a high order. One type of metal rod can be bent into any of a variety of shapes to provide an effective means of monitoring the fuel level. In this metal rod, the propagation characteristics of a certain type of sound wave, known as bending waves, display major variations according to the level of the surrounding medium: The waves spread more rapidly through the exposed section of the rod than through the area which remains submerged. Thus the rod's characteristic oscillation frequency varies as a function of immersion depth.

The long-term goal of this work is to develop a conceptual model for multiple injections of diesel jets. The current work contributes to that effort by performing a detailed modeling investigation into mechanisms that are predicted to control 1st and 2nd stage ignition in single-pulse diesel (n-dodecane) jets under different conditions. One condition produces a jet with negative ignition dwell that is dominated by mixing-controlled heat release, and the other, a jet with positive ignition dwell and dominated by premixed heat release. During 1st stage ignition, fuel is predicted to burn similarly under both conditions; far upstream, gases at the radial-edge of the jet, where gas temperatures are hotter, partially react and reactions continue as gases flow downstream. Once beyond the point of complete fuel evaporation, near-axis gases are no longer cooled by the evaporation process and 1st stage ignition transitions to 2nd stage ignition.

Accurate modeling of the internal flow and spray characteristics in fuel injectors is a critical aspect of direct injection engine design. However, such high-fidelity computational fluid dynamics (CFD) models are often computationally expensive due to the requirement of resolving fine temporal and spatial scales. This paper addresses the computational bottleneck issue by proposing a machine learning-based emulator framework, which learns efficient surrogate models for spatiotemporal flow distributions relevant for static coupling injection maps, namely total void fraction, velocity, and mass, within a design space of interest. Different design points involving variations of needle lift, fuel viscosity, and level of non-condensable gas in the fuel were explored in this study. An interpretable Bayesian learning strategy was employed to understand the effect of the design parameters on the void fraction fields at the exit of the injector orifice.

In an effort of providing better understanding of regeneration mechanisms of diesel particulate matter (PM), this experimental investigation focused on evaluating the amount of heat release generated during the thermal reaction of diesel PM and the concentrations of soluble organic compounds (SOCs) dissolved in PM emissions. Differences in oxidation behaviors were observed for two different diesel PM samples: a SOC-containing PM sample and a dry soot sample with no SOCs. Both samples were collected from a cordierite particulate filter membrane in a thermal reactor connected to the exhaust pipe of a light-duty diesel engine. A differential scanning calorimeter (DSC) and a thermogravimetric analyzer (TGA) were used to measure the amount of heat release during oxidation, along with subsequent oxidation rates and the concentrations of SOCs dissolved in particulate samples, respectively.

For several years there has been a great deal of effort made in researching ways to run a compression ignition engine with simultaneously high efficiency and low emissions. Recently much of this focus has been dedicated to using gasoline-like fuels that are more volatile and less reactive than conventional diesel fuel to allow the combustion to be more premixed. One of the key challenges to using fuels with such properties in a compression ignition engine is stable engine operation at low loads. This paper provides an analysis of how stable gasoline compression ignition (GCI) engine operation was achieved down to idle speed and load on a multi-cylinder compression ignition engine using only 87 anti-knock index (AKI) gasoline. The variables explored to extend stable engine operation to idle included: uncooled exhaust gas recirculation (EGR), injection timing, injection pressure, and injector nozzle geometry.

Optical engines are often skip-fired to maintain optical components at acceptable temperatures and to reduce window fouling. Although many different skip-fired sequences are possible, if exhaust emissions data are required, the skip-firing sequence ought to consist of a single fired cycle followed by a series of motored cycles (referred to here as singleton skip-firing). This paper compares a singleton skip-firing sequence with continuous firing at the same inlet conditions, and shows that combustion performance trends with equivalence ratio are similar. However, as expected, reactant temperatures are lower with skip-firing, resulting in retarded combustion phasing, and lower pressures and combustion efficiency. LIF practitioners often employ a homogeneous charge of known composition to create calibration images for converting raw signal to equivalence ratio.

Knock in spark-ignition (SI) engines has been a subject of many research efforts and its relationship with high efficiency operating conditions keeps it a contemporary issue as engine technologies push classical limits. Despite this long history of research, literature is lacking coherent and generalized descriptions of how knock is affected by changes in the full cylinder temperature field, residence time (engine speed), and air/fuel ratio. In this work, two dimensionless numbers are applied to fully 3D SI conditions. First, the characteristic time of autoignition (ignition delay) is compared against the characteristic time of end-gas deflagration, which was used to predict knocking propensity. Second, the temperature gradient of the end-gas is compared against a critical detonation-based temperature gradient, which predicts the knock intensity.

This paper presents advanced planar ZrO2 oxygen sensors being developed at Robert Bosch using a modified tetragonal partially stabilized zirconia (TZP) with high ionic conductivity, high phase stability and high thermo-mechanical strength. Green tape technology combined with highly automated thickfilm techniques allows robust and cost effective manufacturing of those novel sensing elements. Standardization of assembling parts reduces the complexity of the assembly line even in the case of different sensing principles. The sensor family meets the new requirements of modern ULEV strategies like fast light off below 10 s and linear control capability as well as high quality assurance standards. High volume production will start in 1997 for European customers.