Search Results

A newly developed turbocharging system, named MIXPC, is proposed and the performance of the proposed system applied to diesel engines is evaluated. The aim of this proposed system is to reduce the scavenging interference between cylinders, and to lower the pumping loss in cylinders and the brake specific fuel consumption. In addition, exhaust manifolds of simplified design can be constructed with small dimensions, low weight and a single turbine entry. A simulation code based on a second-order FVM+TVD (finite volume method + total variation diminishing) is developed and used to simulate engines with MIXPC. By simulating a 16V280ZJG diesel engine using the MPC turbocharging system and MIXPC, it is found that not only the average scavenging coefficient of MIXPC is larger than that of MPC, but also cylinders of MIXPC have more homogeneous scavenging coefficients than that of MPC, and the pumping loss and BSFC of MIXPC are lower than those of MPC.

A nonintrusive diagnostic technique has been developed by which dynamic axial piston-position and tilt-angle measurements have been made in a single-cylinder research engine. A laser beam, introduced into the combustion chamber through an optical port in the cylinder head, was reflected by a polished surface on the piston crown. Motion of the reflected beam, carrying with it information on piston position and piston tilt, was monitored by a set of receiving optics. Piston motion was studied as a function of both engine speed and cylinder pressure (i.e., piston loading.) Measured axial piston-position was found to deviate from the theoretical position calculated from the measured crank-shaft position owing to the effects of tilt and piston loading. Furthermore, evidence of piston veer (tilt of the piston in a plane parallel to the axis of the wrist pin) was observed, which had an effect on the accuracy of the axial piston-position measurement.

1 An all fiber-optic sensor has been developed to measure H2O mole fraction and gas temperature in an HCCI engine. This absorption-spectroscopy-based sensor utilizes a broad wavelength (1320 to 1380 nm) source (supercontinua generated by a microchip laser) and a series of fiber Bragg gratings (19 gratings centered on unique water absorption peaks) to track the formation and temperature of combustion water vapor. The spectral coverage of the system promises improved measurement accuracy over two-line diode-laser based systems. Meanwhile, the simplicity of the fiber Bragg grating chromatic dispersion approach significantly reduces the data reduction time and cost relative to previous supercontinuum-based sensors. The data provided by the system is expected to enhance studies of the chemical kinetics which govern HCCI ignition as well as HCCI modeling efforts.

A single cylinder Yamaha research engine was operated with gasoline HCCI combustion using negative valve overlap (NVO). The injection strategy for this study involved using fuel injected directly into the cylinder during the NVO period (pre-DI) along with a secondary injection either in the intake port (PI) or directly into the cylinder (DI). The effects of timing of the pre-DI injection along with the percent of fuel injected during the pre-DI injection were studied in two sets of experiments using secondary PI and DI injections in separate experiments. Results have shown that by varying the pre-DI timing and pre-DI percent the main HCCI combustion timing can be influenced as a result of varied heat release during the negative valve overlap period along with hypothesized varied degrees of reformation of the pre-DI injected fuel. In addition to varying the main combustion timing the ISFC, emissions and combustion stability are all influenced by changes in pre-DI timing and percent.

A multi-objective genetic algorithm methodology was applied to a heavy-duty diesel engine at three different operating conditions of interest. Separate optimizations were performed over various fuel injection nozzle parameters, piston bowl geometries and swirl ratios (SR). Different beginning of injection (BOI) timings were considered in all optimizations. The objective of the optimizations was to find the best possible fuel economy, NOx, and soot emissions tradeoffs. The input parameter ranges were determined using design of experiment methodology. A non-dominated sorting genetic algorithm II (NSGA II) was used for the optimization. For the optimization of piston bowl geometry, an automated grid generator was used for efficient mesh generation with variable geometry parameters. The KIVA3V release 2 code with improved ERC sub-models was used. The characteristic time combustion (CTC) model was employed to improve computational efficiency.

This paper is a continuation of an earlier paper, which examined the steady-state internal heat transfer in the exhaust system of a diesel powered, light-duty vehicle. The present paper deals with the heat transfer of the exhaust system during two types of transient testing, as well as, the estimation of the exhaust systems external heat transfer. Transient heat transfer was evaluated using: a simple fuel-step transient under constant speed and the New European Driving Cycle (NEDC). The thermal response of the external walls varied considerably for the various components of the exhaust system. The largest percent difference between the measured temperatures and the corresponding quasi-steady estimates were about 10%, which is attributed to thermal storage. Allowing for thermal storage resulted in an excellent agreement between measurements and analysis.

Multi-dimensional computational efforts using comprehensive and skeletal kinetics have been made to investigate the cool flame region in HCCI combustion. The work was done in parallel to an experimental study that showed the impact of the negative temperature coefficient and the cool flame on the start of combustion using different fuels, which is now the focus of the simulation work. Experiments in a single cylinder CFR research engine with n-butane and a primary reference fuel with an octane number of 70 (PRF 70) were modeled. A comparison of the pressure and heat release traces of the experimental and computational results shows the difficulties in predicting the heat release in the cool flame region. The behavior of the driving radicals for two-stage ignition is studied and is compared to the behavior for a single-ignition from the literature. Model results show that PRF 70 exhibits more pronounced cool flame heat release than n-butane.

The effect of injection rate shape on spray evolution and emission characteristics is investigated and a methodology for active control of fuel injection is proposed. Extensive validation of advanced vaporization and primary jet breakup models was performed with experimental data before studying the effects of systematic changes of injection rate shape. Excellent agreement with the experiments was obtained for liquid and vapor penetration lengths, over a broad range of gas densities and temperatures. Also the predicted flame lift-off lengths of reacting diesel fuel sprays were in good agreement with the experiments. After the validation of the models, well-defined rate shapes were used to study the effect of injection rate shape on liquid and vapor penetration, flame lift-off lengths and emission characteristics.

A cylinder model was developed using artificial neural networks (ANN). The cylinder model utilized the trained ANN models to predict engine parameters including cylinder pressures, cylinder temperatures, cylinder wall heat transfer, NOx and soot emissions. The ANN models were trained to approximate CFD simulation results of an engine. The ANN cylinder model was then applied to predict engine performance and emissions over the standard heavy-duty FTP transient cycle. The engine responses varying over the engine speed and torque range were simulated in the course of the transient test cycle. It was demonstrated that the ANN cylinder model is capable of simulating the characteristics of the engine operating under transient conditions reasonably well.

The KIVA 3V code has been applied to predict combustion chamber heat flux in an air-cooled utility engine. The KIVA heat flux predictions were compared with experimentally measured data in the same engine over a wide range of operating conditions. The measured data were found to be approximately two times larger than the predicted results, which is attributed to the omission of chemical heat release in the near-wall region for the heat transfer model applied. Modifying the model with a simple scaling factor provided a good comparison with the measured data for the full range of engine load, heat flux sensor location, air-fuel ratio and spark timings tested. The detailed spatially resolved results of the KIVA predictions were then used to develop a simplified model of the combustion chamber temporally integrated heat flux using an artificial neural network (ANN).

The recently developed KIVA-GA computer code was used in the current study to optimize the combustion chamber geometry of a heavy -duty diesel truck engine and a high-speed direct-injection (HSDI) small-bore diesel engine. KIVA-GA performs engine simulations within the framework of a genetic algorithm (GA) global optimization code. Design fitness was determined using a modified version of the KIVA-3V code, which calculates the spray, combustion, and emissions formation processes. The measure of design fitness includes NOx, unburned HC, and soot emissions, as well as fuel consumption. The simultaneous minimization of these factors was the ultimate goal. The KIVA-GA methodology was used to optimize the engine performance using nine input variables simultaneously. Three chamber geometry related variables were used along with six other variables, which were thought to have significant interaction with the chamber geometry.

A single cylinder CFR research engine has been run in HCCI combustion mode at the rich and the lean limits of the homogeneous charge operating range. To achieve a variation of the degree of charge stratification, two GDI injectors were installed: one was used for generating a homogeneous mixture in the intake system, and the other was mounted directly into the side of the combustion chamber. At the lean limit of the operating range, stratification showed a tremendous improvement in IMEP and emissions. At the rich limit, however, the stratification was limited by the high-pressure rise rate and high CO and NOx emissions. In this experiment the location of the DI injector was in such a position that the operating range that could be investigated was limited due to liquid fuel impingement onto the piston and liner.

A single cylinder CFR research engine has been run in HCCI combustion mode for a range of temperatures and fuel compositions. The data indicate that the best HCCI operation, as measured by a combination of successful combustion with low ISFC, occurs at or near the rich limit of operation. Analysis of the pressure and heat release histories indicated the presence, or absence, and impact of the fuel's NTC ignition behavior on establishing successful HCCI operation. The auto-ignition trends observed were in complete agreement with previous results found in the literature. Furthermore, analysis of the importance of the fuel's octane sensitivity, through assessment of an octane index, successfully explained the changes in the fuels auto-ignition tendency with changes in engine operating conditions.

Artificial neural networks (ANN) have been recognized as universal approximators for nonlinear continuous functions and actively applied in engine research in recent years [1, 2, 3, 4, 5, 6, 7 and 8]. This paper describes the methodology and results of using the ANN to model a turbocharged DI diesel engine. The engine was simulated using the CFD code (KIVA-ERC) over a wide range of operating conditions, and numerical simulation results were used to train the ANN. An efficient data collection methodology using the Design of Experiments (DOE) techniques was developed to select the most characteristic engine operating conditions and hence the most informative data to train the ANN. This approach minimizes the time and cost of collecting training data from either computational or experimental resources. The trained ANN was then used to predict engine parameters such as cylinder pressure, cylinder temperature, NOx and soot emissions, and cylinder heat transfer.

An experimental and numerical characterization has been conducted for high-pressure hydraulically actuated fuel injection systems. One single and one double-guided multi-hole Valve-Covered-Orifice (VCO) type injector was used with a Common Rail (CR) injection system, and two mini-sac injectors for Hydraulic electronic Unit Injection system (HEUI) were used with different orifice diameters. The purpose of the study was to explore the effects of the injection system and the operating conditions on the engine emissions for a direct injection small bore diesel engine. The diesel spray was injected into a pressurized chamber with optical access at ambient temperature. The gas density inside the chamber was representative of the density in a High Speed Direct Injection (HSDI) diesel engine at the time of injection. The experimental spray parameters included: injection pressure, injection duration, nozzle type, and nozzle diameter.

An improved discrete particle ignition kernel (DPIK) model and the G-equation combustion model have been developed and implemented in KIVA-3V. In the ignition model, the spark ignition kernel growth is tracked by Lagrangian markers and the spark discharge energy and flow turbulence effects on the ignition kernel growth are considered. The predicted ignition kernel size was compared with the available measurements and good agreement was obtained. Once the ignition kernel grows to a size where the turbulent flame is fully developed, the level set method (G-equation) is used to track the mean turbulent flame propagation. It is shown that, by ignoring the detailed turbulent flame brush structure, fine numerical resolution is not needed, thus making the models suitable for use in multidimensional modeling of SI engine combustion.

A comprehensive system level modeling approach is used to understand the effects of the various physical actuators during diesel HCCI transients. Control concepts during transient operations are simulated using a set of actuators suitable for combustion control in diesel HCCI engines (intake valve actuation, injection timing, cooled EGR, intake boost pressure and droplet size). The impact of these actuating techniques on the overall engine performance is quantified by investigating the amount of actuation required, timing of actuation and the use of a combination of actuators. Combined actuation improved actuation space that can be used to phase combustion timing better and in extending the operating range. The results from transient simulations indicate that diesel HCCI operation would benefit from the combined actuation of intake valve closure, injection timing, boost and cooled EGR.

The effect of piston ring pack crevice flow and lubricant oil vaporization on heavy-duty diesel engine deposits is investigated numerically using a multidimensional CFD code, KIVA3V, coupled with Chemkin II, and computational grids that resolve part of the crevice region appropriately. Improvements have been made to the code to be able to deal with the complex geometry of the ring pack, and sub-models for the crevice flow dynamics, lubricating oil vaporization and combustion, soot formation and deposition were also added to the code. Eight parametric cases were simulated under reacting conditions using detailed chemical kinetics to determine the effects of variations of lube-oil film thickness, distribution of the oil film thickness, number of injection pulses, and the main injection timing on engine soot deposition. The results show that crevice-borne hydrocarbon species play an important role in deposit formation on crevice surfaces.

Schlieren visualization was performed to investigate hydrogen injection into a quiescent chamber. The injection pressures investigated were 52 and 104 bar, and the chamber density ranged from 1.15 to 12.8 kg/m3, giving rise to underexpanded jets for all conditions. The expansion waves outside the nozzle were clearly visible with hydrogen, and the effect was confirmed with studies of nitrogen injected into a nitrogen environment. The distance between the expansion wave fronts was found to scale directly with the ratio of the exit pressure to the chamber pressure. The jet tip penetration rate was measured and was found to increase with injection pressure, and decrease with chamber density as expected. A mass- and momentum-preserving scheme was developed to relate the underexpanded jet to a subsonic jet of larger diameter.

An overall diesel engine and aftertreatment system model has been created that integrates diesel engine, exhaust system, engine emissions, and diesel particulate filter (DPF) models using MATLAB Simulink. The 1-D engine and exhaust system models were developed using WAVE. The engine emissions model combines a phenomenological soot model with artificial neural networks to predict engine out soot emissions. Experimental data from a light-duty diesel engine was used to calibrate both the engine and engine emissions models. The DPF model predicts the behavior of a clean and particulate-loaded catalyzed wall-flow filter. Experimental data was used to validate this sub-model individually. Several model integration issues were identified and addressed. These included time-step selection, continuous vs. limited triggering of sub-models, and code structuring for simulation speed. Required time-steps for different sub models varied by orders of magnitude.