Search Results

One in-cylinder strategy for reducing soot emissions from diesel engines while maintaining fuel efficiency is the use of close-coupled post injections, which are small fuel injections that follow the main fuel injection after a short delay. While the in-cylinder mechanisms of diesel combustion with single injections have been studied extensively and are relatively well understood, the in-cylinder mechanisms affecting the performance and efficacy of post injections have not been clearly established. Here, experiments from a single-cylinder heavy-duty optical research engine incorporating close- coupled post injections are modeled with three dimensional (3D) computational fluid dynamics (CFD) simulations. The overall goal is to complement experimental findings with CFD results to gain more insight into the relationship between post-injections and soot. This paper documents the first stage of CFD results for simulating and analyzing the experimental conditions.

A computational study was performed to evaluate the effects of bowl geometry, fuel spray targeting and swirl ratio under highly diluted, low-temperature combustion conditions in a heavy-duty diesel engine. This study is used to examine aspects of low-temperature combustion that are affected by mixing processes and offers insight into the effect these processes have on emissions formation and oxidation. The foundation for this exploratory study stems from a large data set which was generated using a genetic algorithm optimization methodology. The main results suggest that an optimal combination of spray targeting, swirl ratio and bowl geometry exist to simultaneously minimize emissions formation and improve soot and CO oxidation rates. Spray targeting was found to have a significant impact on the emissions and fuel consumption performance, and was furthermore found to be the most influential design parameter explored in this study.

The objective of this investigation is to optimize a light-duty diesel engine in order to minimize soot, NOx, carbon monoxide (CO), unburned hydrocarbon (UHC) emissions and peak pressure rise rate (PPRR) while improving fuel economy in a low oxygen environment. Variables considered are the injection timings, fractional amount of fuel per injection, half included spray angle, swirl, and stepped-bowl piston geometry. The KIVA-CHEMKIN code, a multi-dimensional computational fluid dynamics (CFD) program with detailed chemistry is used and is coupled to a multi-objective genetic algorithm (MOGA) along with an automated grid generator. The stepped-piston bowl allows more options for spray targeting and improved charge preparation. Results show that optimal combinations of the above variables exist to simultaneously reduce emissions and fuel consumption. Details of the spray targeting were found to have a major impact on the combustion process.

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.

With recent increases in global fuel prices there has become a growing interest in expanding the use of diesel engines in the transportation industry. However, new engine development is costly and time intensive, requiring many hours of expensive engine tests. The ability to accurately predict an engine's performance based on existing models would reduce the expense involved in creating a new engine of different size. In the present study experimental results from two single-cylinder direct injection diesel engines were used to examine previously developed engine scaling models. The first scaling model was based on an equal spray penetration correlation. The second model considered both equal spray penetration and flame lift-off length. The engines used were a heavy-duty Caterpillar engine with a 2.44L displacement and a light-duty GM engine with a 0.48L displacement.

Optimizations were performed on a single-cylinder heavy-duty Caterpillar SCOTE 3401E engine for NOx, PM and BSFC reductions. The engine was equipped with a Caterpillar 300B HEUI fuel injection system capable of up to four injections with timings from 90 BTDC to 90 ATDC. The engine was operated at a medium load (57%), high speed (1737 rev/min) operation point. A micro-genetic algorithm was utilized to optimize a hybrid, double-injection strategy, which incorporated an early, premixed pilot injection with a late main injection. The fuel injection parameters, intake boost pressure, and EGR were considered in the optimization. The optimization produced a parameter set that met the 2007 and 2010 PM emissions mandate of 0.0134 g/kW-hr, and was within the 1.5x not to exceed NOx + HC mandate of 2.694 g/kW-hr. Following the optimization exercise, further parametric interaction studies were performed to reveal the underlying interactions and phenomena.

Current automotive diesel engine research is motivated by the need to meet more-and-more strict emission regulations. The major target for future HSDI combustion research and development is to find the most effective ways of reducing the soot particulate and NOx emissions to the levels required by future emission regulations. Recently, a variety of statistical optimization tools have been proposed to optimize engine-operating conditions for emissions reduction. In this study, a micro-genetic algorithm technique, which locates a global optimum via the law of “the survival of the fittest”, was applied to a high-speed, direct-injection, single-cylinder (HSDI) diesel engine. The engine operating condition considered single-injection operation using a common-rail fuel injection system was at 1757 rev/min and 45% load.

In this paper, optimized single and double injection schemes were found using multi-dimensional engine simulation software (KIVA-3V) and a micro-genetic algorithm for a heavy duty diesel engine. The engine operating condition considered was at 1737 rev/min and 57 % load. The engine simulation code was validated using an engine equipped with a hydraulic-electronically controlled unit injector (HEUI) system. Five important parameters were used for the optimization - boost pressure, EGR rate, start-of-injection timing, fraction of fuel in the first pulse and dwell angle between first and second pulses. The optimum results for the single injection scheme showed significant improvements for the soot and NOx emissions. The start of injection timing was found to be very early, which suggests HCCI-like combustion. Optimized soot and NOx emissions were reduced to 0.005 g/kW-hr and 1.33 g/kW-hr, respectively, for the single injection scheme.

This paper is part of a larger body of experimental and computational work devoted to studying the role of close-coupled post injections on soot reduction in a heavy-duty optical engine. It is a continuation of an earlier computational paper. The goals of the current work are to develop new CFD analysis tools and methods and apply them to gain a more in depth understanding of the different in-cylinder environments into which fuel from main- and post-injections are injected and to study how the in-cylinder flow, thermal and chemical fields are transformed between start of injection timings. The engine represented in this computational study is a single-cylinder, direct-injection, heavy-duty, low-swirl engine with optical components. It is based on the Cummins N14, has a cylindrical shaped piston bowl and an eight-hole injector that are both centered on the cylinder axis. The fuel used was n-heptane and the engine operating condition was light load at 1200 RPM.

In the present paper optimization tools are used to recommend low-emission engine combustion chamber designs, spray targeting and swirl ratio levels for a heavy-duty diesel engine operated at high-load. The study identifies aspects of the combustion and pollution formation that are affected by mixing processes, and offers guidance for better matching of the piston geometry with the spray plume geometry for enhanced mixing. By coupling a GA (genetic algorithm) with the KIVA-CFD code, and also by utilizing an automated grid generation technique, multi-objective optimizations with goals of low emissions and fuel economy were achieved. Three different multi-objective genetic algorithms including a Micro-Genetic Algorithm (μGA), a Nondominated Sorting Genetic Algorithm II (NSGA II) and an Adaptive Range Multi-Objective Genetic Algorithm (ARMOGA) were compared for conducting the optimization under the same conditions.

RNG k-ε closure turbulence dissipation equations are evaluated employing the CFD code KIVA-3V Release 2. The numerical evaluations start by considering simple jet flows, including incompressible air jets and compressible helium jets. The results show that the RNG closure turbulence model predicts lower jet tip penetration than the "standard" k-ε model, as well as being lower than experimental data. The reason is found to be that the turbulence kinetic energy is dissipated too slowly in the downstream region near the jet nozzle exit. In this case, the over-predicted R term in RNG model becomes a sink of dissipation in the ε-equation. As a second step, the RNG turbulence closure dissipation models are further tested in complex engine flows to compare against the measured evolution of turbulence kinetic energy, and an estimate of its dissipation rate, during both the compression and expansion processes.

The application of close-coupled post injections in diesel engines has been proven to be an effective in-cylinder strategy for soot reduction, without much fuel efficiency penalty. But due to the complexity of in-cylinder combustion, the soot reduction mechanism of post-injections is difficult to explain. Accordingly, a simulation study using a three dimensional computational fluid dynamics (CFD) model, coupled with the SpeedChem chemistry solver and a semi-detailed soot model, was carried out to investigate post-injection in a constant volume combustion chamber, which is more simple and controllable with respect to the boundary conditions than an engine. A 2-D axisymmetric mesh of radius 2 cm and height 5 cm was used to model the spray. Post-injection durations and initial oxygen concentrations were swept to study the efficacy of post-injection under different combustion conditions.

The focus of the present study was to characterize Reactivity Controlled Compression Ignition (RCCI) using a single-fuel approach of gasoline and gasoline mixed with a commercially available cetane improver on a multi-cylinder engine. RCCI was achieved by port-injecting a certification grade 96 research octane gasoline and direct-injecting the same gasoline mixed with various levels of a cetane improver, 2-ethylhexyl nitrate (EHN). The EHN volume percentages investigated in the direct-injected fuel were 10, 5, and 2.5%. The combustion phasing controllability and emissions of the different fueling combinations were characterized at 2300 rpm and 4.2 bar brake mean effective pressure over a variety of parametric investigations including direct injection timing, premixed gasoline percentage, and intake temperature. Comparisons were made to gasoline/diesel RCCI operation on the same engine platform at nominally the same operating condition.

While Low Temperature Combustion (LTC) strategies such as Reactivity Controlled Compression Ignition (RCCI) exhibit high thermal efficiency and produce low NOx and soot emissions, low load operation is still a significant challenge due to high unburnt hydrocarbon (UHC) and carbon monoxide (CO) emissions, which occur as a result of poor combustion efficiencies at these operating points. Furthermore, the exhaust gas temperatures are insufficient to light-off the Diesel Oxidation Catalyst (DOC), thereby resulting in poor UHC and CO conversion efficiencies by the aftertreatment system. To achieve exhaust gas temperature values sufficient for DOC light-off, combustion can be appropriately phased by changing the ratio of gasoline to diesel in the cylinder, or by burning additional fuel injected during the expansion stroke through post-injection.

A modification of the computational fluid dynamics code KIVA-II is presented that allows computations to be made in complex engine geometries. An example application is given in which three versions of KIVA-II are run simultaneously. Each version considers a separate block of the computational domain, and the blocks exchange boundary condition information with each other at their common interfaces. The use of separate blocks permits the connectedness of the overall computational domain to change with time. The scavenging flow in the cylinder, transfer pipes (ports), and exhaust pipe of a ported two-stroke engine with a moving piston was modeled in this way. Results are presented for three engine designs that differ only in the angle of their boost ports. The calculated flow fields and the resulting fuel distributions are shown to be markedly different with the different geometries.

The present work proposes a methodology for diesel engine development using scaling laws and computational optimization with multi-dimensional CFD tools. A previously optimized 450cc HSDI diesel engine was down-scaled to 400cc size using recently developed scaling laws. The scaling laws were validated by comparing the performance of these two engines, including pressure, HRR, peak and averaged temperature, and pollutant emissions. A novel optimization methodology, which is able to simultaneously optimize multiple operating conditions, was proposed. The method is based on multi-objective genetic algorithms, and was coupled with the KIVA3V Release 2 code to further optimize the down-scaled diesel engine. An adaptive multi-grid chemistry model was used in the KIVA3V code to reduce the computational cost of the optimization. The computations were conducted using high-throughput computing with the CONDOR system.

A new search technique, called Non-Gradient Step-Controlled algorithm (NGSC), is presented. The NGSC was applied independently from pre-selected starting points and as a supplement to a Genetic Algorithm (GA) to optimize a HSDI diesel engine using split injection strategies. It is shown that the NGSC handles well the challenges of a complex response surface and factor high-dimensionality, which demonstrates its capability as an efficient and accurate tool to seek “local” convergence on complex surfaces. By directly tracking the change of a merit function, the NGSC places no requirement on response surface continuity / differentiability, and hence is more robust than gradient-dependent search techniques. The directional search mechanism takes factor interactions into consideration, and search step size control is adopted to facilitate search efficiency.

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.

The present experimental study explores the effects of compression ratio and piston design in a heavy-duty diesel engine operated with Reactivity Controlled Compression Ignition (RCCI) combustion. In previous studies, RCCI combustion with in-cylinder fuel blending using port-fuel-injection of a low reactivity fuel and optimized direct-injections of higher reactivity fuels was demonstrated to permit near-zero levels of NOX and PM emissions in-cylinder, while simultaneously realizing high thermal efficiencies. The present study consists of RCCI experiments at loads from 4 to 17 bar indicated mean effective pressure at engine speeds of 1,300 and 1,700 [rev/min]. The experiments used a modified piston to examine the effect of piston crevice volume, squish geometry, and compression ratio on performance and efficiency.

Two different types of mesh used for diesel combustion with the KIVA-4 code are compared. One is a well established conventional KIVA-3 type polar mesh. The other is a non-polar mesh with uniform size throughout the piston bowl so as to reduce the number of cells and to improve the quality of the cell shapes around the cylinder axis which can contain many fuel droplets that affect prediction accuracy and the computational time. This mesh is specialized for the KIVA-4 code which employs an unstructured mesh. To prevent dramatic changes in spray penetration caused by the difference in cell size between the two types of mesh, a recently developed spray model which reduces mesh dependency of the droplet behavior has been implemented. For the ignition and combustion models, the Shell model and characteristic time combustion (CTC) model are employed.