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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.

This computational study compares predictions and experimental results for the use of direct injected iso-octane fuel during the negative valve overlap (NVO) period to achieve HCCI combustion. The total fuel injection was altered in two ways. First the pre-DI percent, (the ratio of direct injected fuel during the NVO period “pre-DI” to the secondary fuel supplied at the intake manifold “PI”), was varied at a fixed pre-DI injection timing, Secondly the timing of the pre-DI injection was varied while all of the fuel was supplied during the NVO period. A multi-zone, two-dimensional CFD simulation with chemistry was performed using KIVA-3V release 2 implemented with the CHEMKIN solver. The simulations were performed during the NVO period only.

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.

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.

Homogeneous Charge Compression Ignition (HCCI) combustion is being considered as a practical solution for diesel engines due to its high efficiency and low NOx and PM emissions. However, for diesel HCCI operation, there are still several problems that need to be solved. One is the spay-wall impingement issue associated with early injection, and a further problem is the extension of HCCI operation from low load to higher engine loads. In this study, a combination of Adaptive Injection Strategies (AIS) and a Two-Stage Combustion (TSC) strategy are proposed to solve the aforementioned problems. A multi-dimensional Computational Fluid Dynamics (CFD) code with detailed chemistry, the KIVA-CHEMKIN-GA code, was employed in this study, where Genetic Algorithms (GA) were used to optimize heavy-duty diesel engine operating parameters. The TSC concept was applied to optimize the combustion process at high speed (1737 rev/min) and medium load (57% load).

Hydraulically intensified medium pressure common rail (MPCR) electronic fuel injection systems are an attractive concept for heavy-duty diesel engine applications. They offer excellent packaging flexibility and thorough engine management system integration. Two different concepts were evaluated in this study. They are different in how the pressure generation and injection events are related. One used a direct principle, where the high-pressure generation and injection events occur simultaneously producing a near square injection rate profile. Another concept was based on an indirect principle, where potential energy (pressure) is first stored inside a hydraulic accumulator, and then released during injection, as a subsequent event. A falling rate shape is typically produced in this case. A unit pump, where the hydraulic intensifier is separated from the injector by a high-pressure line, and a unit injector design are considered for both concepts.

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.

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.

Lagrangian-Droplet and Eulerian-Fluid (LDEF) based spray models are widely used in engine and combustion system computations. Numerical grid and time-step-dependencies of Discrete Droplet Lagrangian spray models have been identified by previous researchers [1, 2]. The two main sources of grid-dependency are due to errors in predicting the droplet-gas relative velocity, and errors in describing droplet-droplet collision and coalescence processes. For reducing grid-dependency due to the relative velocity effects, results from gas jet theory are introduced along with a Lagrangian collision model [1, 3] and applied to model diesel sprays. The improved spray model is implemented in the engine simulation code KIVA-3V [4] and is tested under various conditions, including constant volume chambers and various engine geometries with vaporizing and combusting sprays with detailed chemistry.

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.

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.

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.

A computational optimization study was performed for a direct-injection diesel engine using a recently developed 1-D-KIVA3v-GA (1-Dimensional-KIVA3v-Genetic Algorithm) computer code. The code performs a full engine cycle simulation within the framework of a genetic algorithm (GA) code. Design fitness is determined using a 1-D (one-dimensional) gas dynamics code for the simulation of the gas exchange process, coupled with the KIVA3v code for three-dimensional simulations of spray, combustion and emissions formation. The 1-D-KIVA3v-GA methodology was used to simultaneously investigate the effect of eight engine input parameters on emissions and performance for four cases, which include cases at 2500 RPM and 1000 RPM, with both simulated at high-load and low-load conditions.

An integrated system based modeling approach has been developed to understand early Direct Injection (DI) Diesel Homogeneous Charge Compression Ignition (HCCI) process. GT-Power, a commercial one-dimensional (1-D) engine cycle code has been coupled with an external cylinder model which incorporates sub-models for fuel injection, vaporization, detailed chemistry calculations (Chemkin), heat transfer, energy conservation and species conservation. In order to improve the modeling accuracy, a multi-zone model has been implemented to account for temperature and fuel stratifications in the cylinder charge. The predictions from the coupled simulation have been compared with experimental data from a single cylinder Caterpillar truck engine modified for Diesel HCCI operation. A parametric study is conducted to examine the effect of combustion timing on four major control parameters. Overall the results show good agreement of the trends between the experiments and model predictions.

A reduced chemical reaction mechanism is developed and validated in the present study for multi-dimensional diesel HCCI engine combustion simulations. The motivation for the development of the reduced mechanism is to enhance the computational efficiency of engine stimulations. The new reduced mechanism was generated starting from an existing n-heptane mechanism (40 species and 165 reactions). The procedure of generating the reduced mechanism included: using SENKIN to produce the ignition delay data and solution files, using XSENKPLOT to analyze the base mechanism and to identify important reactions and species, eliminating unimportant species and reactions, formulating the new reduced mechanism, using the new mechanism to generate ignition delay data, and finally adjusting kinetic constants in the new mechanism to improve ignition delay and engine combustion predictions to account for diesel fuel cetane number and composition effects.

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).

A universal engine combustion model based on the level-set approach was developed in this study. It was first used to model combustion in Spark Ignition (SI) and Direct Injection Spark Ignition (DISI) engines when combined with the Discrete Particle Spark Ignition model, in which the ignition kernel is represented by particles. Once the flame kernel grows to a size that the turbulent flame is fully developed, the G-equation model is used to track the subsequent propagation of the turbulent flame. When combined with a characteristic time combustion model, the triple flame structure that is found in DISI engine combustion was successfully modeled. The model was also applied to simulate diesel combustion where the diffusion combustion regime is dominant. In this case, the ignition was modeled using the Shell auto-ignition model. Satisfactory agreement with features of the conceptual diesel combustion model of Dec [1997] was found.

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 contribution of fuel adsorption in engine oil and its subsequent desorption following combustion to the engine-out hydrocarbon (HC) emissions of a spark-ignited, air-cooled, V-twin utility engine was studied by comparing steady state and cycle-resolved HC emission measurements from operation with a standard full-blend gasoline, and with propane, which has a low solubility in oil. Experiments were performed at two speeds and three loads, and for different mean crankcase pressures. The crankcase pressure was found to impact the HC emissions, presumably through the ringpack mechanism, which was largely unaltered by the different fuels. The average and cycle-resolved HC emissions were found to be in good agreement, both qualitatively and quantitatively, for the two fuels. Further, the two fuels showed the same response to changes in the crankcase pressure. The solubility of propane in the oil is approximately an order of magnitude lower than for gasoline.

In-cylinder heat flux and temperature measurements were obtained in an air-cooled four-stroke utility engine for a range of air-fuel ratios. For these measurements, the magnitude of the integrated heat flux peaked at the stoichiometric air-fuel ratio, with an approximately linear decrease on either side of stoichiometric. Advancing the spark generally increased the magnitude of the integrated heat flux. Evaluation of the Brake Specific Integrated Heat Flux (BSIHF) mitigated these trends, and, the effects of changes in timing were eliminated for some operating conditions Examination of the BSIHF from the compression and expansion stroke showed behavior mimicking the full cycle BSIHF. However, the fraction of the total flux contributed by this portion of the cycle varied greatly from approximately 98% of the total to approximately 75% of the total.