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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.

The objective of this investigation is to optimize light-duty diesel engine operating parameters using Adaptive Injection Strategies (AIS) for optimal fuel preparation. A multi-dimensional Computational Fluid Dynamics (CFD) code with detailed chemistry, the KIVA-CHEMKIN code, is employed and a Multi-Objective Genetic Algorithm (MOGA) is used to study a Two-Stage Combustion (TSC) concept. The combustion process is considered at a light load operating condition (nominal IMEP of 5.5 bar and high speed (2000 rev/min)), and two combustion modes are combined in this concept. The first stage is ideally Homogeneous Charge Compression Ignition (HCCI) combustion and the second stage is diffusion combustion under high temperature and low oxygen concentration conditions. Available experimental data on a 1.9L single-cylinder research engine is used for model validation.

A detailed comparison of cylinder pressure derived combustion performance and engine-out emissions is made between an all-metal single-cylinder light-duty diesel engine and a geometrically equivalent engine designed for optical accessibility. The metal and optically accessible single-cylinder engines have the same nominal geometry, including cylinder head, piston bowl shape and valve cutouts, bore, stroke, valve lift profiles, and fuel injection system. The bulk gas thermodynamic state near TDC and load of the two engines are closely matched by adjusting the optical engine intake mass flow and composition, intake temperature, and fueling rate for a highly dilute, low temperature combustion (LTC) operating condition with an intake O2 concentration of 9%. Subsequent start of injection (SOI) sweeps compare the emissions trends of UHC, CO, NOx, and soot, as well as ignition delay and fuel consumption.

Experiments were performed on a single-cylinder heavy-duty Caterpillar SCOTE 3401E engine at high speed (1737 rev/min) and loads up to 60% of full load for fully Premixed Charge Compression Ignition (PCCI) combustion. The engine was equipped with a high pressure (150 MPa) Caterpillar 300B HEUI fuel injection system. The engine was run with EGR levels up to 75% and with equivalence ratios up to 0.95. These experiments resulted in compliance of NOx and PM emissions to 2010 emissions mandates levels up to the tested load. The set of experiments also demonstrated the importance of cylinder charge preparation by way of optimized start-of-combustion timing for sufficient in-cylinder mixing. It was found that increased EGR rates, even with the correspondingly increased equivalence ratios, increase mixing time and substantially decrease PM emissions.

A transport equation residual model incorporating refined G-equation and detailed chemical kinetics combustion models has been developed and implemented in the ERC KIVA-3V release2 code for Gasoline Direct Injection (GDI) engine simulations for better predictions of flame propagation. In the transport equation residual model a fictitious species concept is introduced to account for the residual gases in the cylinder, which have a great effect on the laminar flame speed. The residual gases include CO2, H2O and N2 remaining from the previous engine cycle or introduced using EGR. This pseudo species is described by a transport equation. The transport equation residual model differentiates between CO2 and H2O from the previous engine cycle or EGR and that which is from the combustion products of the current engine cycle.

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).

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.

Deviations between transient and steady state operation of a modern light duty diesel engine were identified by comparing rapid load transitions to steady state tests at the same speeds and fueling rates. The validity of approximating transient performance by matching the transient charge air flow rate and intake manifold pressure at steady state was also assessed. Results indicate that for low load operation with low temperature combustion strategies, transient deviations of MAF and MAP from steady state values are small in magnitude or short in duration and have relatively little effect on transient engine performance. A new approximation accounting for variations in intake temperature and excess oxygen content of the EGR was more effective at capturing transient emissions trends, but significant differences in magnitudes remained in certain cases indicating that additional sources of variation between transient and steady state performance remain unaccounted for.

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.

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.

Homogeneous-charge, compression-ignition (HCCI) combustion is triggered by spontaneous ignition in dilute homogeneous mixtures. The combustion rate must be reduced by suitable solutions such as high rates of Exhaust Gas Recirculation (EGR) and/or lean mixtures. HCCI is considered a very effective way to reduce engine pollutant emissions, however only a few HCCI engines have entered into production. HCCI combustion currently cannot be extended to the whole engine operating range, especially to high loads, since the use of EGR displaces air from the cylinder, limiting engine mean effective pressure, thus the engine must be able to operate also in conventional mode. This paper concerns an innovative concept to control HCCI combustion in diesel-fuelled engines. This new combustion concept is called Homogenous Charge Progressive Combustion (HCPC). HCPC is based on split-cycle principle.

Homogeneous-charge, compression-ignition (HCCI) combustion is triggered by spontaneous ignition in dilute homogeneous mixtures. The combustion rate must be reduced by suitable solutions such as high rates of Exhaust Gas Recirculation (EGR) and/or lean mixtures. HCCI is considered a very effective way to reduce engine pollutant emissions, however only a few HCCI engines have entered into production. HCCI combustion currently cannot be extended to the whole engine operating range, especially to high loads, since the use of EGR displaces air from the cylinder, limiting engine mean effective pressure, thus the engine must be able to operate also in conventional mode. This paper concerns a study of an innovative concept to control HCCI combustion in diesel-fuelled engines. The concept consists in forming a pre-compressed homogeneous charge outside the cylinder and gradually admitting it into the cylinder during the combustion process.

The applicability of several popular diesel particulate matter (PM) measurement techniques to low temperature combustion is examined. The instruments' performance in measuring low levels of PM from advanced diesel combustion is evaluated. Preliminary emissions optimization of a high-speed light-duty diesel engine was performed for two conventional and two advanced low temperature combustion engine cases. A low PM (<0.2 g/kg_fuel) and NOx (<0.07 g/kg_fuel) advanced low temperature combustion (LTC) condition with high levels of exhaust gas recirculation (EGR) and early injection timing was chosen as a baseline. The three other cases were selected by varying engine load, injection timing, injection pressure, and EGR mass fraction. All engine conditions were run with ultra-low sulfur diesel fuel. An extensive characterization of PM from these engine operating conditions is presented.

Many studies have demonstrated ability of low temperature combustion to yield low NOx and soot while maintaining diesel-like thermal efficiencies. Methods of achieving low temperature combustion are numerous and range from using high cetane number fuels, like diesel, with large amounts of exhaust gas recirculation, to completely premixing a high octane number fuel, like gasoline, and approaching an HCCI-like condition. Both of the aforementioned techniques have relatively short combustion duration that results in very a rapid rate of heat release, and hence very rapid rates of pressure rise. This has been one of the major challenges for premixed, low temperature combustion at mid and high load. Reactivity Controlled Compression Ignition (RCCI) has been introduced recently, which is a dual fuel partially premixed combustion concept.

The potential of low temperature combustion to yield low NOx and soot while maintaining diesel-like thermal efficiencies has been demonstrated through countless studies. Methods of achieving low temperature combustion are just as numerous and they range from using high cetane number fuels, like diesel, with large amounts of exhaust gas recirculation, to completely premixing a high octane number fuel, like gasoline, and approaching an HCCI-like condition. The potential of operating a heavy-duty compression ignition engine fueled with conventional gasoline in a partially premixed combustion mode to have high thermal efficiency and low emissions has been demonstrated in this study. The objective of this work was to optimize the engine using computational tools. The KIVA3V-CHEMKIN code, a multi-dimensional engine CFD model was coupled to a Nondominated Sorting Genetic Algorithm (NSGA II), which is a multi-objective genetic algorithm.

The objective of this research is a detailed investigation of unburned hydrocarbon (UHC) in a highly-dilute diesel low temperature combustion (LTC) regime. This research concentrates on understanding the mechanisms that control the formation of UHC via experiments and simulations in a 0.48L signal-cylinder light duty engine operating at 2000 r/min and 5.5 bar IMEP with multiple injections. A multi-gas FTIR along with other gas and smoke emissions instruments are used to measure exhaust UHC species and other emissions. Controlled experiments in the single-cylinder engine are then combined with three computational tools, namely heat release analysis of measured cylinder pressure, analysis of spray trajectory with a phenomenological spray model using in-cylinder thermodynamics [1], and KIVA-3V Chemkin CFD computations recently tested at LTC conditions [2].

A, three-dimensional CFD code, based on the KIVA code, is used to explore alternatives to conventional DI diesel engine designs for reducing NOx and soot emissions without sacrificing engine performance. The effects of combustion chamber design and fuel spray orientation are investigated using a new proposed GAMMA engine concept, and two new multiple injector combustion system (MICS) designs which utilize multiple injectors to increase gas motion and enhance fuel/air mixing in the combustion chamber. From these computational studies, it is found that both soot and nitrous oxide emissions can be significantly reduced without the need for more conventional emission control strategies such as EGR or ultra high injection pressure. The results suggest that CFD models can be a useful tool not only for understanding combustion and emissions production, but also for investigating new design concepts.

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.

Progress on the development and validation of a CFD model for diesel engine combustion and flow is described. A modified version of the KIVA code is used for the computations, with improved submodels for liquid breakup, drop distortion and drag, spray/wall impingement with rebounding, sliding and breaking-up drops, wall heat transfer with unsteadiness and compressibility, multistep kinetics ignition and laminar-turbulent characteristic time combustion models, Zeldovich NOx formation, and soot formation with Nagle Strickland-Constable oxidation. The code also considers piston-cylinder-liner crevice flows and allows computations of the intake flow process in the realistic engine geometry with two moving intake valves. Significant progress has been made using a modified RNG k-ε turbulence model, and a multicomponent fuel vaporization model and a flamelet combustion model have been implemented.