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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. A two-stage combustion (TSC) concept was explored to optimize the combustion process at high speed (1737 rev/min) and medium load (57% load). Two combustion modes were 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. This can be achieved for example by optimization of two-stage combustion using multiple injection or sprays from two different injectors.

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 numerical study of the effects of injection parameters and operating conditions for diesel-fuel HCCI operation is presented with consideration of Variable Geometry Sprays (VGS). Methods of mixture preparation are explored that overcome one of the major problems in HCCI engine operation with diesel fuel and conventional direct injection systems, i.e., fuel loss due to wall impingement and the resulting unburned fuel. Low pressure injection of hollow cone sprays into the cylinder of a production engine with the spray cone angle changing during the injection period were simulated using the multi-dimensional KIVA-3V CFD code with detailed chemistry. Variation of the starting and ending spray angles, injection timing, initial cylinder pressure and temperature, swirl intensity, and compression ratio were explored. As a simplified case of VGS, two-pulse, hollow-cone sprays were also simulated.

Low-temperature combustion concepts that utilize cooled EGR, early/retarded injection, high swirl ratios, and modest compression ratios have recently received considerable attention. To understand the combustion and, in particular, the soot formation process under these operating conditions, a modeling study was carried out using the KIVA-3V code with an improved phenomenological soot model. This multi-step soot model includes particle inception, surface growth, surface oxidation, and particle coagulation. Additional models include a piston-ring crevice model, the KH/RT spray breakup model, a droplet wall impingement model, a wall heat transfer model, and the RNG k-ε turbulence model. The Shell model was used to simulate the ignition process, and a laminar-and-turbulent characteristic time combustion model was used for the post-ignition combustion process.

The strategy of variable Intake Valve Closure (IVC) timing, as a means to improve performance and emission characteristics, has gained much acceptance in gasoline engines; yet, it has not been explored extensively in diesel engines. In this study, genetic algorithms are used in conjunction with the multi-dimensional engine simulation code KIVA-3V to investigate the optimum operating variables for a typical heavy-duty diesel engine working with late IVC. The effects of start-of-injection timing, injection duration and exhaust gas recirculation were investigated along with the intake valve closure timing. The results show that appreciable reductions in NOx+HC (∼82%), soot (∼48%) and BSFC (∼7.4%) are possible through this strategy, as compared to a baseline diesel case of (NOx+HC) = 9.48g/kW-hr, soot = 0.17 g/kW-hr and BSFC = 204 g-f/kW-hr. The additional consideration of double injections helps to reduce the high rates of pressure rise observed in a single injection scheme.

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.

Experiments show that intake flow details have a significant influence on High-Speed Direct-Injection (HSDI) diesel engine soot emissions. Four different intake modes were simulated using the combination of the CFD codes, STAR-CD and KIVA-3V, to investigate spray-intake flow-emission interaction characteristics. The simulation results were compared to steady-state flow bench data and engine experimental data. It was found that it is difficult to accurately predict the timing of the small pilot and main combustion events, simultaneously, with current simplified ignition models. NOx emissions were predicted well, however, an insensitivity of the soot emissions to the details of the intake process was found, mainly due to the deficiencies in predicting the ignition delay. The results show that a strong swirling flow causes the formed soot to remain within the bowl, leading to high soot emissions.

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 level set G-equation model has been developed to model the combustion process in spark ignition engines. The spark ignition process was modeled using an improved version of the Discrete Particle Ignition Kernel (DPIK) model. The two models were implemented into the KIVA-3V code to simulate SI engine combustion under both premixed and direct injection conditions. In the ignition model, the ignition kernel growth is tracked by Lagrangian markers, and spark discharge energy and flow turbulence effects on the kernel growth are considered. Once the ignition kernel grows to a size where the turbulent flame is fully developed, the G-equation model is used to track the mean turbulent flame evolution. When combined with a characteristic time scale combustion model, the models were also used to simulate stratified combustion in DISI engines, where the triple flame structure must be considered.

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.

The present study uses a numerical model to investigate the effects of flow turbulence on premixed iso-octane HCCI engine combustion. Different levels of in-cylinder turbulence are generated by using different piston geometries, namely a disc-shape versus a square-shape bowl. The numerical model is based on the KIVA code which is modified to use CHEMKIN as the chemistry solver. A detailed reaction mechanism is used to simulate the fuel chemistry. It is found that turbulence has significant effects on HCCI combustion. In the current engine setup, the main effect of turbulence is to affect the wall heat transfer, and hence to change the mixture temperature which, in turn, influences the ignition timing and combustion duration. The model also predicts that the combustion duration in the square bowl case is longer than that in the disc piston case which agrees with the measurements.

Optimizations were performed on a Heavy-Duty diesel engine equipped with a conventional electronic unit injector in order to minimize fuel consumption, and emissions of NOx and particulate matter. A low speed light load case and a high speed light load case were optimized with these considerations in mind. Exhaustive parametric studies were performed in order to find sets of operating conditions that resulted in low emissions and high fuel economy. It was found for the low speed light load case (Mode 2, 25% load and 821 rev/min) that low emissions operating conditions existed at either very early or very late start-of-injection timings and high EGR (PM = 0.018 g/kW-hr, NOx + HC = 1.493 g/kW-hr with SOI = -21 degrees ATDC, 48% EGR; or 0.085 g/kW-hr PM, 1.02 g/kW-hr NOx with SOI = 4 degrees ATDC, 39% EGR).

To overcome the trade-off between NOx and particulate emissions for future diesel vehicles and engines it is necessary to seek methods to lower pollutant emissions. The desired simultaneous improvement in fuel efficiency for future DI (Direct Injection) diesels is also a difficult challenge due to the combustion modifications that will be required to meet the exhaust emission mandates. This study demonstrates the emission reduction capability of split injections, EGR (Exhaust Gas Recirculation), and other parameters on a High Speed Direct Injection (HSDI) diesel engine equipped with a common rail injection system using an RSM (Response Surface Method) optimization method. The optimizations were conducted at 1757 rev/min, 45% load. Six factors were considered for the optimization, namely the EGR rate, SOI (Start of Injection), intake boost pressure, and injection pressure, the percentage of fuel in the first injection, and the dwell between injections.

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.

The present study investigated HCCI combustion in a heavy-duty diesel engine both experimentally and numerically. The engine was equipped with a hollow-cone pressure-swirl injector using gasoline direct injection. Characteristics of HCCI combustion were obtained by very early injection with a heated intake charge. Experimental results showed an increase in NOx emission and a decrease in UHC as the injection timing was retarded. It was also found that optimization can be achieved by controlling the intake temperature together with the start-of-injection timing. The experiments were modeled by using an engine CFD code with detailed chemistry. The CHEMKIN code was implemented into KIVA-3V such that the chemistry and flow solutions were coupled. The model predicted ignition timing, cylinder pressure, and heat release rates reasonably well. The NOx emissions were found to increase as the injection timing was retarded, in agreement with experimental results.

Managing the injection rate profile is a powerful tool to control engine performance and emission levels. In particular, Common Rail (C.R.) injection systems allow an almost completely flexible fuel injection event in DI-diesel engines by permitting a free mapping of the start of injection, injection pressure, rate of injection and, in the near future, multiple injections. This research deals with the development of a network-based numerical tool for understanding operating condition limits of the Common Rail injector. The models simulate the electro-fluid-mechanical behavior of the injector accounting for cavitation in the nozzle holes. Validation against experiments has been performed. The model has been used to provide insight into the operating conditions of the injector and in order to highlight the application to injection system design.

A micro-genetic algorithm (μGA) optimization method was applied to a heavy-duty, direct-injected diesel engine via an automated test bed system. The goal of this application was to demonstrate the feasibility and advantages of automated optimization experiments. With the genetic algorithm, no user input was required other than the factors of interest and their allowable ranges. This means that once the routine was initiated, it was essentially run undisturbed until a preset objective level was reached or a preset number of generations had been run. The automated μGA was successfully demonstrated at all points of the six-mode transient cycle simulation, excluding idle. To accomplish the automated experiments, an automated testing system was developed around a Caterpillar single-cylinder diesel engine.

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.

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.

Experimental data is used in conjunction with multi-dimensional modeling in a modified version of the KIVA-3V code to characterize the emissions behavior of a high-speed, direct-injection diesel engine. Injection pressure and EGR are varied across a range of typical small-bore diesel operating conditions and the resulting soot-NOx tradeoff is analyzed. Good agreement is obtained between experimental and modeling trends; the HSDI engine shows increasing soot and decreasing NOx with higher EGR and lower injection pressure. The model also indicates that most of the NOx is formed in the region where the bulk of the initial heat release first takes place, both for zero and high EGR cases. The mechanism of NOx reduction with high EGR is shown to be primarily through a decrease in thermal NOx formation rate.