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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.

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.

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.

An optimization study combining multidimensional CFD modeling and a global, evolutionary search technique known as the Genetic Algorithm has been carried out. The subject of this study was a 2-stroke, spark-ignited, direct-injection, single-cylinder research engine (SCRE). The goal of the study was to optimize the part load operating parameters of the engine in order to achieve the lowest possible emissions, improved fuel economy, and reduced wall heat transfer. Parameters subject to permutation in this study were the start-of-injection (SOI) timing, injection duration, spark timing, fuel injection angle, dwell between injections, and the percentage of fuel mass in the first injection pulse. The study was comprised of three cases. All simulations were for a part load, intermediate-speed condition representing a transition operating regime between stratified charge and homogeneous charge operation.

A radiation model based on the Discrete Ordinates Method (DOM) was incorporated into the KIVA3v multidimensional code to study the effects of soot and radiation on diesel engine performance at high load. A thermophoretic soot deposition model was implemented to predict soot concentrations in the near-wall region, which was found to affect radiative heat flux levels. Realistic, non-uniform combustion chamber wall surface temperature distributions were predicted using a finite-element-based heat conduction model for the engine metal components that was coupled with KIVA3v in an iterative scheme. The more accurate combustion chamber wall temperatures enhanced the accuracy of both the radiation and soot deposition models as well as the convective heat transfer model. For a basline case, (1500 rev/min, 100% load) it was found that radiation can account for as much as 30% of the total wall heat loss and that soot deposition in each cycle is less than 3% of the total in-cylinder soot.

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.

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.

A study of the combined use of split injections, EGR, and flexible boosting was conducted. Statistical optimization of the engine operating parameters was accomplished using a new response surface method. The objective of the study was to demonstrate the emissions and fuel consumption capabilities of a state-of-the-art heavy -duty diesel engine when using split injections, EGR, and flexible boosting over a wide range of engine operating conditions. Previous studies have indicated that multiple injections with EGR can provide substantial simultaneous reductions in emissions of particulate and NOx from heavy-duty diesel engines, but careful optimization of the operating parameters is necessary in order to receive the full benefit of these combustion control techniques. Similarly, boost has been shown to be an important parameter to optimize. During the experiments, an instrumented single-cylinder heavy -duty diesel engine was used.

A new ignition and combustion model has been developed and tested for use in premixed spark-ignition engines. The ignition model is referred to as the Discrete Particle Ignition Kernel (DPIK) model, and it uses Lagrangian markers to track the flame-front growth. The model includes the effects of electrode heat transfer on the early flame kernel growth process, and it is used in conjunction with a characteristic-time-scale combustion model once the ignition kernel has grown to a size where the effects of turbulence on the flame must be considered. A new term which accounts for the effect of air-fuel ratio, was added to the combustion model for modeling combustion in very lean and very rich mixtures. The flame kernel size predicted by the DPIK model was compared with measurements of Maly and Vogel. Furthermore, predictions of the electrode heat transfer were compared with data of Kravchik and Heywood. In both comparisons the model predictions were in good agreement with the experiments.

A computational optimization study is performed for a heavy-duty direct-injection diesel engine using the recently developed KIVA-GA computer code. KIVA-GA performs full cycle engine simulations within the framework of a Genetic Algorithm (GA) global optimization code. Design fitness is determined using a one-dimensional gas -dynamics code for calculation of the gas exchange process, and a three-dimensional CFD code based on KIVA-3V for spray, combustion and emissions formation. The performance of the present Genetic Algorithm is demonstrated using a test problem with a multi-modal analytic function in which the optimum is known a priori. The KIVA-GA methodology is next used to simultaneously investigate the effects of six engine input parameters on emissions and performance for a high speed, medium load operating point for which baseline experimental validation data is available.

A study of statistical optimization of engine operating parameters was conducted. The objective of the study was to develop a strategy to efficiently optimize operating parameters of diesel engines with multiple injection and EGR capabilities. Previous studies have indicated that multiple injections with EGR can provide substantial simultaneous reductions in emissions of particulate and NOx from heavy-duty diesel engines, but careful optimization of the operating parameters is necessary in order to receive the full benefit of these combustion control techniques. The goal of the present study was to optimize the control parameters to reduce emissions and brake specific fuel consumption. An instrumented single-cylinder heavy-duty diesel engine was used with a prototype mechanically actuated (cam driven) fuel injection system.

Two-Color imaging optics were developed and used to observe soot emission processes in a modern heavy-duty diesel engine. The engine was equipped with a common rail, electronically-controlled, high-pressure fuel injection system that is capable of up to four injection pulses per engine cycle. The engine was instrumented with an endoscope system for optical access for the combustion visualization. Multidimensional combustion and soot modeling results were used for comparisons to enhance the understanding and interpretation of the experimental data. Good agreement between computed and measured cylinder pressures, heat release and soot and NOx emissions was achieved. In addition, good qualitative agreement was found between in-cylinder soot concentration (KL) and temperature fields obtained from the endoscope images and those obtained from the multidimensional modeling.

A modified version of the multi-dimensional KIVA-II code is used to model the effects of multiple injection schemes and exhaust gas recirculation (EGR) on direct injected diesel engine NOx and soot emissions. The computational results, which also considered double and triple injection schemes and varying EGR amounts, are compared with experimental data obtained from a single cylinder version of a Caterpillar heavy-duty truck engine. The study is done at high load (75% of peak torque at 1600 rpm) where EGR is known to produce unacceptable increases in soot (particulate). The effect of soot and spray model formulations are considered. This includes a new spray model based on Rayleigh-Taylor instabilities for liquid breakup. A soot oxidation model that accounts for turbulent mixing and kinetic effects were found to give accurate results. The results showed excellent agreement between predicted and measured in-cylinder pressure, and heat release data for the various cases.

A two-dimensional transient Heat Conduction in Components code (HCC) was successfully set up and extensively used to calculate the temperature field existing in real engine combustion chambers. The Saul'yev method, an explicit, unconditionally stable finite difference method, was used in the code. Consideration of the gasket between the cylinder wall and head, and the air gap between the piston and liner were included in the code. The realistic piston bowl shape was modeled with a grid transformation and piston movement was considered. The HCC code was used to calculate the wall temperature of an Isuzu ceramic engine and a Caterpillar heavy-duty diesel engine. The code was combined with the KIVA-II code in an iterative loop, in which the KIVA-II code provided the instantaneous local heat flux on the combustion chamber surfaces, and the HCC code computed the time-averaged wall temperature distribution on the surfaces.