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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 newly developed turbocharging system, named MIXPC, is proposed and the performance of the proposed system applied to diesel engines is evaluated. The aim of this proposed system is to reduce the scavenging interference between cylinders, and to lower the pumping loss in cylinders and the brake specific fuel consumption. In addition, exhaust manifolds of simplified design can be constructed with small dimensions, low weight and a single turbine entry. A simulation code based on a second-order FVM+TVD (finite volume method + total variation diminishing) is developed and used to simulate engines with MIXPC. By simulating a 16V280ZJG diesel engine using the MPC turbocharging system and MIXPC, it is found that not only the average scavenging coefficient of MIXPC is larger than that of MPC, but also cylinders of MIXPC have more homogeneous scavenging coefficients than that of MPC, and the pumping loss and BSFC of MIXPC are lower than those of MPC.

Gasoline fueled Homogeneous Charge Compression Ignition (HCCI) combustion with internal exhaust gas re-circulation using Negative Valve Overlap (NOL) was investigated by means of calculation and experiment in order to apply this technology to practical use with sufficient operating range and with acceptable emission and fuel consumption. In this paper we discuss the basic characteristics of NOL-HCCI with emphasis on the influence of intake valve timing on load range, residual gas fraction and induction air flow rate. Emission and fuel consumption under various operation conditions are also discussed. A water-cooled 250cc single cylinder engine with a direct injection system was used for this study. Three sets of valve timing were selected to investigate the effect of intake valve opening duration. Experimental results demonstrated that an engine speed of approximately 2000rpm yields an NMEP (Net Mean Effective Pressure) range from 200kPa to 400kPa.

The effects of residual gas mixing were studied in a single-cylinder, air-cooled utility engine using both external exhaust gas recirculation (EGR) and internal residual retention. EGR was introduced far upstream of the throttle to ensure proper mixing. Internal residual was changed by varying the length of the valve overlap period. EGR was measured in the intake system; the total in-cylinder diluent was directly measured using a skip-fire, cylinder dumping technique. A sweep of diluent fraction was performed at different engine speeds, engine loads, fuel mixture preparation systems, and ignition timings. An optimum level of diluent, where the combined hydrocarbon and NOx emissions were minimal, was found to exist for each operating condition. Higher levels of diluent, either through internal retention or external recirculation, caused the combined emissions to increase.

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).

The use of low temperature combustion (LTC) modes has demonstrated abilities to lower diesel engine emissions while maintaining good fuel consumption. LTC is assumed to be a viable solution to assist in meeting stringent upcoming diesel engine emissions targets, particularly nitric oxides (NOx) and particulate matter (PM). However, LTC is currently limited to low engine loads and is not a feasible solution at higher loads on production engines. A mixed mode combustion strategy must be implemented to take advantage of the benefits offered from LTC at the low loads and speeds while switching to a conventional diesel combustion strategy at higher loads and speeds and thus allowing full range use of the engine under realistic driving conditions. Experiments were performed to characterize engine out emissions during transient engine operating conditions involving LTC combustion strategies.

Two advanced combustion models have been validated with the KIVA-3V Release 2 code in the context of two-stage combustion in a heavy duty diesel engine. The first model uses CHEMKIN to directly integrate chemistry in each computational cell. The second model accounts for flame propagation with the G-equation, and CHEMKIN predicts autoignition and handles chemistry ahead of and behind the flame front. A Damköhler number criterion was used in flame containing cells to characterize the local mixing status and determine whether heat release and species change should be a result of flame propagation or volumetric heat release. The purpose of this criterion is to make use of physical and chemical time scales to determine the most appropriate chemistry model, depending on the mixture composition and thermodynamic properties of the gas in each computational cell.

A multi-objective genetic algorithm methodology was applied to a heavy-duty diesel engine at three different operating conditions of interest. Separate optimizations were performed over various fuel injection nozzle parameters, piston bowl geometries and swirl ratios (SR). Different beginning of injection (BOI) timings were considered in all optimizations. The objective of the optimizations was to find the best possible fuel economy, NOx, and soot emissions tradeoffs. The input parameter ranges were determined using design of experiment methodology. A non-dominated sorting genetic algorithm II (NSGA II) was used for the optimization. For the optimization of piston bowl geometry, an automated grid generator was used for efficient mesh generation with variable geometry parameters. The KIVA3V release 2 code with improved ERC sub-models was used. The characteristic time combustion (CTC) model was employed to improve computational efficiency.

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 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 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 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 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.

The heavy-duty diesel engine industry is required to meet stringent emission standards. There is also the demand for more fuel efficient engines by the customer. In a previous study on an engine with variable intake valve closure timing, the authors found that an early single injection and accompanying premixed charge compression ignition (PCCI) combustion provides advantages in emissions and fuel economy; however, unacceptably high peak pressures and rates of pressure-rise impose a severe operating constraint. The use of a Pressure Reactive Piston assembly (PRP) as a means to limit peak pressures is explored in the present work. The concept is applied to a heavy-duty diesel engine and genetic algorithms (GA) are used in conjunction with the multi-dimensional engine simulation code KIVA-3V to provide an optimized set of operating variables.

A computer model that is able to predict the occurrence of knock in spark ignition engines has been developed and implemented into the KIVA-3V code. Three major sub-models were used to simulate the overall process, namely the spark ignition model, combustion model, and end-gas auto-ignition models. The spark ignition and early flame development is modeled by a particle marker technique to locate the flame kernel. The characteristic-time combustion model is applied to simulate the propagation of the regular flame. The autoignition chemistry in the end-gas was modeled by a reduced chemical kinetics mechanism that is based on the Shell model. The present model was validated by simulating the experimental data in three different engines. The spark ignition and the combustion models were first validated by simulating a premixed Caterpillar engine that was converted to run on propane. Computed cylinder pressure agrees well with the experimental data.

A combustion chamber geometry design optimization study has been performed on a high-speed direct-injection (HSDI) automotive diesel engine at a part-load medium-speed operating condition using both modeling and experiments. A model-based optimization was performed using the KIVA-GA code. This work utilized a newly developed 6-parameter automated grid generation technique that allowed a vast number of piston geometries to be considered during the optimization. Other salient parameters were included that are known to have an interaction with the chamber geometry. They included the start of injection (SOI) timing, swirl ratio (SR), exhaust gas recirculation percentage (EGR), injection pressure, and the compression ratio (CR). The measure of design fitness used included NOx, soot, unburned hydrocarbon (HC), and CO emissions, as well as the fuel consumption. Subsequently, an experimental parametric study was performed using the piston geometry found by the numerical optimization.

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.

An integrated system model containing sub-models for a diesel engine, NOx and soot emissions, and a diesel particulate filter (DPF) has been used to simulate stead-state engine operating conditions. The simulation results have been used to investigate the effect of DPF loading and passive regeneration on engine performance and emissions. This work is the continuation of previous work done to create an overall diesel engine/exhaust system integrated model. As in the previous work, a diesel engine, exhaust system, engine soot emissions, and diesel particulate filter (DPF) sub-models have been integrated into an overall model using Matlab Simulink. For the current work new sub-models have been added for engine-out NOx emissions and an engine feedback controller. The integrated model is intended for use in simulating the interaction of the engine and exhaust aftertreatment components.

Transient engine tests were performed to investigate behavior of transient emissions--hydrocarbon (HC) and oxides of Nitrogen (NOx)--in a 2.4L turbocharged four cylinder High Speed Direct Injection (HSDI) diesel engine which is coupled to a hydrostatic transient dynamometer. Emissions were measured from one exhaust port 5 cm downstream of the exhaust valve and from the exhaust pipe 14 cm below the wastegate of the turbocharger. These measurements were made with fast response HC and NOx measurement analyzers. The experiments were conducted by increasing torque at constant speed and by increasing speed at constant torque, in conventional diesel combustion regions. The emissions from the two locations are compared. The transient effects of Exhaust Gas Recirculation (EGR) rates and injection timing on HC and NOx are described and the effects of linear and step load change on emissions are compared.