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The goal of this research is to investigate the physical parameters of stoichiometric operation of a diesel engine under a light load operating condition (6∼7 bar IMEP). This paper focuses on improving the fuel efficiency of stoichiometric operation, for which a fuel consumption penalty relative to standard diesel combustion was found to be 7% from a previous study. The objective is to keep NOx and soot emissions at reasonable levels such that a 3-way catalyst and DPF can be used in an aftertreatment combination to meet 2010 emissions regulation. The effects of intake conditions and the use of group-hole injector nozzles (GHN) on fuel consumption of stoichiometric diesel operation were investigated. Throttled intake conditions exhibited about a 30% fuel penalty compared to the best fuel economy case of high boost/EGR intake conditions. The higher CO emissions of throttled intake cases lead to the poor fuel economy.

This study investigates the potential of controlling premixed charge compression ignition (PCCI and HCCI) combustion strategies by varying fuel reactivity. In-cylinder fuel blending using port fuel injection of gasoline and early cycle direct injection of diesel fuel was used for combustion phasing control at both high and low engine loads and was also effective to control the rate of pressure rise. The first part of the study used the KIVA-CHEMKIN code and a reduced primary reference fuel (PRF) mechanism to suggest optimized fuel blends and EGR combinations for HCCI operation at two engine loads (6 and 11 bar net IMEP). It was found that the minimum fuel consumption could not be achieved using either neat diesel fuel or neat gasoline alone, and that the optimal fuel reactivity required decreased with increasing load. For example, at 11 bar net IMEP, the optimum fuel blend and EGR rate for HCCI operation was found to be PRF 80 and 50%, respectively.

A novel 2-zone combustion chamber concept (patent pending) was developed using multi-dimensional modeling. At minimum volume, an axial projection in the piston divides the volume into distinct zones joined by a communication channel. The projection provides a means to control the mixture formation and combustion phasing within each zone. The novel combustion system was applied to reactivity controlled compression ignition (RCCI) combustion in both light-duty and heavy-duty diesel engines. Results from the study of an 8.8 bar BMEP, 2600 RPM operating condition are presented for the light-duty engine. The results from the heavy-duty engine are at an 18.1 bar BMEP, 1200 RPM operating condition. The effect of several major design features were investigated including the volume split between the inner and outer combustion chamber volumes, the clearance (squish) height, and the top ring land (crevice) volume.

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.

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.

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.

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.

A computational study was performed to evaluate the effects of bowl geometry, fuel spray targeting and swirl ratio under highly diluted, low-temperature combustion conditions in a heavy-duty diesel engine. This study is used to examine aspects of low-temperature combustion that are affected by mixing processes and offers insight into the effect these processes have on emissions formation and oxidation. The foundation for this exploratory study stems from a large data set which was generated using a genetic algorithm optimization methodology. The main results suggest that an optimal combination of spray targeting, swirl ratio and bowl geometry exist to simultaneously minimize emissions formation and improve soot and CO oxidation rates. Spray targeting was found to have a significant impact on the emissions and fuel consumption performance, and was furthermore found to be the most influential design parameter explored in this study.

Stoichiometric combustion could enable a three-way catalyst to be used for treating NOx emissions of diesel engines, which is one of the most difficult species for diesel engines to meet future emission regulations. Previous study by Lee et al. [1] showed that diesel engines can operate with stoichiometric combustion successfully with only a minor impact on fuel consumption. Low NOx emission levels were another advantage of stoichiometric operation according to that study. In this study, the characteristics of stoichiometric diesel combustion were evaluated experimentally to improve fuel economy as well as exhaust emissions The effects of fuel injection pressure, boost pressure, swirl, intake air temperature, combustion regime (injection timing), and engine load (fuel mass injected) were assessed under stoichiometric conditions.

A study of partially premixed combustion (PPC) with non-oxygenated 91 pump octane number1 (PON) commercially available gasoline was performed using a heavy-duty (HD) compression-ignition (CI) 2.44 l Caterpillar 3401E single-cylinder oil test engine (SCOTE). The experimental conditions selected were a net indicated mean effective pressure (IMEP) of 11.5 bar, an engine speed of 1300 rev/min, an intake temperature of 40°C with intake and exhaust pressures of 200 and 207 kPa, respectively. The baseline case for all studies presented had 0% exhaust gas recirculation (EGR), used a dual injection strategy a -137 deg ATDC pilot SOI and a -6 deg ATDC main start-of-injection (SOI) timing with a 30/70% pilot/main fuel split for a total of 5.3 kg/h fueling (equating to approximately 50% load). Combustion and emissions characteristics were explored relative to the baseline case by sweeping main and pilot SOI timings, injection split fuel percentage, intake pressure, load and EGR levels.

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 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 present work proposes a methodology for diesel engine development using multi-dimensional CFD and computer optimization. A multi-objective genetic algorithm coupled with the KIVA3V Release 2 code was used to optimize a high speed direct injection (HSDI) diesel engine for passenger car applications. The simulations were conducted using high-throughput computing with the CONDOR system. An automated grid generator was used for efficient mesh generation with 11 variable piston bowl geometry parameters. The first step in the procedure was to search for an optimal nozzle and piston bowl design. In this case, spray targeting, swirl ratio, and piston bowl shape were optimized separately for two full-load cases using simpler efficient combustion models (the characteristic time scale model and the shell ignition model). The optimal designs from the two optimizations were then validated using a combustion model with detailed chemistry (KIVA-CHEMKIN model and ERC n-heptane mechanism).

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.

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 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.

Engine experiments and multi-dimensional modeling were used to explore Reactivity Controlled Compression Ignition (RCCI) to realize highly-efficient combustion with near zero levels of NOx and PM. In-cylinder fuel blending using port-fuel-injection of a low reactivity fuel and optimized direct-injection of higher reactivity fuels was used to control combustion phasing and duration. In addition to injection and operating parameters, the study explored the effect of fuel properties by considering both gasoline-diesel dual-fuel operation, ethanol (E85)-diesel dual fuel operation, and a single fuel gasoline-gasoline+DTBP (di-tert butyl peroxide cetane improver). Remarkably, high gross indicated thermal efficiencies were achieved, reaching 59%, 56%, and 57% for E85-diesel, gasoline-diesel, and gasoline-gasoline+DTBP respectively.

In automotive industry it has been a challenge to retain diesel-like thermal efficiency while maintaining low emissions. Numerous studies have shown significant progress in achieving low emissions through the introduction of common-rail injection systems, multiple injections and exhaust gas recirculation and by using a high octane number fuel, like gasoline, to achieve adequate premixing. On the other hand, low temperature combustion strategies, like HCCI and PCCI, have also shown promising results in terms of reducing both NOx and soot emissions simultaneously. With the increasing capacity of computers, multi-dimensional CFD engine modeling enables a reasonably good prediction of combustion characteristics and pollutant emissions, which is the motivation behind the present research. The current research effort presents an optimization study of light-duty compression ignition engine performance, while meeting the emission regulation targets.

A comprehensive biodiesel combustion model is presented for use in multi-dimensional engine simulations. The model incorporates realistic physical properties in a vaporization model developed for multi-component fuel sprays and applies an improved mechanism for biodiesel combustion chemistry. Previously, a detailed mechanism for methyl decanoate and methyl-9-decenoate was reduced from 3299 species to 85 species to represent the components of biodiesel fuel. In this work, a second reduction was performed to further reduce the mechanism to 69 species. Steady and unsteady spray simulations confirmed that the model adequately reproduced liquid penetration observed in biodiesel spray experiments. Additionally, the new model was able to capture expected fuel composition effects with low-volatility components and fuel blend sprays penetrating further.