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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.

This study investigates the potential of controlling premixed charge compression ignition (PCCI) 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 a medium engine load of 9 bar net IMEP and was also found to be effective to prevent excessive rates of pressure rise. Parameters used in the experiments were guided from the KIVA-CHEMKIN code with a reduced primary reference fuel (PRF) mechanism including injection timings, fuel percentages, and intake valve closing (IVC) timings for dual-fuel PCCI combustion. The engine experiments were conducted with a conventional common rail injector (i.e., wide angle and large nozzle hole) and demonstrated control and versatility of dual-fuel PCCI combustion with the proper fuel blend, SOI and IVC timings.

The ignition process of fuel reactivity controlled PCCI combustion was investigated using engine experiments and detailed CFD modeling. The experiments were performed using a modified all metal heavy-duty, compression-ignition engine. The engine was fueled using commercially available gasoline (PON 91.6) and ULSD diesel delivered through separate port and direct injection systems, respectively. Experiments were conducted at a steady state-engine load of 4.5 bar IMEP and speed of 1300 rev/min. In-cylinder optical measurements focused on understanding the fuel decomposition and fuel reactivity stratification provided through the charge preparation. The measurement technique utilized point location optical access through a modified cylinder head with two access points in the firedeck. Optical measurements of natural thermal emission were performed with an FTIR operating in the 2-4.5 μm spectral region.

The present experimental engine efficiency study explores the effects of intake pressure and temperature, and premixed and global equivalence ratios on gross thermal efficiency (GTE) using the reactivity controlled compression ignition (RCCI) combustion strategy. Experiments were conducted in a heavy-duty single-cylinder engine at constant net load (IMEPn) of 8.45 bar, 1300 rev/min engine speed, with 0% EGR, and a 50% mass fraction burned combustion phasing (CA50) of 0.5°CA ATDC. The engine was port fueled with E85 for the low reactivity fuel and direct injected with 3.5% 2-ethylhexyl nitrate (EHN) doped into 91 anti-knock index (AKI) gasoline for the high-reactivity fuel. The resulting reactivity of the enhanced fuel corresponds to an AKI of approximately 56 and a cetane number of approximately 28. The engine was operated with a wide range of intake pressures and temperatures, and the ratio of low- to high-reactivity fuel was adjusted to maintain a fixed speed-phasing-load condition.

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as local, globally lean, low-temperature combustion strategies are setting the path towards a more efficient and environmentally sustainable use of energy resources in transportation. In this paper, we assessed the computational efficiency of a recently developed sparse analytical Jacobian chemistry solver, namely ‘SpeedCHEM’, that features both direct and Krylov-subspace solution methods for maximum efficiency for both small and large mechanism sizes. The code was coupled with a high-dimensional clustering algorithm for grouping homogeneous reactors into clusters with similar states and reactivities, to speed-up the chemical kinetics solution in multi-dimensional combustion simulations.

One in-cylinder strategy for reducing soot emissions from diesel engines while maintaining fuel efficiency is the use of close-coupled post injections, which are small fuel injections that follow the main fuel injection after a short delay. While the in-cylinder mechanisms of diesel combustion with single injections have been studied extensively and are relatively well understood, the in-cylinder mechanisms affecting the performance and efficacy of post injections have not been clearly established. Here, experiments from a single-cylinder heavy-duty optical research engine incorporating close- coupled post injections are modeled with three dimensional (3D) computational fluid dynamics (CFD) simulations. The overall goal is to complement experimental findings with CFD results to gain more insight into the relationship between post-injections and soot. This paper documents the first stage of CFD results for simulating and analyzing the experimental conditions.

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 multi-objective genetic algorithm coupled with the KIVA3V release 2 code was used to optimize the piston bowl geometry, spray targeting, and swirl ratio levels of a high speed direct injected (HSDI) diesel engine for passenger cars. Three modes, which represent full-, mid-, and low-loads, were optimized separately. A non-dominated sorting genetic algorithm II (NSGA II) was used for the optimization. High throughput computing was conducted using the CONDOR software. An automated grid generator was used for efficient mesh generation with variable geometry parameters, including open and reentrant bowl designs. A series of new spray models featuring reduced mesh dependency were also integrated into the code. A characteristic-time combustion (CTC) model was used for the initial optimization for time savings. Model validation was performed by comparison with experiments for the baseline engine at full-, mid-, and low-load operating conditions.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline (termed GDICI for Gasoline Direct-Injection Compression Ignition) in the low temperature combustion (LTC) regime is presented. As an aid to plan engine experiments at full load (16 bar IMEP, 2500 rev/min), exploration of operating conditions was first performed numerically employing a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion. Operation ranges of a light-duty diesel engine operating with GDICI combustion with constraints of combustion efficiency, noise level (pressure rise rate) and emissions were identified as functions of injection timings, exhaust gas recirculation rate and the fuel split ratio of double-pulse injections.

In this study we identify components of a typical biodiesel fuel and estimate both their individual and mixed thermo-physical and transport properties. We then use the estimated mixture properties in computational simulations to gauge the extent to which combustion is modified when biodiesel is substituted for conventional diesel fuel. Our simulation studies included both conventional diesel combustion (DI) and premixed charge compression ignition (PCCI). Preliminary results indicate that biodiesel ignition is significantly delayed due to slower liquid evaporation, with the effects being more pronounced for DI than PCCI. The lower vapor pressure and higher liquid heat capacity of biodiesel are two key contributors to this slower rate of evaporation. Other physical properties are more similar between the two fuels, and their impacts are not clearly evident in the present study.

Homogeneous or partially premixed charge compression ignition combustion is considered to be an attractive alternative to traditional internal combustion engine operation because of its extremely low levels of pollutant emissions. However, since it is difficult to control the start of combustion timing, direct injection of fuel into the combustion chamber is often used for combustion phasing control, as well as charge preparation. In this paper, numerical simulations of compression ignition processes using gasoline fuel directly injected using a low pressure, hollow cone injector are presented. The multi-dimensional CFD code, KIVA3V, that incorporates various advanced sub-models and is coupled with CHEMKIN for modeling detailed chemistry, was used for the study. Simulation results of the spray behavior at various injection conditions were validated with available experimental data.

Parametric tests using various EGR amounts, boost intake pressures, fueling rates, intake valve closings (IVC), injection pressures, and start-of-injection timings were executed to explore the limitations and potential of an intake valve actuation system on a heavy-duty diesel engine. At high-speed, intermediate load (56%) operation, constant airflow and no EGR, the use of late intake valve closing enabled a 70% NOx reduction while maintaining PM levels. Through an investigation using low load operation, late IVC, and reduced intake pressure, 2010 not-to-exceed NOx and PM emissions (0.25 g/kW-hr NOx, 0.02 g/kW-hr PM) were achieved with 40% EGR. At medium load, constant air flow, and early SOI, it was found that the NOx, HC and BSFC levels at a late IVC with 30%EGR were comparable to those with the stock camshaft IVC timing of 143°BTDC with 40%EGR. In comparison, the CO and PM levels decreased by nearly 70% with the use of late IVC timing and less EGR.

Hydraulically intensified medium pressure common rail (MPCR) electronic fuel injection systems are an attractive concept for heavy-duty diesel engine applications. They offer excellent packaging flexibility and thorough engine management system integration. Two different concepts were evaluated in this study. They are different in how the pressure generation and injection events are related. One used a direct principle, where the high-pressure generation and injection events occur simultaneously producing a near square injection rate profile. Another concept was based on an indirect principle, where potential energy (pressure) is first stored inside a hydraulic accumulator, and then released during injection, as a subsequent event. A falling rate shape is typically produced in this case. A unit pump, where the hydraulic intensifier is separated from the injector by a high-pressure line, and a unit injector design are considered for both concepts.

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.

An experimental study was conducted on an air cooled high-speed, direct-injection diesel generator that investigated the use of gasoline in a dual fuel PCCI strategy. The single-speed generator used in the study has an effective compression ratio of 17 and runs at 3600 rev/min. Varying amounts of gasoline were introduced into the combustion chamber through a port injection system. The generator uses an all-mechanical diesel fuel injection system that has a fixed injection timing. The experiments explored variable intake temperatures and fuel split quantities to investigate different combustion phasing regimes. Results from the study showed low combustion efficiency at low load. Low load operation was also characterized by high levels of HC and CO (in excess of 20 g/kwh and 50 g/kwh respectively). Operation at 75% load was more efficient, and displayed three different combustion regimes that are possible with PIG (port injected gasoline) dual fuel PCCI.

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.

This study explores an Adaptive Injection Strategy (AIS) that employs multiple injections at both low and high pressures to reduce spray-wall impingement, control combustion phasing, and limit pressure rise rates in a Premixed Compression Ignition (PCI) engine. Previous computational studies have shown that reducing the injection pressure of early injections can prevent spray-wall impingement caused by long liquid penetration lengths. This research focuses on understanding the performance and emissions benefits of low and high pressure split injections through experimental parametric sweeps of a 0.48 L single-cylinder test engine operating at 2000 rev/min and 5.5 bar nominal IMEP. This study examines the effects of 2nd injection pressure, EGR, swirl ratio, and 1st and 2nd injection timing, for both single heat release and two-peak high temperature heat release cases. In order to investigate the AIS concept experimentally, a Variable Injection Pressure (VIP) system was developed.

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).

Detailed knowledge of hydrocarbon fuel combustion chemistry has grown tremendously in recent years. However, the gap between detailed chemistry and computational fluid dynamics (CFD) remains, because of the high cost of solving detailed chemistry in a large number of computational cells. This paper presents the results of applying a suite of techniques aimed at closing this gap. The techniques include use of a surrogate blend optimizer and a guided mechanism reduction methodology, as well as advanced methods for efficiently and accurately coupling the pre-reduced kinetic models with the multidimensional transport equations. The advanced methods include dynamic adaptive chemistry (DAC) and dynamic cell clustering (DCC) algorithms.