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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.

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.

Gasoline Direct Injection (GDI) fuel injectors are fouled when carbon deposits build-up on the injector tip, impeding fuel droplet atomization and dispersion. These issues, if left untreated, can lead to losses in engine power and fuel economy, as well as increased emissions of particulate matter (PM). Bottled aftermarket gasoline detergents are commonly used to remove deposits and restore injector performance. A performance analysis of three classes of bottled gasoline additives was performed, focusing on products that do not contain nitrogen-based detergents; products containing nitrogen-based detergents; and a new class of gasoline detergent formulations designed specifically for GDI injector fouling.

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.

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.

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 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 application of close-coupled post injections in diesel engines has been proven to be an effective in-cylinder strategy for soot reduction, without much fuel efficiency penalty. But due to the complexity of in-cylinder combustion, the soot reduction mechanism of post-injections is difficult to explain. Accordingly, a simulation study using a three dimensional computational fluid dynamics (CFD) model, coupled with the SpeedChem chemistry solver and a semi-detailed soot model, was carried out to investigate post-injection in a constant volume combustion chamber, which is more simple and controllable with respect to the boundary conditions than an engine. A 2-D axisymmetric mesh of radius 2 cm and height 5 cm was used to model the spray. Post-injection durations and initial oxygen concentrations were swept to study the efficacy of post-injection under different combustion conditions.

Vaporization models for continuous multi-component liquid sprays and liquid wall films are presented using a continuous thermodynamics formulation. The models were implemented in the KIVA3V-Release 2.0 code. The models are first applied to clarify the characteristics of vaporizing continuous multi-component liquid wall films and liquid drops, and then applied to numerically analyze a practical continuous multi-component fuel - gasoline behavior in a 4-valve port fuel injection (PFI) gasoline engine under warm conditions. Corresponding computations with single-component fuels are also performed and presented for comparison purposes. As compared to the results of its single-component counterpart, the vaporizing continuous multi-component fuel drop displays a larger vaporization rate initially and a smaller vaporization rate as it becomes more and more dominated by heavy species.

While Low Temperature Combustion (LTC) strategies such as Reactivity Controlled Compression Ignition (RCCI) exhibit high thermal efficiency and produce low NOx and soot emissions, low load operation is still a significant challenge due to high unburnt hydrocarbon (UHC) and carbon monoxide (CO) emissions, which occur as a result of poor combustion efficiencies at these operating points. Furthermore, the exhaust gas temperatures are insufficient to light-off the Diesel Oxidation Catalyst (DOC), thereby resulting in poor UHC and CO conversion efficiencies by the aftertreatment system. To achieve exhaust gas temperature values sufficient for DOC light-off, combustion can be appropriately phased by changing the ratio of gasoline to diesel in the cylinder, or by burning additional fuel injected during the expansion stroke through post-injection.

A modification of the computational fluid dynamics code KIVA-II is presented that allows computations to be made in complex engine geometries. An example application is given in which three versions of KIVA-II are run simultaneously. Each version considers a separate block of the computational domain, and the blocks exchange boundary condition information with each other at their common interfaces. The use of separate blocks permits the connectedness of the overall computational domain to change with time. The scavenging flow in the cylinder, transfer pipes (ports), and exhaust pipe of a ported two-stroke engine with a moving piston was modeled in this way. Results are presented for three engine designs that differ only in the angle of their boost ports. The calculated flow fields and the resulting fuel distributions are shown to be markedly different with the different geometries.

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.

Multidimensional modeling is used to study air-fuel mixing in a direct-injection spark-ignition engine. Emphasis is placed on the effects of the start of fuel injection on gas/spray interactions, wall wetting, fuel vaporization rate and air-fuel ratio distributions in this paper. It was found that the in-cylinder gas/spray interactions vary with fuel injection timing which directly impacts spray characteristics such as tip penetration and spray/wall impingement and air-fuel mixing. It was also found that, compared with a non-spray case, the mixture temperature at the end of the compression stroke decreases substantially in spray cases due to in-cylinder fuel vaporization. The computed trapped-mass and total heat-gain from the cylinder walls during the induction and compression processes were also shown to be increased in spray cases.

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.

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 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.

The light-medium load operating range (4-7 bar net IMEP) presents many challenges for advanced low temperature combustion strategies utilizing low cetane fuels (specifically, 87-octane gasoline) in light-duty, high-speed engines. The overly lean overall air-fuel ratio (Φ≺0.4) sometimes requires unrealistically high inlet temperatures and/or high inlet boost conditions to initiate autoignition at engine speeds in excess of 1500 RPM. The objective of this work is to identify and quantify the effects of variation in input parameters on overall engine operation. Input parameters including inlet temperature, inlet pressure, injection timing/duration, injection pressure, and engine speed were varied in a ~0.5L single-cylinder engine based on a production General Motors 1.9L 4-cylinder high-speed diesel engine.

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.

In the current work, a series-hybrid vehicle has been constructed that utilizes a dual-fuel, Reactivity Controlled Compression Ignition (RCCI) engine. The vehicle is a 2009 Saturn Vue chassis and a 1.9L turbo-diesel engine converted to operate with low temperature RCCI combustion. The engine is coupled to a 90 kW AC motor, acting as an electrical generator to charge a 14.1 kW-hr lithium-ion traction battery pack, which powers the rear wheels by a 75 kW drive motor. Full vehicle testing was conducted on chassis dynamometers at the Vehicle Emissions Research Laboratory at Ford Motor Company and at the Vehicle Research Laboratory at Oak Ridge National Laboratory. For this work, the US Environmental Protection Agency Highway Fuel Economy Test was performed using commercially available gasoline and ultra-low sulfur diesel. Fuel economy and emissions data were recorded over the specified test cycle and calculated based on the fuel properties and the high-voltage battery energy usage.

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.