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Although in-cylinder optical diagnostics have provided significant understanding of conventional diesel combustion, most alternative combustion strategies have not yet been explored to the same extent. In an effort to build the knowledge base for alternative low-temperature combustion strategies, this paper presents a comparison of three alternative low-temperature combustion strategies to two high-temperature conventional diesel combustion conditions. The baseline conditions, representative of conventional high-temperature diesel combustion, have either a short or a long ignition delay. The other three conditions are representative of some alternative combustion strategies, employing significant charge-gas dilution along with either early or late fuel injection, or a combination of both (double-injection).

Manufacturers of heavy-duty diesel engines are facing increasingly stringent, emission standards. These standards have motivated new research efforts towards improving the performance of diesel engines. The objective of the present program is to develop a comprehensive analytical model of the diesel combustion process that can be used to explore the influence of design changes. This will enable industry to predict the effect of these changes on engine performance and emissions. A major benefit of the successful implementation of such models is that engine development time and costs would be reduced through their use. The computer model is based on the three-dimensional KIVA-II code, with state-of-the-art submodels for spray atomization, drop breakup / coalescence, multi-component fuel vaporization, spray/wall interaction, ignition and combustion, wall heat transfer, unburned HC and NOx formation, and soot and radiation.

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.

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.

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 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.

In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.

We propose a novel dual-fuel combustion model for simulating heavy-duty engines with the G-Equation. Dual-Fuel combustion strategies in such engines features direct injection of a high-reactivity fuel into a lean, premixed chamber which has a high resistance to autoignition. Distinct combustion modes are present: the DI fuel auto-ignites following chemical ignition delay after spray vaporization and mixing; a reactive front is formed on its surroundings; it develops into a well-structured turbulent flame, which propagates within the premixed charge. Either direct chemistry or the flame-propagation approach (G- Equation), taken alone, do not produce accurate results. The proposed Dual-Fuel model decides what regions of the combustion chamber should be simulated with either approach, according to the local flame state; and acts as a “kernel” model for the G- Equation model. Direct chemistry is run in the regions where a premixed front is not present.

A droplet vaporization model has been developed for use in high pressure spray modeling. The model is a modification of the common Spalding vaporization model that accounts for the effects of high pressure on phase equilibrium, transport properties, and surface tension. The new model allows for a nonuniform temperature within the liquid by using a simple 2-zone model for the droplet. The effects of the different modifications are tested both for the case of a single vaporizing droplet in a quiescent environment as well as for a high pressure spray using the KIVA II code. Comparisons with vaporizing spray experiments show somewhat improved spray penetration predictions. Also, the effect of the vaporization model on diesel combustion predictions was studied by applying the models to simulate the combustion process in a heavy duty diesel engine. In this case the standard and High Pressure vaporization models were found to give similar heat release and emissions results.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

The physical in-cylinder processes and ignition during cold starting have been studied using computational models, with particular attention to the influences of blowby, heat transfer during the compression stroke, spray development, vaporization and fuel/air mixture formation and ignition. Two different modeling approaches were used. A thermodynamic zero dimensional cycle analysis program in which the fuel injection effects were not modeled, was used to determine overall and gas exchange effects. The three-dimensional KIVA-II code was used to determine details of the closed cycle events, with modified atomization, blowby and spray/wall impingement models, and a simplified model for ignition. The calculations were used to obtain an understanding of the cold starting process and to identify practical methods for improving cold starting of direct injection diesel engines.

Experiments were performed on a single-cylinder heavy-duty Caterpillar SCOTE 3401E engine at high speed (1737 rev/min) and loads up to 60% of full load for fully Premixed Charge Compression Ignition (PCCI) combustion. The engine was equipped with a high pressure (150 MPa) Caterpillar 300B HEUI fuel injection system. The engine was run with EGR levels up to 75% and with equivalence ratios up to 0.95. These experiments resulted in compliance of NOx and PM emissions to 2010 emissions mandates levels up to the tested load. The set of experiments also demonstrated the importance of cylinder charge preparation by way of optimized start-of-combustion timing for sufficient in-cylinder mixing. It was found that increased EGR rates, even with the correspondingly increased equivalence ratios, increase mixing time and substantially decrease PM emissions.

Real transportation fuels, such as gasoline and diesel, are mixtures of thousands of different hydrocarbons. For multidimensional engine applications, numerical simulations of combustion of real fuels with all of the hydrocarbon species included exceeds present computational capabilities. Consequently, surrogate fuel models are normally utilized. A good surrogate fuel model should approximate the essential physical and chemical properties of the real fuel. In this work, we present a novel methodology for the formulation of surrogate fuel models based on local optimization and sensitivity analysis technologies. Within the proposed approach, several important fuel properties are considered. Under the physical properties, we focus on volatility, density, lower heating value (LHV), and viscosity, while the chemical properties relate to the chemical composition, hydrogen to carbon (H/C) ratio, and ignition behavior. An error tolerance is assigned to each property for convergence checking.

A transport equation residual model incorporating refined G-equation and detailed chemical kinetics combustion models has been developed and implemented in the ERC KIVA-3V release2 code for Gasoline Direct Injection (GDI) engine simulations for better predictions of flame propagation. In the transport equation residual model a fictitious species concept is introduced to account for the residual gases in the cylinder, which have a great effect on the laminar flame speed. The residual gases include CO2, H2O and N2 remaining from the previous engine cycle or introduced using EGR. This pseudo species is described by a transport equation. The transport equation residual model differentiates between CO2 and H2O from the previous engine cycle or EGR and that which is from the combustion products of the current engine cycle.

Homogeneous low temperature combustion is believed to be a promising approach to resolve the conflict of goals between high efficiency and low exhaust emissions. Disadvantageously for this kind of combustion, the whole process depends on chemical kinetics and thus is hard to control. Reactivity controlled combustion can help to overcome this difficulty. In the so-called RCCI (reactivity controlled compression ignition) combustion concept a small amount of pilot diesel that is injected directly into the combustion chamber ignites a highly diluted gasoline-air mixture. As the gasoline does not ignite without the diesel, the pilot injection timing and the ratio between diesel and gasoline can be used to control the combustion process. A phenomenological multi-zone model to predict RCCI combustion has been developed and validated against experimental and 3D-CFD data. The model captures the main physics governing ignition and combustion.

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 simulation of combustion chemistry in internal combustion engines is challenging due to the need to include detailed reaction mechanisms to describe the engine physics. Computational times needed for coupling full chemistry to CFD simulations are still too computationally demanding, even when distributed computer systems are exploited. For these reasons the present paper proposes a time scale separation approach for the integration of the chemistry differential equations and applies it in an engine CFD code. The time scale separation is achieved through the estimation of a characteristic time for each of the species and the introduction of a sampling timestep, wherein the chemistry is subcycled during the overall integration. This allows explicit integration of the system to be carried out, and the step size is governed by tolerance requirements.

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.

Simultaneous measurements of the radial and the tangential components of velocity are obtained in a high-speed, direct-injection diesel engine typical of automotive applications. Results are presented for engine operation with fuel injection, but without combustion, for three different swirl ratios and four injection pressures. With the mean and fluctuating velocities, the r-θ plane shear stress and the mean flow gradients are obtained. Longitudinal and transverse length scales are also estimated via Taylor's hypothesis. The flow is shown to be sufficiently homogeneous and stationary to obtain meaningful length scale estimates. Concurrently, the flow and injection processes are simulated with KIVA-3V employing a RNG k-ε turbulence model. The measured turbulent kinetic energy k, r-θ plane mean strain rates ( 〈Srθ〉, 〈Srr〉, and 〈Sθθ〉 ), deviatoric turbulent stresses , and the r-θ plane turbulence production terms are compared directly to the simulated results.

With recent increases in global fuel prices there has become a growing interest in expanding the use of diesel engines in the transportation industry. However, new engine development is costly and time intensive, requiring many hours of expensive engine tests. The ability to accurately predict an engine's performance based on existing models would reduce the expense involved in creating a new engine of different size. In the present study experimental results from two single-cylinder direct injection diesel engines were used to examine previously developed engine scaling models. The first scaling model was based on an equal spray penetration correlation. The second model considered both equal spray penetration and flame lift-off length. The engines used were a heavy-duty Caterpillar engine with a 2.44L displacement and a light-duty GM engine with a 0.48L displacement.