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Resolution of droplet-scale processes occurring within engine sprays in multi-dimensional Computational Fluid Dynamics (CFD) simulations is not possible because impractically refined numerical meshes or time steps would be required. As a result, simulations that use coarse meshes and large time steps suffer from inaccurate predictions of mass, momentum and energy transfer between the spray drops and the combustion chamber gas, or poor prediction of droplet breakup and collision and coalescence processes. Several new spray models have been proposed to address these deficiencies, including use of an unsteady gas jet model to improve momentum transfer predictions in under-resolved regions of the spray, a vapor particle model to minimize numerical diffusion effects, and a Radius of Influence drop collision model to ensure consistent collision computations on different meshes.

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.

Reactivity-controlled compression ignition (RCCI) has been shown to be capable of providing improved engine efficiencies coupled with the benefit of low emissions via in-cylinder fuel blending. Much of the previous body of work has studied the benefits of RCCI operation using high injection pressures (e.g., 500 bar or greater) with common rail injection (CRI) hardware. However, low-pressure fueling technology is capable of providing significant cost savings. Due to the broad market adoption of gasoline direct injection (GDI) fueling systems, a market-type prototype GDI injector was selected for this study. Single-cylinder light-duty engine experiments were undertaken to examine the performance and emissions characteristics of the RCCI combustion strategy with low-pressure GDI technology and compared against high injection pressure RCCI operation. Gasoline and diesel were used as the low-reactivity and high-reactivity fuels, respectively.

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.

Reactivity Controlled Compression Ignition (RCCI) is an engine combustion strategy that utilizes in-cylinder fuel blending to produce low NOx and PM emissions while maintaining high thermal efficiency. The current study investigates RCCI and conventional diesel combustion (CDC) operation in a light-duty multi-cylinder engine over transient operating conditions using a high-bandwidth, transient capable engine test cell. Transient RCCI and CDC combustion and emissions results are compared over an up-speed change from 1,000 to 2,000 rev/min. and a down-speed change from 2,000 to 1,000 rev/min. at a constant 2.0 bar BMEP load. The engine experiments consisted of in-cylinder fuel blending with port fuel-injection (PFI) of gasoline and early-cycle, direct-injection (DI) of ultra-low sulfur diesel (ULSD) for the RCCI tests and the same ULSD for the CDC tests.

Reactivity Controlled Compression Ignition (RCCI) is an engine combustion strategy that utilizes in-cylinder fuel blending to produce low NOx and PM emissions, while maintaining high thermal efficiency. Previous RCCI steady-state performance studies provided a fundamental understanding of the RCCI combustion process in steady-state, single-cylinder and multi-cylinder engine tests. The current study investigates RCCI and conventional diesel combustion (CDC) operation in a light-duty multi-cylinder engine over transient operating conditions. In this study, a high-bandwidth, transient-capable engine test cell was used and multi-cylinder engine RCCI combustion is compared to CDC over a step load change from 1 to 4 bar BMEP at 1,500 rev/min. The engine experiments consisted of in-cylinder fuel blending using port fuel-injection (PFI) of gasoline and early-cycle, direct-injection (DI) of ultra-low sulfur diesel (ULSD) for the RCCI tests and used the same ULSD for the CDC tests.

Reactivity Controlled Compression Ignition (RCCI) has been shown to be an attractive concept to achieve clean and high efficiency combustion. RCCI can be realized by applying two fuels with different reactivities, e.g., diesel and gasoline. This motivates the idea of using a single low reactivity fuel and direct injection (DI) of the same fuel blended with a small amount of cetane improver to achieve RCCI combustion. In the current study, numerical investigation was conducted to simulate RCCI and HCCI combustion and emissions with various fuels, including gasoline/diesel, iso-butanol/diesel and iso-butanol/iso-butanol+di-tert-butyl peroxide (DTBP) cetane improver. A reduced Primary Reference Fuel (PRF)-iso-butanol-DTBP mechanism was formulated and coupled with the KIVA computational fluid dynamic (CFD) code to predict the combustion and emissions of these fuels under different operating conditions in a heavy duty diesel engine.

This paper is part of a larger body of experimental and computational work devoted to studying the role of close-coupled post injections on soot reduction in a heavy-duty optical engine. It is a continuation of an earlier computational paper. The goals of the current work are to develop new CFD analysis tools and methods and apply them to gain a more in depth understanding of the different in-cylinder environments into which fuel from main- and post-injections are injected and to study how the in-cylinder flow, thermal and chemical fields are transformed between start of injection timings. The engine represented in this computational study is a single-cylinder, direct-injection, heavy-duty, low-swirl engine with optical components. It is based on the Cummins N14, has a cylindrical shaped piston bowl and an eight-hole injector that are both centered on the cylinder axis. The fuel used was n-heptane and the engine operating condition was light load at 1200 RPM.

Due to the upcoming regulations for particulate matter (PM) emissions from GDI engines, a computational fluid dynamic (CFD) modeling study to predict soot emissions (both mass and solid particle number) from gasoline direct injection (GDI) engines was undertaken to provide insights on how and why soot emissions are formed from GDI engines. In this way, better methods may be developed to control or reduce PM emissions from GDI engines. In this paper, the influence of engine operating parameters was examined for a side-mounted fuel injector configuration in a direct-injection spark-ignition (DISI) engine. The present models are able to reasonably predict the influences of the variables of interest compared to available experimental data or literature. For a late injection strategy, effects of the fuel composition, and spray cone angle were investigated with a single-hole injector.

Homogeneous Charge Compression Ignition (HCCI) has been shown as a promising technique for simultaneous NOx and soot reduction while maintaining diesel-like efficiency. Although HCCI has been shown to yield very low emissions levels, spray-wall impingement and high pressure rise rates can be problematic due to the early injection timings necessary for certain HCCI operations. To address spray-wall impingement, an Adaptive Injection Strategy (AIS) was employed. This strategy uses multiple pulses at both low and high injection pressures to prepare an optimal in-cylinder mixture. A unique Variable Pressure Pulse (VPP) was developed to investigate the AIS concept experimentally. The VPP has the capability of delivering multiple injections at both low and high injection pressures (∼100 bar and ∼1000 bar respectively) through a single injector in the same engine cycle. Comparisons were made between model predictions and engine experiments using the VPP system.

A computational study using multi-dimensional CFD modeling was performed to investigate the effects of physical properties on diesel engine combustion characteristics with bio-diesel fuels. Properties of typical bio-diesel fuels that were either calculated or measured are used in the study and the simulation results are compared with those of conventional diesel fuels. The sensitivity of the computational results to individual physical properties is also investigated, and the results provide information about the desirable characteristics of the blended fuels. The properties considered in the study include liquid density, vapor pressure, surface tension, liquid viscosity, liquid thermal conductivity, liquid specific heat, latent heat, vapor specific heat, vapor diffusion coefficient, vapor viscosity and vapor thermal conductivity. The results show significant effects of the fuel physical properties on ignition delay and burning rates at various engine operating conditions.

In-cylinder flow and combustion processes simulated with the standard k-ε turbulence model and with an alternative model-employing a non-linear, quadratic equation for the turbulent stresses-are contrasted for both motored and fired engine operation at two loads. For motored operation, the differences observed in the predictions of mean flow development are small and do not emerge until expansion. Larger differences are found in the spatial distribution and magnitude of turbulent kinetic energy. The non-linear model generally predicts lower energy levels and larger turbulent time scales. With fuel injection and combustion, significant differences in flow structure and in the spatial distribution of soot are predicted by the two models. The models also predict considerably different combustion efficiencies and NOx emissions.

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.

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.

Single-cylinder engine experiments were used to investigate a fuel reactivity controlled compression ignition (RCCI) concept in both light- and heavy-duty engines and comparisons were made between the two engine classes. It was found that with only small changes in the injection parameters, the combustion characteristics of the heavy-duty engine could be adequately reproduced in the light-duty engine. Comparisons of the emissions and performance showed that both engines can simultaneously achieve NOx below 0.05 g/kW-hr, soot below 0.01 g/kW-hr, ringing intensity below 4 MW/m2, and gross indicated efficiencies above 50 per cent. However, it was found that the peak gross indicated efficiency of the baseline light-duty engine was approximately 7 per cent lower than the heavy-duty engine. The energy balances of the two engines were compared and it was found that the largest factor contributing to the lower efficiency of the light-duty engine was increased heat transfer losses.

A multi-component fuel model is used to represent gasoline in computational fluid dynamics (CFD) simulations of a dual-fuel engine that combines premixed gasoline injection with diesel direct injection. The simulations employ detailed-kinetics mechanisms for both the gasoline and diesel surrogate fuels, through use of an advanced and efficient chemistry solver. The objective of this work is to elucidate kinetics effects of dual-fuel usage in Reactivity Controlled Compression Ignition (RCCI) combustion. The model is applied to simulate recent experiments on highly efficient RCCI engines. These engine experiments used a dual-fuel RCCI strategy with port-fuel-injection of gasoline and early-cycle, multiple injections of diesel fuel with a conventional diesel injector. The experiments showed that the US 2010 heavy-duty NO and soot emissions regulations were easily met without aftertreatment, while achieving greater than 50% net indicated thermal efficiency.

In a recent experimental study the in-cylinder spatial distribution of mixture equivalence ratio was quantified under non-combusting conditions by planar laser-induced fluorescence (PLIF) of a fuel tracer (toluene). The measurements were made in a single-cylinder, direct-injection, light-duty diesel engine at conditions matched to an early-injection low-temperature combustion mode. A fuel amount corresponding to a low load (3.0 bar indicated mean effective pressure) operating condition was introduced with a single injection at -23.6° ATDC. The data were acquired during the mixture preparation period from near the start of injection (-22.5° ATDC) until the crank angle where the start of high-temperature heat release normally occurs (-5° ATDC). In the present study the measured in-cylinder images are compared with a fully resolved three-dimensional CFD model, namely KIVA3V-RANS simulations.