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A kinetic carbon monoxide (CO) emission model is developed to simulate engine out CO emissions for conventional diesel combustion. The model also incorporates physics governing CO emissions for low temperature combustion (LTC). The emission model will be used in an integrated system level model to simulate the operation and interaction of conventional and low temperature diesel combustion with aftertreatment devices. The Integrated System Model consists of component models for the diesel engine, engine-out emissions (such as NOx and Particulate Matter), and aftertreatment devices (such as DOC and DPF). The addition of CO emissions model will enhance the capability of the Integrated System Model to predict major emission species, especially for low temperature combustion. In this work a CO emission model is developed based on a two-step global kinetic mechanism [8].

Two different types of mesh used for diesel combustion with the KIVA-4 code are compared. One is a well established conventional KIVA-3 type polar mesh. The other is a non-polar mesh with uniform size throughout the piston bowl so as to reduce the number of cells and to improve the quality of the cell shapes around the cylinder axis which can contain many fuel droplets that affect prediction accuracy and the computational time. This mesh is specialized for the KIVA-4 code which employs an unstructured mesh. To prevent dramatic changes in spray penetration caused by the difference in cell size between the two types of mesh, a recently developed spray model which reduces mesh dependency of the droplet behavior has been implemented. For the ignition and combustion models, the Shell model and characteristic time combustion (CTC) model are employed.

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.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode.

Past experimental studies conducted by the current authors on a 13 liter 16.7:1 compression ratio heavy-duty diesel engine have shown that diesel-Compressed Natural Gas (CNG) Reactivity Controlled Compression Ignition (RCCI) combustion targeting low NOx emissions becomes progressively difficult to control as the engine load is increased. This is mainly due to difficulty in controlling reactivity levels at higher loads. For the current study, CFD investigations were conducted in CONVERGE using the SAGE combustion solver with the application of the Rahimi mechanism. Studies were conducted at a load of 5 bar BMEP to validate the simulation results against RCCI experimental data. In the low load study, it was found that the Rahimi mechanism was not able to predict the RCCI combustion behavior for diesel injection timings advanced beyond 30 degCA bTDC. This poor prediction was found at multiple engine speed and load points.

Gasoline compression ignition (GCI) technology shows the potential to obtain high thermal efficiencies while maintaining low soot and NOx emissions in light-duty engine applications. Recent experimental studies and numerical simulations have indicated that high reactivity gasoline-like fuels can further enable the benefits of GCI combustion. However, there is limited empirical data in the literature studying the gasoline compression ignition process at relevant in-cylinder conditions, which are required for further optimizing combustion system designs. This study investigates the temporal and spatial evolution of the compression ignition process of various high reactivity gasoline fuels with research octane numbers (RON) of 71, 74 and 82, as well as a conventional RON 97 E10 gasoline fuel. A ten-hole prototype gasoline injector specifically designed for GCI applications capable of injection pressures up to 450 bar was used.

In-cylinder ion sensing is a subject of interest due to its application in spark-ignited (SI) engines for feedback control and diagnostics including: combustion knock detection, rate and phasing of combustion, and mis-fire On Board Diagnostics (OBD). Further advancement and application is likely to continue as the result of the availability of ignition coils with integrated ion sensing circuitry making ion sensing more versatile and cost effective. In SI engines, combustion knock is controlled through closed loop feedback from sensor metrics to maintain knock near the borderline, below engine damage and NVH thresholds. Combustion knock is one of the critical applications for ion sensing in SI engines and improvement in knock detection offers the potential for increased thermal efficiency. This work analyzes and characterizes the ionization signal in reference to the cylinder pressure signal under knocking and non-knocking conditions.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

Studies have shown that there are a significant number of chemical species present in engine exhaust particulate matter emissions. Additionally, the majority of current world-wide regulatory methods for measuring engine particulate emissions are gravimetrically based. As modern engines considerably reduce particulate mass emissions, these methods become less stable and begin to display higher levels of measurement uncertainty. In this study, a characterization of mass emissions from three heavy-duty diesel engines, with a range of particulate emission levels, was made in order to gain a better understanding of the variability and uncertainty associated with common mass measurement methods, as well as how well these methods compare with each other. Two gravimetric mass measurement methods and a reconstructed mass method were analyzed as part of the present study.

Diesel particulate filters are designed to reduce the mass emissions of diesel particulate matter and have been proven to be effective in this respect. Not much is known, however, about their effects on other unregulated chemical species. This study utilized source dilution sampling techniques to evaluate the effects of a catalyzed diesel particulate filter on a wide spectrum of chemical emissions from a heavy-duty diesel engine. The species analyzed included both criteria and unregulated compounds such as particulate matter (PM), carbon monoxide (CO), hydrocarbons (HC), inorganic ions, trace metallic compounds, elemental and organic carbon (EC and OC), polycyclic aromatic hydrocarbons (PAHs), and other organic compounds. Results showed a significant reduction for the emissions of PM mass, CO, HC, metals, EC, OC, and PAHs.

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.

Research into the estimation of diesel engine combustion metrics via non-intrusive means, typically referred to as “remote combustion sensing” has become an increasingly active area of combustion research. Success in accurately estimating combustion metrics with low-cost non-intrusive transducers has been proven and documented by multiple sources on small scale diesel engines (2-4 cylinders, maximum outputs of 67 Kw, 210 N-m). This paper investigates the application of remote combustion sensing technology to a larger displacement inline 6-cylinder diesel with substantially higher power output (280 kW, 1645 N-m) than previously explored. An in-depth frequency analysis has been performed with the goal of optimizing the estimated combustion signature which has been computed based upon the direct relationship between the combustion event measured via a pressure transducer, and block vibration measured via accelerometers.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline injected using a triple-pulse strategy in the low temperature combustion (LTC) regime is presented. This work aims to extend the operation ranges for a light-duty diesel engine, operating on gasoline, that have been identified in previous work via extended controllability of the injection process. The single-cylinder engine (SCE) was operated at full load (16 bar IMEP, 2500 rev/min) and computational simulations of the in-cylinder processes were performed using 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 chosen to match ignition characteristics of the gasoline fuel used for the SCE experiments.

Many recent studies have shown that the Reactivity Controlled Compression Ignition (RCCI) combustion strategy can achieve high efficiency with low emissions. However, it has also been revealed that RCCI combustion is difficult at high loads due to its premixed nature. To operate at moderate to high loads with gasoline/diesel dual fuel, high amounts of EGR or an ultra low compression ratio have shown to be required. Considering that both of these approaches inherently lower thermodynamic efficiency, in this study natural gas was utilized as a replacement for gasoline as the low-reactivity fuel. Due to the lower reactivity (i.e., higher octane number) of natural gas compared to gasoline, it was hypothesized to be a better fuel for RCCI combustion, in which a large reactivity gradient between the two fuels is beneficial in controlling the maximum pressure rise rate.

In-cylinder temperature and velocity fields were quantified simultaneously in an optically accessible, small-bore diesel engine. A technique utilizing luminescence from Pr:YAG phosphor particles aerosolized into the intake air was used for temperature determination while particle image velocimetry (PIV) on the aforementioned phosphor particles was used to simultaneously measure the velocity field. The temperature and velocity fields were measured at different points throughout the compression stroke up to −30 CAD. Systematic interference due to emission from the piston window reduced the accuracy of the measurements at crank angles closer to TDC. Single-shot simultaneous measurements of the temperature and velocity fields were made using both unheated and heated intake temperatures. In both cases, cycle-to-cycle variations in the temperature and velocity fields were visible.

Exhaust emissions were characterized from a Cummins LTA10 heavy-duty diesel engine operated at two EPA steady-state modes with and without an uncatalyzed Corning ceramic particulate trap. The regulated emissions of nitrogen oxides (NOx), hydrocarbons (HC), and total particulate matter (TPM) and its components as well as the unregulated emissions of PAH, nitro-PAH, mutagenic activity and particle size distributions were measured. The consistently significant effects of the trap on regulated emissions included reductions of TPM and TPM-associated components. There were no changes in NOx and HC were reduced only at one operating condition. Particle size distribution measurements showed that nuclei-mode particles were formed downstream of the trap, which effectively removed accumulation-mode particles. All of the mutagenicity was direct-acting and the mutagenic activity of the XOC was approximately equivalent to that of the SOF without the trap.

This paper evaluates the potential of adding higher alcohols to gasoline blendstock in an attempt to improve overall fuel performance. The alcohols considered include ethanol, normal- and iso-structures of propanol, butanol and pentanol as well as normal-hexanol (C2-C6). Fuel performance is quantified based on energy content, knock resistance as well as petroleum displacement and promising multi-component blends are systematically identified based on property prediction methods. These promising multi-component blends, as well as their respective reference fuels, are subsequently tested for efficiency and emissions performance utilizing a gasoline direct injection, spark ignition engine. The engine test results confirm that combustion and efficiency of tailored multi-component blends closely match those of the reference fuels. Regulated emissions stemming from combustion of these blends are equal or lower compared to the reference fuels across the tested engine speed and load regime.

This paper describes a study to demonstrate the feasibility of developing an acoustic encapsulation to reduce airborne noise from a commercial diesel engine. First, the various sources of noise from the engine were identified using Nearfield Acoustical Holography (NAH). Detailed NAH measurements were conducted on the four sides of the engine in an engine test cell. The main sources of noise from the engine were ranked and identified within the frequency ranges of interest. Experimental modal analysis was conducted on the oil pan and front cover plate of the engine to reveal correlations of structural vibration results with the data from the NAH. The second phase of the study involved the design and fabrication of the acoustical encapsulation (noise covers) for the engine in a test cell to satisfy the requirements of space, cost and performance constraints. The acoustical materials for the enclosure were selected to meet the frequency and temperature ranges of interest.