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Low temperature combustion through in-cylinder blending of fuels with different reactivity offers the potential to improve engine efficiency while yielding low engine-out NOx and soot emissions. A Navistar MaxxForce 13 heavy-duty compression ignition engine was modified to run with two separate fuel systems, aiming to utilize fuel reactivity to demonstrate a technical path towards high engine efficiency. The dual-fuel engine has a geometric compression ratio of 14 and uses sequential, multi-port-injection of a low reactivity fuel in combination with in-cylinder direct injection of diesel. Through control of in-cylinder charge reactivity and reactivity stratification, the engine combustion process can be tailored towards high efficiency and low engine-out emissions. Engine testing was conducted at 1200 rpm over a load sweep.

In this study, the combustion system of a light-duty compression ignition engine running on a market gasoline fuel with Research Octane Number (RON) of 91 was optimized using computational fluid dynamics (CFD) and Machine Learning (ML). This work was focused on optimizing the piston bowl geometry at two compression ratios (CR) (17 and 18:1) and this exercise was carried out at full-load conditions (20 bar indicated mean effective pressure, IMEP). First, a limited manual piston design optimization was performed for CR 17:1, where a couple of pistons were designed and tested. Thereafter, a CFD design of experiments (DoE) optimization was performed where CAESES, a commercial software tool, was used to automatically perturb key bowl design parameters and CONVERGE software was utilized to perform the CFD simulations. At each compression ratio, 128 piston bowl designs were evaluated.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.

In this work, a turbulent combustion model is developed for large eddy simulation (LES) using a novel flamelet tabulation technique based on the framework of the multi-flamelet representative interactive flamelet (RIF) model. The overall aim is to develop a detailed model with elaborate chemistry mechanisms, LES turbulence models and highly resolved grids leveraging the computational cost advantage of a tabulated model. A novel technique of implementing unsteady flamelet libraries by using the residence time instead of the progress variables is proposed. In this study, LES of n-dodecane spray flame is performed using the tabulated turbulent combustion model along with a dynamic structure subgrid model. A high-resolution mesh is employed with a cell size of 62.5 microns in the entire spray and combustion regions. This model is then validated against igniting n-dodecane sprays under diesel engine conditions.

Advanced internal combustion engines, although generally more efficient than conventional combustion engines, often encounter limitations in multi-cylinder applications due to variations in the combustion process. This study leverages experimental data from an inline 6-cylinder heavy-duty dual fuel engine equipped with a fully-flexible variable intake valve actuation system to study cylinder-to-cylinder variations in power production. The engine is operated with late intake valve closure timings in a dual-fuel combustion mode featuring a port-injection and a direct-injection fueling system in order to improve fuel efficiency and engine performance. Experimental results show increased cylinder-to-cylinder variation in IMEP as IVC timing moves from 570°ATDC to 610°ATDC, indicating an increasingly uneven fuel distribution between cylinders.

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.

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.

Achieving robust ignitability for compression ignition of diesel engines at cold conditions is traditionally challenging due to insufficient fuel vaporization, heavy wall impingement, and thick wall films. Gasoline compression ignition (GCI) has shown the potential to offer an enhanced NOx-particulate matter tradeoff with diesel-like fuel efficiency, but it is unknown how the volatility and reactivity of the fuel will affect ignition under very cold conditions. Therefore, it is important to investigate the impact of fuel physical and chemical properties on ignition under pressures and temperatures relevant to practical engine operating conditions during cold weather. In this paper, 0-D and 3-D computational fluid dynamics (CFD) simulations of GCI combustion at cold conditions were performed.

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.

An accurate prediction of internal nozzle flow in fuel injector offers the potential to improve predictions of spray computational fluid dynamics (CFD) in an engine, providing a coupled internal-external calculation or by defining better rate of injection (ROI) profile and spray angle information for Lagrangian parcel computations. Previous research has addressed experiments and computations in transparent nozzles, but less is known about realistic multi-hole diesel injectors compared to single axial-hole fuel injectors. In this study, the transient injector opening and closing is characterized using a transparent multi-hole diesel injector, and compared to that of a single axial hole nozzle (ECN Spray D shape). A real-size five-hole acrylic transparent nozzle was mounted in a high-pressure, constant-flow chamber. Internal nozzle phenomena such as cavitation and gas exchange were visualized by high-speed long-distance microscopy.

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.

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.

This paper describes the validation of a CFD code for mixture preparation in a direct injection hydrogen-fueled engine. The cylinder geometry is typical of passenger-car sized spark-ignited engines, with a centrally located injector. A single-hole and a 13-hole nozzle are used at about 100 bar and 25 bar injection pressure. Numerical results from the commercial code Fluent (v6.3.35) are compared to measurements in an optically accessible engine. Quantitative planar laser-induced fluorescence provides phase-locked images of the fuel mole-fraction, while single-cycle visualization of the early jet penetration is achieved by a high-speed schlieren technique. The characteristics of the computational grids are discussed, especially for the near-nozzle region, where the jets are under-expanded. Simulation of injection from the single-hole nozzle yields good agreement between numerical and optical results in terms of jet penetration and overall evolution.

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.

The application of hydrogen (H2) as an internal combustion (IC) engine fuel has been under investigation for several decades. The favorable physical properties of hydrogen make it an excellent alternative fuel for fuel cells as well as IC engines and hence it is widely regarded as the energy carrier of the future. The potential of hydrogen as an IC engine fuel can be optimized by direct injection (DI) as it provides multiple degrees of freedom to influence the in-cylinder combustion processes and consequently the engine efficiency and exhaust emissions. This paper studies a single-hole nozzle and examines the effects of injection strategy on engine efficiency, combustion behavior and NOx emissions. The experiments for this study are done on a 0.5 liter single-cylinder research engine which is specifically designed for combustion studies and equipped with a cylinder head that allows side as well as central injector location.

It is challenging to develop highly efficient and clean engines while meeting user expectations in terms of performance, comfort, and drivability. One of the critical aspects in this regard is combustion noise control. Combustion noise accounts for about 40 percent of the overall engine noise in typical turbocharged diesel engines. The experimental investigation of noise generation is difficult due to its inherent complexity and measurement limitations. Therefore, it is important to develop efficient numerical strategies in order to gain a better understanding of the combustion noise mechanisms. In this work, a novel methodology was developed, combining computational fluid dynamics (CFD) modeling and genetic algorithm (GA) technique to optimize the combustion system hardware design of a high-speed direct injection (HSDI) diesel engine, with respect to various emissions and performance targets including combustion noise.

Dimethyl ether (DME) is an alternative to diesel fuel for use in compression-ignition engines with modified fuel systems and offers potential advantages of efficiency improvements and emission reductions. DME can be produced from natural gas (NG) or from renewable feedstocks such as landfill gas (LFG) or renewable natural gas from manure waste streams (MANR) or any other biomass. This study investigates the well-to-wheels (WTW) energy use and emissions of five DME production pathways as compared with those of petroleum gasoline and diesel using the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model developed at Argonne National Laboratory (ANL).

Previous studies have shown that fuels with higher laminar flame speed also have increased tolerance to EGR dilution. In this work, the effects of fuel laminar flame speed on both lean and EGR dilute spark ignition combustion stability were examined. Fuels blends of pure components (iso-octane, n-heptane, toluene, ethanol, and methanol) were derived at two levels of laminar flame speed. Each fuel blend was tested in a single-cylinder spark-ignition engine under both lean-out and EGR dilution sweeps until the coefficient of variance of indicated mean effective pressure increased above thresholds of 3% and 5%. The relative importance of fuel laminar flame speed to changes to engine design parameters (spark ignition energy, tumble ratio, and port vs. direct injection) was also assessed.