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The possibility to operate current diesel engines in dual-fuel mode with the addition of an alternative fuel is fundamental to accelerate the energy transition to achieve carbon neutrality. The simulation of the dual- fuel combustion process with 0D/1D combustion models is fundamental for the performance prediction, but still particularly challenging, due to chemical interactions of the mixture. The authors defined a novel data-driven workflow for the development of combustion reaction mechanisms and used it to generate a dual-fuel mechanism for Ammonia and Diesel Primary Reference Fuels (DPRF) suitable for efficient combustion simulations in heavy duty engines, with variable cetane number Diesel fuels. A baseline reaction mechanism was created by merging the detailed ammonia mechanism by Glarborg et al. with reaction pathways for n- hexadecane and 2,2,4,4,6,8,8-heptamethylnonane from a well-established multi-component fuel mechanism.

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.

Accelerated computational optimization of a diesel engine calibration was achieved by combining Support Vector Regression models with the Particle Swarm Optimization routine. The framework utilized a full engine simulation as a surrogate for a real engine test with test parameters closely resembling a typical 4.5L diesel engine. Initial tests were run with multi-modal test problems including Rastragin's, Bukin's, Ackely's, and Schubert's functions which informed the ML model tuning hyper-parameters. To improve the performance of the engine the hybrid approach was used to optimize the Fuel Pressure, Injection Timing, Pilot Timing and Fraction, and EGR rate. Nitrogen Oxides, Particulate Matter, and Specific Fuel Consumption are simultaneously reduced. As expected, optimums reflect a late injection strategy with moderately high EGR rates.

In this study both double and triple injection strategies were used with fuel pressures up to 300 and 250 MPa, respectively. Tests were conducted at medium load conditions with cooled, high-pressure EGR at a ratio of 40% and higher. A four-cylinder production engine, featuring double turbochargers with one variable geometry turbocharger, was tested. The double injection strategy consisted of a 20% close-coupled pilot injection while the triple injection strategy introduced a post injection consisting of 10% the total cycle fuel. Results of this study do not indicate an advantage to extreme fuel pressure. The increased air entrainment reduces soot while increasing the premixed burn heat release, mean cylinder temperature, and NOx. Compared to the double injection scheme, triple injections achieved much lower soot for the same EGR rate with only a small NOx penalty.

The objective of this work was to identify methods of reliably predicting optimum operating conditions in an experimental compression ignition engine using multiple injections. Abstract modeling offered an efficient way to predict large volumes data, when compared with simulation, although the initial cost of constructing such models can be large. This work aims to reduce that initial cost by adding knowledge about the favorable network structures and training rules which are discovered. The data were gathered from a high pressure common rail direct injection turbocharged compression ignition engine utilizing a high EGR configuration. The range of design parameters were relatively large; 100 MPa - 240 MPa for fuel pressure, up to 62% EGR using a modified, long-route, low pressure EGR system, while the pilot timing, main timing, and pilot ratio were free within the safe operating window for the engine.

Particle Swarm and the Genetic Algorithm were coupled to optimize multiple performance metrics for the combustion of neat biodiesel in a turbocharged, four cylinder, John Deere engine operating under constant partial load. The enhanced algorithm was used with five inputs including EGR, injection pressure, and the timing/distribution of fuel between a pilot and main injection. A merit function was defined and used to minimize five output parameters including CO, NOx, PM, HC and fuel consumption simultaneously. The combination of PSO and GA yielded convergence to a Pareto regime without the need for excessive engine runs. Results along the Pareto front illustrate the tradeoff between NOx and particulate matter seen in the literature.

Due to the new challenge of meeting number-based regulations for particulate matter (PM), a numerical and experimental study has been conducted to better understand particulate formation in engines fuelled with compressed natural gas. The study has been conducted on a Heavy-Duty, Euro VI, 4-cylinder, spark ignited engine, with multipoint sequential phased injection and stoichiometric combustion. For the experimental measurements two different instruments were used: a condensation particle counter (CPC) and a fast-response particle size spectrometer (DMS) the latter able also to provide a particle size distribution of the measured particles in the range from 5 to 1000 nm. Experimental measurements in both stationary and transient conditions were carried out. The data using the World Harmonized Transient Cycle (WHTC) were useful to detect which operating conditions lead to high numbers of particles. Then a further transient test was used for a more detailed and deeper analysis.

Control of the timing and magnitude of heat release is one of the biggest challenges for premixed compression ignition, especially when attempting to operate at high load. Single-fuel strategies such as partially premixed combustion (PPC) use direct injection of gasoline to stratify equivalence ratio and retard heat release, thereby reducing pressure rise rate and enabling high load operation. However, retarding the heat release also reduces the maximum work extraction, effectively creating a tradeoff between efficiency and noise. Dual-fuel strategies such as reactivity controlled compression ignition (RCCI) use premixed gasoline and direct injection of diesel to stratify both equivalence ratio and fuel reactivity, which allows for greater control over the timing and duration of heat release. This enables combustion phasing closer to top dead center (TDC), which is thermodynamically favorable.

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.

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.

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.

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 research has been investigated in single-cylinder heavy-duty engines [1, 2, 3, 4, 5, 6]. The current study investigates RCCI operation in a light-duty multi-cylinder engine over a wide number of operating points representing vehicle operation over the US EPA FTP test. Similarly, previous RCCI engine experiments have used petroleum based fuels such as ultra-low sulfur diesel fuel (ULSD) and gasoline, with some work done using high percentages of biofuels, namely E85 [7]. The current study was conducted to examine RCCI performance with moderate biofuel blends, such as E20 and B20, as compared to conventional gasoline and ULSD.

A single-cylinder light-duty diesel engine was used to investigate dual fuel reactivity controlled compression ignition (RCCI) operated with two different fuel combinations: gasoline/diesel fuel and methanol/diesel fuel. The engine was operated over a range of conditions, from 1500 to 2300 rpm and 3.5 to 17 bar gross IMEP. Using the stock re-entrant piston bowl geometry, both fuel combinations were able to achieve low NOx and PM emissions with a peak gross indicated efficiency of 48%. However, at light load conditions both gasoline and methanol yielded poorer combustion efficiencies. Previous studies have shown that the high-levels of piston induced mixing that are created by the stock piston are not required, and in fact are detrimental due to increased heat transfer losses, for premixed combustion. Thus a modified piston featuring a shallow, flat piston bowl with nearly no squish land was also investigated.

The focus of the present study was to characterize the fuel reactivity of high octane number fuels (i.e., low fuel reactivity), namely gasoline, ethanol, and methanol when mixed with cetane improvers under lean, premixed combustion conditions. Two commercially available cetane improvers, 2-ethylhexyl nitrate and di-tert-butyl peroxide, were used in the study. First, blends of the primary reference fuels iso-octane and n-heptane were port injected under fixed operating conditions. The resulting combustion phasings were used to generate effective PRF number maps. Then, blends of the aforementioned base fuels and cetane improvers were tested under the same lean premixed conditions as the PRF blends. Based on the combustion phasing results of the base fuel and cetane improver mixture, the effective PRF number, or octane number, could be determined.

Various mixtures of ammonia (NH₃) and dimethyl ether (DME) were tested in a diesel engine to explore the feasibility of using ammonia as an alternative, non-carbon fuel to mitigate greenhouse gas emissions. The original diesel fuel injection system was replaced with a new system for injecting ammonia-DME mixtures into the cylinder directly. The injection pressure was maintained at approximately 206 bar for various fuel mixtures including 100% DME, 60%DME-40%NH₃, and 40%DME-60%NH₃ (by weight). As ammonia content was increased in the fuel mixture, the injection timing needed to be advanced to ensure successful engine operation. It was found that cycle-to-cycle variation increased significantly when 40%DME-60%NH₃ was used. In the meantime, combustion of 40%DME-60%NH₃ exhibited HCCI characteristics as the injection timing ranged from 90 to 340 before top-dead-center (BTDC). Emissions data show that soot emissions remained extremely low for the fuel mixtures tested.

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.

Accurate modeling of evaporating sprays is critical for diesel engine simulations. The standard spray and evaporation models in KIVA-3V tend to under-predict the vapor penetration, especially at high ambient pressure conditions. A sharp decrease of vapor penetration gradient is observed soon after the liquid spray is completely evaporated due to the lack of momentum sources beyond the liquid spray region. In this study, a gas particle model is implemented in KIVA-3V which tracks the momentum sources resulting from the evaporated spray. Lagrangian tracking of imaginary gas particles is considered until the velocity of the gas particle is comparable to that of the gas phase velocity. The gas particle continuously exchanges momentum with the gas phase and as a result the vapor penetrations are improved. The results using the present gas particle model is compared with experimental data over a wide range of ambient conditions and good levels of agreement are observed in vapor penetration.

Advanced combustion systems that simultaneously address PM and NOx while retaining the high efficiency of modern diesel engines, are being developed around the globe. One of the most difficult problems in the area of advanced combustion technology development is the control of combustion initiation and retaining power density. During the past several years, significant progress has been accomplished in reducing emissions of NOx and PM through strategies such as LTC/HCCI/PCCI/PPCI and other advanced combustion processes; however control of ignition and improving power density has suffered to some degree - advanced combustion engines tend to be limited to the 10 bar BMEP range and under. Experimental investigations have been carried out on a light-duty DI multi-cylinder diesel automotive engine. The engine is operated in low temperature combustion (LTC) mode using 93 RON (Research Octane Number) and 74 RON fuel.

The paper presents the development of a novel approach to the solution of detailed chemistry in internal combustion engine simulations, which relies on the analytical computation of the ordinary differential equations (ODE) system Jacobian matrix in sparse form. Arbitrary reaction behaviors in either Arrhenius, third-body or fall-off formulations can be considered, and thermodynamic gas-phase mixture properties are evaluated according to the well-established 7-coefficient JANAF polynomial form. The current work presents a full validation of the new chemistry solver when coupled to the KIVA-4 code, through modeling of a single cylinder Caterpillar 3401 heavy-duty engine, running in two-stage combustion mode.

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.