Search Results

Abstract This study demonstrates the defossilized operation of a heavy-duty port-fuel-injected dual-fuel engine and highlights its potential benefits with minimal retrofitting effort. The investigation focuses on the optical characterization of the in-cylinder processes, ranging from mixture formation, ignition, and combustion, on a fully optically accessible single-cylinder research engine. The article revisits selected operating conditions in a thermodynamic configuration combined with Fourier transform infrared spectroscopy. One approach is to quickly diminish fossil fuel use by retrofitting present engines with decarbonized or defossilized alternatives. As both fuels are oxygenated, a considerable change in the overall ignition limits, air–fuel equivalence ratio, burning rate, and resistance against undesired pre-ignition or knocking is expected, with dire need of characterization.

Abstract A detailed investigation was carried out on the performance, combustion, and emissions of a single-cylinder direct injection hydrogen spark ignition (SI) engine with either a side-mounted direct injection (SDI) or a centrally installed direct injection (CDI) injector. The first part of the study analyzed the performance and emissions characteristics of CDI and SDI engine operations with different injection timings and pressures. This was followed by comparing the engine’s performance and emissions of the CDI and SDI operations at different engine speeds and relative air-to-fuel ratios (lambda) with the optimized injection pressure and timings. Furthermore, the performance and emission attributes of the hydrogen engine with the CDI and SDI setups were conducted at a fixed λ value of 2.75 across a broad spectrum of engine loads. The study’s main outcome demonstrates that both direct injection systems produced near-zero CO2, CO, and HC emissions.

Abstract Fossil fuel reserves are swiftly depleting when consumer demand for these fuels continues to rise. In order to meet the demand and diminish the pollution derived through conventional fuels, it is crucial to employ cleaner fuels made from substitutes such as waste biomass. Also, converting waste biomass to fuel can lower usage of landfills. There are many biomass resources that are suitable for fuel production, out of which groundnut is also a potential feedstock. Groundnut shell biomass was chosen for this study, as it is a waste leftover during shelling of groundnuts for various commercial applications. The procured groundnut shells were converted to oil using pyrolysis process and was distilled. Both the pyrolysis oil and the distilled oil were analyzed using Fourier transform infrared instrument wherein the presence of functional groups such as alcohols, amines, and carboxylic acids were identified.

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Abstract Various feedstocks can be employed for biodiesel production, leading to considerable variation in composition and engine fuel characteristics. Using biodiesels originating from diverse feedstocks introduces notable variations in engine characteristics. Therefore, it is imperative to scrutinize the composition and properties of biodiesel before deployment in engines, a task facilitated by predictive models. Additionally, the international commercialization of biodiesel fuel is contingent upon stringent regulations. The traditional experimental measurement of biodiesel properties is laborious and expensive, necessitating skilled personnel. Predictive models offer an alternative approach by estimating biodiesel properties without depending on experimental measurements. This research is centered on building models that correlate mid-infrared spectra of biodiesel and critical fuel properties, encompassing kinematic viscosity, cetane number, and calorific value.

Abstract Driving schedule of every vehicle involves transient operation in the form of changing engine speed and load conditions, which are relatively unchanged during steady-state conditions. As well, the results from transient conditions are more likely to reflect the reality. So, the current research article is focused on analyzing the biofuel-like lemon peel oil (LPO) behavior under real-world transient conditions with fuel injection parameter MAP developed from steady-state experiments. At first, engine parameters and response MAPs are developed by using a response surface methodology (RSM)-based multi-objective optimization technique. Then, the vehicle model has been developed by incorporating real-world transient operating conditions. Finally, the developed injection parameters and response MAPs are embedded in the vehicle model to analyze the biofuel behavior under transient operating conditions.

Abstract This article presents surrogate mixtures that simulate the physical and chemical properties in the auto-ignition of hydrotreated vegetable oil (HVO). Experimental investigation was conducted in the Ignition Quality Tester (IQT) to validate the auto-ignition properties with respect to those of the target fuel. The surrogate development approach is assisted by artificial neural network (ANN) embedded in MATLAB optimization function. Aspen HYSYS is used to calculate the key physical and chemical properties of hundreds of mixtures of representative components, mainly alkanes—the dominant components of HVO, to train the learning algorithm. Binary and ternary mixtures are developed and validated in the IQT. The target properties include the derived cetane number (DCN), density, viscosity, surface tension, molecular weight, and volatility represented by the distillation curve. The developed surrogates match the target fuel in terms of ignition delay and DCN within 6% error range.

Abstract Reactivity-controlled compression ignition (RCCI) engine is an innovative dual-fuel strategy, which uses two fuels with different reactivity and physical properties to achieve low-temperature combustion, resulting in reduced emissions of oxides of nitrogen (NOx), particulate matter, and improved fuel efficiency at part-load engine operating conditions compared to conventional diesel engines. However, RCCI operation at high loads poses challenges due to the premixed nature of RCCI combustion. Furthermore, precise controls of indicated mean effective pressure (IMEP) and CA50 combustion phasing (crank angle corresponding to 50% of cumulative heat release) are crucial for drivability, fuel conversion efficiency, and combustion stability of an RCCI engine.

Abstract In view of the combustion efficiency and emission performance, various new clean combustion modes put forward higher requirements for the performance of the fuel injection system, and the cavitating two-phase flow characteristics in the injector nozzle have a significant impact on the spray atomization and combustion performance. This article comprehensively discusses and summarizes the factors that affect cavitation and the effectiveness of cavitation, and presents the research status and existent problems under each factor. Among them, viscosity factors are a hot research topic that researchers are passionate about, and physical properties factors still have the value of further in-depth research. However, the importance of material surface factors ranks last since the nozzle material was determined. Establishing a more comprehensive cavitation–atomization model considering various factors is the focus of research on cavitation phenomena.

Abstract The numerical study presented in this article is based on an automotive diesel engine (2.8 L, 4-cylinder, turbocharged), considering a NG–H2 blend with 30 vol% of H2, ignited by multiple diesel fuel injections. The 3D-CFD investigation aims at improving BTE, CO, and UHC emissions at low load, by means of an optimization of the diesel fuel injection strategy and of the in-cylinder turbulence (swirl ratio, SR). The operating condition is 3000 rpm – BMEP = 2 bar, corresponding to about 25% of the maximum load of a gen-set engine, able to deliver up to 83 kW at 3000 rpm (rated speed). The reference diesel fuel injection strategy, adopted in all the previous numerical and experimental studies, is a three-shot mode. The numerical optimization carried out in this study consisted in finding the optimal number of injections per cycle, as well as the best timing of each injection and the fuel mass split among the injections.

Abstract Limited fossil fuel resources and carbonaceous greenhouse gas emissions are two major problems the world faces today. Alternative fuels can effectively power internal combustion engines to address these issues. Methanol can be an alternative to conventional fuels, particularly to displace gasoline in spark ignition engines. The physicochemical properties of methanol are significantly different than baseline gasoline and fuel mixture-aim lambda; hence methanol-fueled engines require modifications in the fuel injection parameters. This study optimized the fuel injection quantity, spark timing, and air–fuel ratio for M85 (85% v/v methanol + 15% v/v gasoline) fueling of a port fuel-injected single-cylinder 500 cc motorcycle test engine. Comparative engine performance, combustion, and emissions analyses were performed for M85 and baseline gasoline.

Abstract Greenhouse gas emissions reduction from the light-duty transportation fleet is urgent and should address both electric and conventional powertrain technologies. Internal combustion engines will continue to be employed for vehicle propulsion and fleet turnover is slow, encouraging reduction of carbon content in gasoline. Currently ethanol, a renewable fuel, is blended at the 10% level into petroleum to produce finished market gasoline. Ethanol enables a less carbon-intensive petroleum blendstock composition, providing for additional reduction, but this is often overlooked in studies. Carbon intensity, as a ratio of CO2 mass to heat released upon combustion, is a measure of well-to-wheels greenhouse gas production. The well-to-wheels carbon intensity of ethanol does not include its chemical carbon content because it arises from a renewable source, but does consider all upstream farming, production, and transportation carbon impacts.

Abstract Methanol is emerging as an alternate internal combustion engine fuel. It is getting attention in countries such as China and India as an emerging transport fuel. Using methanol in spark ignition engines is easier and more economical than in compression ignition engines via the blending approach. M85 (85% v/v methanol and 15% v/v gasoline) is one of the preferred blends with the highest methanol concentration. However, its physicochemical properties significantly differ from gasoline, leading to challenges in operating existing vehicles. This experimental study addresses the challenges such as cold-start operation and poor throttle response of M85-fueled motorcycle using a port fuel injection engine. In this study, M85-fueled motorcycle prototype is developed with superior performance, similar/better drivability, and lower emissions than a gasoline-fueled port-fuel-injected motorcycle.

Abstract The present study examines the effect of the multiple injection strategies in a common rail diesel engine using machine learning, image processing, and object detection techniques. The study demonstrates a novel approach of utilizing image-processing tools to gain information from heat release rates and in-cylinder visualizations from experimental or computational studies. The 3D CFD combustion and emission predictions of a commercial code ANSYS FORTE© are validated with small-bore common rail diesel engine data with known injection strategies. The validated CFD tool is used as a virtual plant model to optimize the injection schedule for reducing oxides of nitrogen (NOx) and soot emissions using an apparent heat release rate image-based machine learning tool. A methodology of the machine learning tool is quite helpful in predicting the NO–soot trade-off.

Abstract Tank-to-wheels (TTW) CO2 reduction for ethanol blends is determined from either gasoline composition or vehicle exhaust measurements. Fuels are characterized using a carbon intensity (CI), which is the ratio of carbon (as CO2 mass) in the fuel to the net heating value. Our objective is to assess changes in CI of market gasoline with varying ethanol content that can be used to appreciate change in vehicle tailpipe greenhouse gases (GHG) in response to policy controlling the ethanol level in market fuels. Ethanol has both a reduced carbon content and a reduced net (lower) heating value relative to petroleum species, with a CI slightly lower than that of typical petroleum gasoline. However, ethanol blending offers additional CI reduction because it enables a reduction of aromatics in the petroleum blendstock for oxygenate blending (BOB) while maintaining octane rating of the blend. Aromatics have a CI about 20% higher than paraffins.

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Abstract The European Union’s pro-ecological policy imposes a requirement to use biofuel additives in diesel fuel which is supposed to support the sustainable development of transport and limit its negative impact on the natural environment. The study presents an analysis of the exhaust gas components and the amount of solid particles carried out for internal combustion engines fueled with mixtures of diesel fuel and fatty acid methyl esters. Additionally, the computer software of the tested power units was modified by changing the amount of fuel to be supplied and the air intake. The goal of the tests was to find out how the fuel mixture and reprogramming of the computer control systems would impact the emission of exhaust gas components. Based on the tests, it was found that an additive of fatty acid methyl esters to diesel does have an influence on the tested unit parameters.

Abstract Research into efficient internal combustion (IC) engines need to continue as the majority of vehicles will still be powered by IC or hybrid powertrains in the foreseeable future. Recently, lean-burn gasoline compression ignition (GCI) with high-pressure direct injection has been receiving considerable attention among the research community due to its ability to improve thermal efficiency and reduce emissions. To maximize GCI benefits in engine efficiency and emissions tradeoff, co-optimization of the combustion system and fuel formation is required. Thus, it is essential to study the spray characteristics of different fuels under engine-like operating conditions. In this work, high-pressure spray characteristics are experimentally studied for three blends of gasoline, namely, Naphtha, E30, and research octane number (RON) 98. A single-hole custom-built injector was used to inject fuel into a constant volume chamber with injection pressure varying from 40 MPa to 100 MPa.

Abstract Letter from the Special Issue Editors

Abstract Due to the incoming phase out of fossil fuels from the market in order to reduce the carbon footprint of the automotive sector, hydrogen-fueled engines are candidate mid-term solution. Thanks to its properties, hydrogen promotes flames that poorly suffer from the quenching effects toward the engine walls. Thus, emphasis must be posed on the heat-up of the oil layer that wets the cylinder liner in hydrogen-fueled engines. It is known that motor oils are complex mixtures of a number of mainly heavy hydrocarbons (HCs); however, their composition is not known a priori. Simulation tools that can support the early development steps of those engines must be provided with oil composition and properties at operation-like conditions. The authors propose a statistical inference-based optimization approach for identifying oil surrogate multicomponent mixtures. The algorithm is implemented in Python and relies on the Bayesian optimization technique.