Search Results

Abstract In this article, the effects of mixture dilution using EGR or excessive air on adiabatic flame temperature, laminar flame speed, and minimum ignition energy are studied to illustrate the fundamental benefits of lean combustion. An ignition system developing a new active pre-chamber (APC) design was assessed, aimed at improving the indicated thermal efficiency (ITE) of a 1.5 L four-cylinder gasoline direct injection (GDI) engine. The engine combustion process was simulated with the SAGE detailed chemistry model within the CONVERGE CFD tool, assuming the primary reference fuel (PRF) to be a volumetric mixture of 93% iso-octane and 7% n-heptane. The effects of design parameters, such as APC volume, nozzle diameter, and nozzle orientations, on ITE were studied. It was found that the ignition jet velocity from the pre-chamber to the main chamber had a significant impact on the boundary heat losses and combustion phasing.

Abstract Biogas (60% methane–40% CO2 approximately) can be used in the reactivity-controlled compression ignition (RCCI) mode along with a high-reactivity fuel (HRF). In this work dimethyl ether (DME) that can also be produced from renewable sources was used as the HRF as a move toward sustainable power generation. The two-cylinder turbocharged diesel engine modified to work in the DME–biogas RCCI (DMB-RCCI) mode was studied under different proportions of methane (45–95%) in biogas since the quality of this fuel can vary depending on the feedstock and production method. Only a narrow range of biogas to DME ratios could be tolerated in this mode at each output without misfire or knock. Detailed experiments were conducted at brake mean effective pressures (BMEPs) of 3 and 5 bar at a speed of 1500 rpm and comparisons were made with the diesel–biogas dual-fuel and diesel–biogas RCCI modes under similar methane flow rates while the proportion of CO2 was varied.

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 The water droplet erosion (WDE) on high-speed rotating wheels appears in several engineering fields such as wind turbines, stationary steam turbines, fuel cell turbines, and turbochargers. The main reasons for this phenomenon are the high relative velocity difference between the colliding particles and the rotor, as well as the presence of inadequate material structure and surface parameters. One of the latest challenges in this area is the compressor wheels used in turbochargers, which has a speed up to 300,000 rpm and have typically been made of aluminum alloy for decades, to achieve the lowest possible rotor inertia. However, while in the past this component was only encountered with filtered air, nowadays, due to developments in compliance with tightening emission standards, various fluids also collide with the spinning blades, which can cause mechanical damage.

Abstract The two-branch exhaust of an asymmetric twin-scroll turbocharged engine are asymmetrically and periodically complicated, which has great impact on turbine matching. In this article, a matching effect of turbine speed parameter on asymmetric twin-scroll turbines based on the exhaust pulse energy weight distribution of a heavy-duty diesel engine was introduced. First, it was built as an asymmetric twin-scroll turbine matching based on exhaust pulse energy distribution. Then, by comparing the average matching point and energy matching points on the corresponding turbine performance map, it is revealed that the turbine speed parameter of energy matching points was a significant deviation from the turbine speed parameter under peak efficiency, which leads to the actual turbine operating efficiency lower than the optimal state.

Abstract Asymmetric twin-scroll turbocharging technology, as one of the effective technologies for balancing fuel economy and nitrogen oxide emissions, has been widely studied in the past decade. In response to the ever-increasing demands for improved fuel efficiency and reduced exhaust emissions, extensive research efforts have been dedicated to investigating various aspects of this technology. Researchers have conducted both experimental and simulation studies to delve into the intricate flow mechanism of asymmetric twin-scroll turbines. Furthermore, considerable attention has been given to exploring the optimal matching between asymmetric twin-scroll turbines and engines, as well as devising innovative flow control methods for these turbines. Additionally, researchers have sought to comprehend the impact of exhaust pulse flow on the performance of asymmetric twin-scroll turbines.

Abstract Heavy-duty on-road engines are expected to conform to an ultralow NOx (ULNOx) standard of 0.027 g/kWh over the composite US heavy-duty transient federal test procedure (HD-FTP) cycle by 2031, a 90% reduction compared to 2010 emissions standards. Additionally, these engines are expected to conform to Phase 2 greenhouse gas regulations, which require tailpipe CO2 emissions under 579 g/kWh. This study experimentally demonstrates the ability of high fuel stratification gasoline compression ignition (HFS-GCI) to satisfy these emissions standards. Steady-state and transient tests are conducted on a prototype multi-cylinder heavy-duty GCI engine based on a 2010-compliant Cummins ISX15 diesel engine with a urea-SCR aftertreatment system (ATS). Steady-state calibration exercises are undertaken to develop highly fuel-efficient GCI calibration maps at both cold-start and warmed up 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 Improving thermal efficiency of an internal combustion engine is one of the most cost-effective ways to reduce life cycle-based CO2 emissions for transportation. Lean burn technology has the potential to reach high thermal efficiency if simultaneous low NOx, HC, and CO emissions can be achieved. Low NOx can be realized by ultra-lean (λ ≥ 2) spark-ignited combustion; however, the HC and CO emissions can increase due to slow flame propagation and high combustion variability. In this work, we introduce a new combustion concept called turbulent jet-controlled compression ignition, which utilizes multiple turbulent jets to ignite the mixture and subsequently triggers end gas autoignition. As a result, the ultra-lean combustion is further improved with reduced late-cycle combustion duration and enhanced HC and CO oxidation. A low-cost passive prechamber is innovatively fueled using a DI injector in the main combustion chamber through spray-guided stratification.

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 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 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 Pre-chamber jet ignition technologies have been garnering significant interest in the internal combustion engine field, given their potential to deliver shorter burn durations, increased combustion stability, and improved dilution tolerance. However, a clear understanding of the relationship between pre-chamber geometry, operating condition, jet formation, and engine performance in light-duty gasoline injection engines remains under-explored. Moreover, research specifically focusing on high dilution levels and passive pre-chambers with optical accessibility is notably scarce. This study serves to bridge these knowledge gaps by examining the influence of passive pre-chamber nozzle diameter and dilution level on jet formation and engine performance.

Abstract The use of data-driven algorithms for the integration or substitution of current production sensors is becoming a consolidated trend in research and development in the automotive field. Due to the large number of variables and scenarios to consider; however, it is of paramount importance to define a consistent methodology accounting for uncertainty evaluations and preprocessing steps, that are often overlooked in naïve implementations. Among the potential applications, the use of virtual sensors for the analysis of solid emissions in transient cycles is particularly appealing for industrial applications, considering the new legislations scenario and the fact that, to our best knowledge, no robust models have been previously developed.

Abstract Emissions and effects of climate change have prompted study into fuels that reduce global dependence on traditional fuels. This study seeks to investigate engine performance, thermochemical properties, emissions, and perform NVH analysis of Jet-A and S8 using a single-stage turbojet engine at three engine speeds. Experimental Jet-A results were used to validate a CFX simulation of the engine. Engine performance was quantified using thermocouples, pressure sensors, tachometers, flow meters, and load cells fitted to the engine. Emissions results were collected using an MKS Multigas Emissions Analyzer that examined CO, CO₂, H₂O, NOx, and THC. NVH analysis was conducted using a multifield, free-field microphone, and triaxial accelerometer. This study found that Jet-A operates at higher temperatures and pressures than S8, and S8 requires higher fuel flow rates than Jet-A, leading to poorer efficiency and thrust. S8 produced stronger vibrations over 5 kHz compared to Jet-A.

Abstract The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen-based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This article introduces the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy-duty (HD) fuel cell electric commercial vehicles (FCEV).

Abstract Biodiesel is a suitable alternative to diesel because of its carbon neutrality, renewability, lubricity, and lower pollutant emissions. However, extensive research indicates higher oxides of nitrogen (NOx) emissions with biodiesel. A practical method to combat this problem is utilizing water and biodiesel as emulsions. The effect of biodiesel-water emulsion in high-pressure fuel injection systems is not fully explored in the existing literature. The present study addresses this research gap by utilizing biodiesel-water emulsions in a modified light-duty diesel engine. The governor-controlled injection system was adapted to a fully flexible electronic system capable of high-pressure injection. Unlike other literature studies, the fuel injection timings were optimized with biodiesel-water emulsions to maximize brake thermal efficiency (bte) at every load condition.