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Regulations have been established for the monitoring and reporting of greenhouse gas (GHG) emissions and fuel consumption from the transport sector. Low carbon fuels combined with new powertrain technologies have the potential to provide significant reductions in GHG emissions while decreasing the dependence on fossil fuel. In this study, a lean-burn ethanol-diesel dual-fuel combustion strategy has been used as means to improve upon the efficiency and emissions of a conventional diesel engine. Experiments have been performed on a 2.0 dm3 single cylinder heavy-duty engine equipped with port fuel injection of ethanol and a high-pressure common rail diesel injection system. Exhaust emissions and fuel consumption have been measured at a constant engine speed of 1200 rpm and various steady-state loads between 0.3 and 2.4 MPa net indicated mean effective pressure (IMEP).

Diesel engine cold-start problems include long cranking periods, hesitation and white smoke emissions. A better understanding of these problems is essential to improve diesel engine cold-start. In this study computer simulation model is developed for the steady state and transient cold starting processes in a single-cylinder naturally aspirated direct injection diesel engine. The model is verified experimentally and utilized to determine the key parameters that affect the cranking period and combustion instability after the engine starts. The behavior of the fuel spray before and after it impinges on the combustion chamber walls was analyzed in each cycle during the cold-start operation. The analysis indicated that the accumulated fuel in combustion chamber has a major impact on engine cold starting through increasing engine compression pressure and temperature and increasing fuel vapor concentration in the combustion chamber during the ignition delay period.

Main topics are the development and the build-up of an 18ton hybrid truck with a parallel hybrid drivetrain. With this truck it is possible to drive up to 3 kilometers in the pure electric driving mode. Presenter Andreas Eglseer, Engineering Center Steyr GmbH & Co. KG

After-treatment sensors are used in the ECU feedback control to calibrate the engine operating parameters. Due to their contact with exhaust gases, especially NOx sensors are prone to soot deposition with a consequent decay of their performance. Several phenomena occur at the same time leading to sensor contamination: thermophoresis, unburnt hydrocarbons condensation and eddy diffusion of submicron particles. Conversely, soot combustion and shear forces may act in reducing soot deposition. This study proposes a predictive 3D-CFD model for the analysis of the development of soot deposition layer on the sensor surfaces. Alongside with the implementation of deposit and removal mechanisms, the effects on both thermal properties and shape of the surfaces are taken in account. The latter leads to obtain a more accurate and complete modelling of the phenomenon influencing the sensor overall performance.

This study utilized a 4-valve engine under HCCI combustion conditions. Each side of the split intake port was fed independently with different temperatures and reactant compositions. Therefore, two stratification approaches were enabled: thermal stratification and compositional stratification. Argon was used as a diluent to achieve higher temperatures and stratify the in-cylinder temperature indirectly via a stratification of the ratio of specific heats (γ = cp/cv). Tests covered five operating conditions (including two values of A/F and two loads) and four stratification cases (including one homogeneous and three with varied temperature and composition). Stratifications of the reactants were expected to affect the combustion control and upper load limit through the combustion phasing and duration, respectively. The two approaches to stratification both affect thermal unmixedness. Since argon has a high γ, it reached higher temperatures through the compression stroke [1].

A computational and experimental study was performed to characterize the flow within a gasoline injector and the ensuing sprays. The computations included the effects of turbulence, cavitation, flash-boiling, compressibility, and the presence of non-condensible gases. The flow domain corresponded to the Engine Combustion Network's Spray G, an eight-hole counterbore injector operating in a variety of conditions. First, a rate tube method was used to measure the rate of injection, which was then used to define inlet boundary conditions for simulation. Correspondingly, injection under submerged conditions was simulated for direct comparison with experimental measurements of discharge coefficient. Next, the internal flow and external spray into pressurized nitrogen were simulated under the base spray G conditions. Finally, injection under flashing conditions was simulated, where the ambient pressure was below the vapor pressure of the fuel.

The control of NOx emissions is the greatest technical challenge in meeting future emission regulations for diesel engines. In this work, a modal analysis was performed for developing an engine control strategy to take advantage of fuel properties to minimize engine-out NOx emissions. This work focused on the use of EGR to reduce NOx while counteracting anticipated PM increases by using oxygenated fuels. A DaimlerChrysler OM611 CIDI engine for light-duty vehicles was controlled with a SwRI Rapid Prototyping Electronic Control System. Engine mapping consisted of sweeping parameters of greatest NOx impact, starting with OEM injection timing (including pilot injection) and EGR. The engine control strategy consisted of increased EGR and simultaneous modulation of both main and pilot injection timing to minimize NOx and PM emission indexes with constraints based on the impact of the modulation on BSFC, Smoke, Boost and BSHC.

A compact, lightweight compression-ignition engine designed for high fuel economy and low emissions was developed by ISUZU for the GM PNGV vehicle. This engine was the key component in the selected parallel hybrid vehicle powertrain for the 80 mpg fuel economy target. The base hardware was derived from a 1.7 Liter, 4-cylinder engine, and a three-cylinder version was created for the PNGV application. To achieve the required high efficiency, the engine used lightweight components thus minimizing weight and friction. To reduce exhaust emissions, electromechanical actuators were used for EGR, intake throttle, and turbocharger. Through careful application of these devices and combustion development, stringent engine out exhaust emission targets were also met.

Engine oil specifications have been changing since the invention of the automobile and the internal combustion engine. The industry associations that have played a key role in engine oil specification development have changed or evolved in fairly regular time intervals. The specifications, the tests behind the specifications, and the groups involved in shaping the specifications are discussed from a historical and present day perspective.

The paper describes the challenges and results achieved in developing a new high-speed Diesel combustion system capable of exceeding the imaginative threshold of 100 kW/l. High-performance, state-of-art prototype components from automotive diesel technology were provided in order to set-up a single-cylinder research engine demonstrator. Key design parameters were identified in terms boost, engine speed, fuel injection pressure and injector nozzle flow rates. In this regard, an advanced piezo injection system capable of 3000 bar of maximum injection pressure was selected, coupled to a robust base engine featuring ω-shaped combustion bowl and low swirl intake ports. The matching among the above-described elements has been thoroughly examined and experimentally parameterized.

In this multi-phase study, fuel and lubricant effects on stochastic preignition (SPI) were examined. First, the behavior of fuels for which SPI data had previously been collected were characterized in terms of their combustion and emissions behavior, and correlations between these characteristics and their SPI behavior were examined. Second, new SPI data was collected for a matrix of fuels that was constructed to test and confirm hypotheses that resulted from interpretation of the earlier data in the study and from data in open literature. Specifically, the extent to which the presence of heavy components in the fuel affected SPI propensity, and the extent to which flame initiation propensity affected SPI propensity, were examined. Finally, the interaction of fuels with lubricants expected to exhibit a range of SPI propensities was examined.

The goal of this study was to generate exhaust fast gas data that could be used to identify phenomena that occur before, during, and after stochastic preignition (SPI), also called low-speed preignition (LSPI), events. Crank angle resolved measurement of exhaust hydrocarbons, NO, CO, and CO2 was performed under engine conditions prone to these events. Fuels and engine operating strategies were varied in an attempt to understand similarities and differences in SPI-related behavior that may occur between them. Several different uncommon (typically occurring in less than 1% of engine cycles) features of the fast gas data were identified, and the correlations between them and SPI events were explored. Although the thresholds used to define and identify these observations were arbitrary, they provided a practical means of identifying behavior in the fast gas data and correlating it to SPI occurrence.

The unsteady flow fields behind two different automobile outside side rear view mirrors were examined experimentally in order to obtain a comprehensive data base for the validation of the ongoing computational investigation effort to predict the aero-acoustic noise due to the outside rear view mirrors. This study is part of a larger scheme to predict the aero-acoustic noise due to various external components in vehicles. To aid with the characterization of this complex flow field, mean and unsteady surface pressure measurements were undertaken in the wake of two mirror models. Velocity measurements with particle image velocimetry were also conducted to develop the mean velocity field of the wake. Two full-scale mirror models with distinctive geometrical features were investigated.

ORVR (Onboard Refueling Vapor Recovery) canisters trap vapors during normal operations of a vehicle's engine, and during refueling. This study evaluates the relative risks involved should a canister rupture in a crash. A canister impactor was developed to simulate real-world impacts and to evaluate the canisters' rupture characteristics. Numerous performance aspects of canisters were evaluated: the energy required to rupture a canister; the spread of carbon particles following rupture; the ease of ignition of vapor-laden particles; the vapor concentration in the area of ruptured, vapor-laden canisters; and the potential of crashes to rupture and ignite canisters. Results from these five items were combined into a risk analysis.

Carbon, hydrogen and oxygen are major elements in vehicle fuels. Knowledge of fuels elemental composition is helpful in addressing its performance characteristics. Carbon, hydrogen and oxygen composition is an important parameter in engine calibration affecting vehicle performance, emissions and fuel economy. Biodiesel, a fuel comprised of mono-alkyl esters of long-chain fatty acids also known as Fatty Acid Methyl Esters(FAME), derived from vegetable oils or animal fats, has become an important commercial marketplace automotive fuel in the United States (US) and around the world over last few years. FAME biodiesels have many chemical and physical property differences compared to conventional petroleum based diesel fuels. Also, the properties of biodiesel vary based on the feedstock chosen for biodiesel production. One of the key differences between petroleum diesel fuels and biodiesel is the oxygen content.

A Soot-NOx Trap (SNT) is a combinatorial aftertreatment device intended to decrease both particulate and NOx emissions simultaneously. A system-level Soot-NOx Trap model was developed by adding Lean NOx Trap kinetics to a 1D Diesel Particulate Filter model. The hybrid model was validated against each parent model for the limiting cases, then exercised to investigate the interacting redox behavior. Modulations in temperature and exhaust air-fuel ratio were investigated for their ability to facilitate particulate oxidation and NOx reduction in the trap.

Several predictive equations based on the chemical composition of gasoline have been shown to estimate the particulate emissions of light-duty, internal combustion engine (ICE) powered vehicles and are reviewed in this paper. Improvements to one of them, the PEISimDis equation are detailed herein. The PEISimDis predictive equation was developed by General Motor’s researchers in 2022 based on two laboratory gas chromatography (GC) analyses; Simulated Distillation (SimDis), ASTM D7096 and Detailed Hydrocarbon Analysis (DHA), ASTM D6730. The DHA method is a gas chromatography mass spectroscopy (GC/MS) methodology and provides the detailed speciation of the hundreds of hydrocarbon species within gasoline. A DHA’s aromatic species from carbon group seven through ten plus (C7 – C10+) can be used to calculate a Particulate Evaluation Index (PEI) of a gasoline, however this technique takes many hours to derive because of its long chromatography analysis time.

The introduction of new light-duty vehicle emission limits to comply under real driving conditions (RDE) is pushing the diesel engine manufacturers to identify and improve the technologies and strategies for further emission reduction. The latest technology advancements on the after-treatment systems have permitted to achieve very low emission conformity factors over the RDE, and therefore, the biggest challenge of the diesel engine development is maintaining its competitiveness in the trade-off “CO2-system cost” in comparison to other propulsion systems. In this regard, diesel engines can continue to play an important role, in the short-medium term, to enable cost-effective compliance of CO2-fleet emission targets, either in conventional or hybrid propulsion systems configuration. This is especially true for large-size cars, SUVs and light commercial vehicles.

Economic market forces and increasing environmental awareness of gasoline have led to interest in developing alternatives to gasoline, and extending the current global supply for transportation fuels. One viable strategy is the use of alternative alcohol fuels for combustion engines, with ethanol and methanol in various concentration ranges proposed and in-use. Utilizing and citing data from this review, a comprehensive overview of the materials selection and engineering challenges facing metals, plastics and elastomers are presented. The engineering approach and solution-sets discussed will focus on production feasibility and implementation. The effects from the fuel chemistry and quality of fuel ethanol produced on the related vehicle components are discussed.

Internal combustion engines (ICEs) exhaust emissions, particularly nitrogen oxides (NOx), have become a growing environmental and health concern. The biggest challenge for contemporary ICE industry is the development of clean ICEs, and the use of advanced design tools like Computational Fluid Dynamics (CFD) simulation is paramount to achieve this goal. In particular, the development of aftertreatment systems like Selective Catalyst Reduction (SCR) is a key step to reduce NOx emissions, and accurate and efficient CFD models are essential for its design and optimization. In this work, we propose a novel 3D-CFD methodology, which uses a Machine Learning (ML) approach as a surrogate model for the SCR catalyst chemistry, which aims to enhance accuracy of the simulations with a moderate computational cost. The ML approach is trained on a dataset generated from a set of 1D-CFD simulations of a single channel of an SCR catalyst.