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The internal combustion engine (ICE) has long dominated the heavy-duty sector by using liquid fossil fuels such as diesel but global commitments by countries and OEMs to reduce lifecycle carbon dioxide (CO2) emissions has garnered interest in alternative fuels like hydrogen. Hydrogen is a unique gaseous fuel that contains zero carbon atoms and has desired thermodynamic properties of high energy density per unit mass and high flame speeds. However, there are challenges related to its adoption to the heavy-duty sector as a drop-in fuel replacement for compression ignition (CI) diesel combustion given its high autoignition resistance. To overcome this fundamental barrier, engine manufacturers are exploring dual fuel combustion engines by substituting a fraction of the diesel fuel with hydrogen which enables fuel flexibility when there is no infrastructure and retrofittability to existing platforms.

Ammonia is a promising carbon-free alternative fuel for use in combustion systems. The main associated challenges are its relatively low reactivity and high NOx emissions compared to conventional fuels. Therefore, the combustion behaviour of ammonia and ammonia blends still needs to be better understood over a wide range of conditions. To this end, a comprehensive chemical kinetic mechanism C3MechV3.4, which is an update of C3MechV3.3, has been developed for improved predictions of the combustion of ammonia and ammonia blends. C3MechV3.4 has been validated using a wide range of experimental results for pure ammonia and ammonia/hydrogen, ammonia/methanol and ammonia/n-heptane blends. These validations target different data sets including ignition delay times, species profiles measured as a function of time, and/or temperature and laminar flame speeds over a wide range of conditions.

Gasoline-related factors that affect low-speed pre-ignition (LSPI) include the distillation properties of gasoline, manganese (Mn), ethanol, diesel fuel, detergent for aftermarket, and iron (Fe). The combined effect of Mn with ethanol or high calcium engine oil (high-Ca oil) has not been sufficiently clarified. Therefore, appropriate countermeasures for LSPI have not yet been implemented. To clarify the effect of the gasoline properties and additives on LSPI, engine tests were conducted using gasoline with different “PM Index” values, an indicator of distillation properties, different concentrations of Mn, ethanol, diesel fuel, detergent, Fe, and high-Ca oil. The results showed that the LSPI frequency tended to increase with the PM Index, Mn up to 60 ppm, diesel fuel up to 2 vol.%, and detergent up to three times the standard amount.

The modeling of fuel jet atomization is key in the characterization of Internal Combustion (IC) engines, and 3D Computational Fluid Dynamics (CFD) is a recognized tool to provide insights for design and control purposes. Multi-hole injectors with counter-bored nozzle are the standard for Gasoline Direct Injection (GDI) applications and the Spray-G injector from the Engine Combustion Network (ECN) is considered the reference for numerical studies, thanks to the availability of extensive experimental data. In this work, the behavior of the Spray-G injector is simulated in a constant volume chamber, ranging from sub-cooled (nominal G) to flashing conditions (G2), validating the models on Diffused Back Illumination and Phase Doppler Anemometry data collected in vaporizing inert conditions.

HTL is a kind of biodiesel converted from wet biowaste via hydrothermal liquefaction (HTL), which has drawn increasing attention in recent years due to its wide range of raw materials (algae, swine manure, and food processing waste). However, from the previous experiments done in a constant volume chamber, it was observed that the presence of 20% of HTL in the blend produced as much soot as pure diesel at in chamber environment oxygen ratio of 21%, and even more soot at low oxygen ratios. It was also observed that n-butanol addition could reduce the soot emission of diesel significantly under all tested conditions. In this work, the spray and combustion characteristics of HTL and diesel blends with n-butanol added were investigated in a constant volume chamber. The in-chamber temperature and oxygen ranged from 800 to 1200 K and 21% to 13%, respectively, covering both conventional and low-temperature combustion (LTC) regimes.

The SAE J300 classification was expanded to 0W-12 and 0W-8 viscosity grades in 2015, and lower viscosity engine oils have been studied in the industry. ILSAC GF-6B that will be introduced in 2020 will specify a 0W-16 requirement, but 0W-12 and 0W-8 grades are not considered. Because engine oil equal to or higher than the 0W-20 grade is recommended for almost all engines globally, suitable engine tests for 0W-12 and 0W-8 do not exist. Therefore, the Japan Automobile Manufacturers Association, Petroleum Association of Japan and Society of Automotive Engineers of Japan decided to establish new 0W-12 and 0W-8 low viscosity engine oil specifications. It is referred to as JASO GLV-1, and together with a new fuel economy engine test procedure, these engine oils for better fuel economy will be put on the Japanese market in 2019. Motoring friction torque tests are widely used to ascertain the friction reduction effect of fuel-economy engine oils.

Flash boiling has drawn much attention recently for its ability to enhance spray atomization and vaporization, while providing better fuel/air mixing for gasoline direct injection engines. However, the behaviors of flash boiling spray with multi-component fuels have not been fully discovered. In this study, isooctane, ethanol and the mixtures of the two with three blend ratios were chosen as the fuels. Measurements were performed with constant fuel temperature while ambient pressures were varied to adjust the superheated degree. Macroscopic and microscopic characteristics of flash boiling spray were investigated using Diffused Back-Illumination (DBI) imaging and Phase Doppler Anemometry (PDA). Comparisons between flash boiling sprays with single component and binary fuel mixtures were performed to study the effect of fuel properties on spray structure as well as atomization and vaporization processes.

The spray structure and vaporization processes of flash-boiling sprays in a constant volume chamber under a wide range of superheated conditions were experimentally investigated by a high speed imaging technique. The Engine Combustion Network’s Spray G injector was used. Four fuels including gasoline, ethanol, and gasoline-ethanol blends E30 and E50 were investigated. Spray penetration length and spray width were correlated to the degree of the superheated degree, which is the ratio of the ambient pressure to saturated vapor pressure (pa/ps). It is found that parameter pa/ps is critical in describing the spray transformation under flash-boiling conditions. Three distinct stages namely the slight flash-boiling, the transition flash-boiling, and the flare flash-boiling are identified to describe the transformation of spray structures.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NOx within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

The accurate modeling of fuel spray behavior under diesel engine conditions requires well-characterized boundary conditions. Among those conditions, the spray cone angle is important due to its impact on the spray mixing process, flame lift-off locations and subsequent soot formation. The spray cone angle is a highly dynamic variable, but existing correlations have been developed mainly for diesel fuels at quasi-steady state and relatively low injection pressures. The objective of this study was to develop spray cone angle correlations for both diesel and a light-end gasoline fuel over a wide range of diesel-engine operating conditions that are capable of capturing both the transient and quasi-steady state processes. Two important macroscopic characteristics of solid cone sprays, the spray cone angle and spray penetration, were measured using a single-hole heavy-duty injector using two fuels at diesel engine conditions in an optical constant volume vessel.

Light-duty China-6, which is among the most stringent vehicle exhaust emission standards globally, mandates the monitoring and reporting of real driving emissions (RDE) from July, 2023. In the process of regulation promulgation and verification, more than 300 RDE tests have been performed on over 50 China-5 and China-6 certified models. This technical paper endeavors to summarize the experience of RDE practice in China, and discuss the impacts of some boundary conditions (including vehicle dynamic parameters, data processing methods, hybrid propulsion and testing altitude) on the result of RDE measurement. In general, gasoline passenger cars confront few challenges to meet the upcoming RDE NOx requirement, but some China-5 certified samples, even powered by naturally-aspirated engines may have PN issues. PN emissions from some GDI-hybrid powertrain systems also need further reduction to meet China-6 RDE requirements.

Particulate matter emissions are becoming a big issue for GDI engines as the emission regulations being more stringent. Methanol has been considered to be an important alternative fuel to reduce soot emissions. To understand the effect of methanol addition on soot and polycyclic aromatic hydrocarbons (PAHs) formation, the 2-D distributions of soot volume fraction and different size PAHs relative concentrations in methanol/gasoline laminar diffusion flames were measured by TC-LII and PLIF techniques. The effect of methanol was investigated under the conditions of the same carbon flow and the same flame height. The methanol volume fraction was set as M0/20/40/60/80. The results showed that the natural luminescent flame lift-off height and soot lift-off height increases consistently with the increasing methanol content due to the increase of outlet velocity of fuel vapor.

Methanol has been regarded as a potential transportation fuel due to its advanced combustion characteristics and flexible source. However, it is suffering from misfire and high HC emissions problems under cold start and low load conditions either on methanol SI engine or on methanol/diesel dual fuel engine. Hydrogen is a potential addition that can enhance the combustion of methanol due to its high flammability and combustion stability. In the current work, the effect of hydrogen fraction on the laminar flame characteristics of methanol- hydrogen-air mixture under varied equivalence ratio was investigated on a constant volume combustion chamber system coupled with a schlieren setup. Experiments were performed over a wide range of equivalence ratio of the premixed charge, varied from 0.8 to 1.4, as well as different hydrogen fraction, 0%, 5%, 10%, 15% and 20% (n/n). All tests were carried out at fixed temperature and pressure of 400K and 0.1MPa.

CNG-diesel dual fuel combustion mode has been regarded as a practical operation strategy because it not only can remain high thermal efficiency but also make full use of an alternative fuel, natural gas. However, it is suffering from misfire and high HC emissions under cold start and low load conditions. As known, hydrogen has high flammability. Thus, a certain proportion of hydrogen can be added in the natural gas (named HCNG) to improve combustion performance. In this work, the effect of hydrogen volume ratio on combustion characteristics was investigated on an optically accessible single-cylinder CNG-diesel engine using a Phantom v7.3 color camera. HCNG was compressed into the tank under different hydrogen volume ratios varied from 0% to 30%, while the energy substitution rate of` HCNG remained at 70%.

Bio-butanol has been widely investigated as a promising alternative fuel. However, the main issues preventing the industrial-scale production of butanol is its relatively low production efficiency and high cost of production. Acetone-butanol-ethanol (ABE), the intermediate product in the ABE fermentation process for producing bio-butanol, has attracted a lot of interest as an alternative fuel because it not only preserves the advantages of oxygenated fuels, but also lowers the cost of fuel recovery for individual component during fermentation. If ABE could be directly used for clean combustion, the separation costs would be eliminated which save an enormous amount of time and money in the production chain of bio-butanol.

Bio-butanol has been considered as a promising alternative fuel for internal combustion engines due to its advantageous physicochemical properties. However, the further development of bio-butanol is inhibited by its high recovery cost and low production efficiency. Hence, the goal of this study is to evaluate two upstream products from different fermentation processes of bio-butanol, namely acetone-butanol-ethanol (ABE) and isopropanol-butanol-ethanol (IBE), as alternative fuels for diesel. The experimental comparison is conducted on a single-cylinder and common-rail diesel engine under various main injection timings (MIT) and equivalent engine load (EEL) conditions. The experimental results show that ABE and IBE significantly affect the combustion phasing. The start of combustion (SOC) is retarded when ABE and IBE are mixed with diesel. Furthermore, the ABE/IBE-diesel blends are more sensitive to the changes in MIT compared with that of pure diesel.

Soot emission, known as PM (particulate matter), is becoming a big issue for GDI engines as the emission regulations being increasingly stricter. It is found that ethanol, as an oxygenated bio-fuel, can reduce the soot emission when added to gasoline. In order to fully understand the effect of ethanol on soot reducing, the soot characteristics of ethanol/gasoline blends were studied on laminar diffusion flames. In this experiment, the blending ratio of ethanol/gasoline was set as E0/20/40/60/80. Considering the carbon content decreasing due to ethanol addition, carbon mass flow rate was remained constant. The two-dimensional distributions of soot volume fraction were measured quantitatively by using two-color laser induced incandescence technique. The results showed that ethanol is able to decrease the soot significantly, but the effect of ethanol on soot reduction is weakened with the increasing ethanol ratio.

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.

Fuels in the gasoline auto-ignition range (Research Octane Number (RON) > 60) have been demonstrated to be effective alternatives to diesel fuel in compression ignition engines. Such fuels allow more time for mixing with oxygen before combustion starts, owing to longer ignition delay. Moreover, by controlling fuel injection timing, it can be ensured that the in-cylinder mixture is “premixed enough” before combustion occurs to prevent soot formation while remaining “sufficiently inhomogeneous” in order to avoid excessive heat release rates. Gasoline compression ignition (GCI) has the potential to offer diesel-like efficiency at a lower cost and can be achieved with fuels such as low-octane straight run gasoline which require significantly less processing in the refinery compared to today’s fuels.