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The regulatory requirements to reduce both greenhouse gases and exhaust gas pollutants from heavy duty engines are driving new perspectives on the interaction between fuels and engines. Fuels that reliefs the burden on engine manufacturers to reach these goals are of particular interest. A low carbon fuel with a higher volatility and heating value than diesel is one such fuel that reduces engine-out emissions and carbon footprint from the entire hydrocarbon lifecycle (well-to-wheel) and improves fuel efficiency, which is a main enabler for gasoline compression ignition (GCI) technology. The present study investigated the potential of GCI technology by evaluating the performance of a low carbon high efficiency, high reactivity gasoline fuel in Doosan’s 6L medium duty diesel engine.

In this study, the combustion system of a light-duty compression ignition engine running on a market gasoline fuel with Research Octane Number (RON) of 91 was optimized using computational fluid dynamics (CFD) and Machine Learning (ML). This work was focused on optimizing the piston bowl geometry at two compression ratios (CR) (17 and 18:1) and this exercise was carried out at full-load conditions (20 bar indicated mean effective pressure, IMEP). First, a limited manual piston design optimization was performed for CR 17:1, where a couple of pistons were designed and tested. Thereafter, a CFD design of experiments (DoE) optimization was performed where CAESES, a commercial software tool, was used to automatically perturb key bowl design parameters and CONVERGE software was utilized to perform the CFD simulations. At each compression ratio, 128 piston bowl designs were evaluated.

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.

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).

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.

Cyclic variability in internal combustion engines (ICEs) arises from multiple concurrent sources, many of which remain to be fully understood and controlled. This variability can, in turn, affect the behavior of the engine resulting in undesirable deviations from the expected operating conditions and performance. Shot-to-shot variation during the fuel injection process is strongly suspected of being a source of cyclic variability. This study focuses on the shot-to-shot variability of injector needle motion and its influence on the internal nozzle flow behavior using diesel fuel. High-speed x-ray imaging techniques have been used to extract high-resolution injector geometry images of the sac, orifices, and needle tip that allowed the true dynamics of the needle motion to emerge. These measurements showed high repeatability in the needle lift profile across multiple injection events, while the needle radial displacement was characterized by a much higher degree of randomness.

The current study utilized 3-D computational fluid dynamics (CFD) combustion analysis to guide the development of a viable full load range combustion strategy in a light-duty gasoline compression ignition (GCI) engine. A higher reactivity gasoline that has a research octane number (RON) of 70 was used for the combustion strategy development. The engine has a geometric compression ratio of 14.5 with a piston bowl designed to accommodate different combustion strategies and injector spray patterns. Detailed combustion optimization was focused on 6 and 18 bar gross indicated mean effective pressure (IMEPg) at 1500 rpm through a Design of Experiments approach. Two different strategies were investigated: (a) a late triggering fuel injection with a wide spray angle (combustion strategy #1); and (b) an early triggering fuel injection with a narrow spray angle (combustion strategy #2).

In internal combustion engine computational fluid dynamics (CFD) simulations, uncertainties arise from various sources, such as estimates of model parameters, experimental boundary conditions, estimates of chemical kinetic rates, etc. These uncertainties propagate through the model and may result in discrepancies compared to experimental measurements. The relative importance of the various sources of uncertainty can be quantified by performing a sensitivity analysis. In this work, global sensitivity analysis (GSA) was applied to engine CFD simulations of a low-temperature combustion concept called gasoline compression ignition, to understand the influence of experimental measurement uncertainties from various sources on specific targets of interest-spray penetration, ignition timing, combustion phasing, combustion duration, and emissions. The sensitivity of these targets was evaluated with respect to imposed uncertainties in experimental boundary conditions and fuel properties.

Gasoline compression ignition (GCI) engines have been considered an attractive alternative to traditional spark ignition engines. Low octane gasoline fuel has been identified as a viable option for the GCI engine applications due to its longer ignition delay characteristics compared to diesel and in the volatility range of gasoline fuels. In this study, we have investigated the effect of different injection timings at part-load conditions using light naphtha stream in single cylinder engine experiments in the GCI combustion mode with injection pressure of 130 bar. A toluene primary reference fuel (TPRF) was used as a surrogate for the light naphtha in the engine simulations performed here. A physical surrogate based on the evaporation characteristics of the light naphtha has been developed and its properties have been implemented in the engine simulations.

It is well known that in-nozzle flow behavior can significantly influence the near-nozzle spray formation and mixing that in turn affect engine performance and emissions. This in-nozzle flow behavior can, in turn, be significantly influenced by fuel properties. The goal of this study is to characterize the behavior of two different fuels, namely, a straight-run naphtha that has an anti-knock index of 58 (denoted as “Full-Range Naphtha”) and n-dodecane, in a simulated multi-hole common-rail diesel fuel injector. Simulations were carried out using a fully compressible multi-phase flow representation based on the mixture model assumption with the Volume of Fluid method. Our previous studies have shown that the characteristics of internal and near-nozzle flow are strongly related to needle motion in both the along- and off-axis directions.

This research investigates the potential of gasoline compression ignition (GCI) to achieve low engine-out NOx emissions with high fuel efficiency in a heavy-duty diesel engine. The experimental work was conducted in a model year (MY) 2013 Cummins ISX15 heavy-duty diesel engine, covering a load range of 5 to 15 bar BMEP at 1375 rpm. The engine compression ratio (CR) was reduced from the production level of 18.9 to 15.7 without altering the combustion bowl design. In this work, four gasolines with research octane number (RON) ranging from 58 to 93 were studied. Overall, GCI operation resulted in enhanced premixed combustion, improved NOx-soot tradeoffs, and similar or moderately improved fuel efficiency compared to diesel combustion. A split fuel injection strategy was employed for the two lower reactivity gasolines (RON80 and RON93), while the RON60 and RON70 gasolines used a single fuel injection strategy.

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.

Direct injection compression ignition engines running on gasoline-like fuels have been considered an attractive alternative to traditional spark ignition and diesel engines. The compression and lean combustion mode eliminates throttle losses yielding higher thermodynamic efficiencies and the better mixing of fuel/air due to the longer ignition delay times of the gasoline-like fuels allows better emission performance such as nitric oxides (NOx) and particulate matter (PM). These gasoline-like fuels which usually have lower octane compared to market gasoline have been identified as a viable option for the gasoline compression ignition (GCI) engine applications due to its lower reactivity and lighter evaporation compared to diesel. The properties, specifications and sources of these GCI fuels are not fully understood yet because this technology is relatively new.

The experimental in-cylinder combustion process was compared with the numerical simualtion for naphtha fuel under conventional compression ignition (CI) and partially premixed combustion (PPC) conditions. The start of injection timing (SOI) with the single injection strategy was changed from late of −10 CAD aTDC to early of −40 CAD aTDC. The three-dimensional full cycle engine combustion simulation was performed coupling with gas phase chemical kinetics by the CFD code CONVERGE™. The flame index was used for evaluating the combustion evolution of premixed flame and diffusion flame. The results show that the flame index could be used as an indicator for in-cylinder homogeneity evaluation. Hydroperoxyl shows a similar distribution with the premixed combustion. Formaldehyde could be used as an indicator for low temperature combustion.

Investigating combustion characteristics of oxygenated gasoline and gasoline blended ethanol is a subject of recent interest. The non-linearity in the interaction of fuel components in the oxygenated gasoline can be studied by developing chemical kinetics of relevant surrogate of fewer components. This work proposes a new reduced four-component (isooctane, heptane, toluene, and ethanol) oxygenated gasoline surrogate mechanism consisting of 67 species and 325 reactions, applicable for dynamic CFD applications in engine combustion and sprays. The model introduces the addition of eight C1-C3 species into the previous model (Li et al; 2019) followed by extensive tuning of reaction rate constants of C7 - C8 chemistry. The current mechanism delivers excellent prediction capabilities in comprehensive combustion applications with an improved performance in lean conditions.

Partially premixed combustion (PPC) is an operating mode that lies between the conventional compression ignition (CI) mode and homogeneous charge compression ignition (HCCI) mode. The combustion in this mixed mode is complex as it is neither diffusion-controlled (CI mode) nor governed solely by chemical kinetics (HCCI mode). In this study, CFD simulations were performed to evaluate flame index, which distinguishes between zones having a premixed flame and non-premixed flame. Experiments performed in the optical engine supplied data to validate the model. In order to realize PPC, the start of injection (SOI) was fixed at −40 CAD (aTDC) so that a required ignition delay is created to premix air/fuel mixture. The reference operating point was selected to be with 3 bar IMEP and 1200 rpm. Naphtha with a RON of 77 and its corresponding PRF surrogate were tested. The simulations captured the general trends observed in the experiments well.

Reynolds-averaged Navier-Stokes (RANS) turbulence model has been used extensively for diesel engine simulations due to its computational efficiency and is expected to remain the workhorse computational fluid dynamics (CFD) tool for industry in the near future. Alternatively, large eddy simulations (LES) can potentially deal with complex flows and cover a large disparity of turbulence length scales, which makes this technique more and more attractive in the engine community. An n-dodecane spray flame (Spray A from Engine Combustion Network) was simulated using a dynamic structure LES model to understand the transient behavior of this turbulent flame. The liquid spray was treated with a traditional Lagrangian method and the gas-phase reaction was closed using a delta probability density function (PDF) combustion model. A 103-species skeletal mechanism was used for n-dodecane chemical kinetic model.

Gasoline compression ignition (GCI) pertains to high efficiency lean burn compression ignition with gasoline fuels, where ignition is controlled by mixture’s auto-ignition chemistry as well as local mixture strength. The presented GCI combustion strategy is based on a multi-mode combustion strategy at various operating conditions. This study presents a part of work on the development of an optimum combustion strategy at medium loading condition for commercial gasoline fuel with research octane number (RON) = 91. The single cylinder engine with a compression ratio (CR) = 16 features a centrally mounted multi-hole injector with a spark plug at a distance from the injector under shallow pent-roof combustion chamber design. The design of combustion chamber and piston was previously optimized based on CFD numerical analysis.

The current work utilizes computational fluid dynamics (CFD) simulations to assess the effects of different piston geometries in an active-type pre-chamber combustion engine fueled with methane. Previous works identified that the interaction of the jets with the main chamber flow and piston wall are key aspects for the local turbulent flame speed and overall burning duration. The combustion process is simulated with the G-equation model for flame propagation combined with the MZ-WSR model to determine the post-flame composition and to predict possible auto-ignition of the reactant mixture. Four setups were considered: two bowl-shaped and one flat piston, and one additional case of the flat piston with jets at wider jet angles to the cylinder axis. The results show that premature jet-wall interaction impacts the main chamber pressure build-up, turbulence, and burn rate.