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Gasoline compression ignition (GCI) has been shown to offer benefits in the NOx-soot tradeoff over conventional diesel combustion while still achieving high fuel efficiency. However, due to gasoline’s low reactivity, it is challenging for GCI to attain robust ignition and stable combustion under cold operating conditions. Building on previous work to evaluate glow plug-assisted GCI combustion at cold idle, this work evaluates the use of a spark plug to assist combustion. The closed-cycle 3-D CFD model was validated against GCI test results at a compression ratio of 17.3 during extended cold idle operation under laboratory-controlled conditions. A market representative, ethanol-free, gasoline (RON92, E0) was used in both the experiment and the numerical analysis. Spark-assisted simulations were performed by incorporating an ignition model with the spark energy required for stable combustion at cold start.

In this last decade, non-destructive X-ray measurement techniques have provided unique insights into the internal surface and flow characteristics of automotive injectors. This has in turn contributed to enhancing the accuracy of Computational Fluid Dynamics (CFD) models of these critical injection system components. By employing realistic injector geometries in CFD simulations, designers and modelers have identified ways to modify the injectors’ design to improve their performance. In recent work, the authors investigated the occurrence of cavitation in a heavy-duty multi-hole diesel injector operating with a high-volatility gasoline-like fuel for gasoline compression ignition applications. They proposed a comprehensive numerical study in which the original diesel injector design would be modified with the goal of suppressing the in-nozzle cavitation that occurs when gasoline fuels are used.

The combustion system of a heavy-duty diesel engine operated in a gasoline compression ignition mode was optimized using a CFD-based response surface methodology and a machine learning genetic algorithm. One common dataset obtained from a CFD design of experiment campaign was used to construct response surfaces and train machine learning models. 128 designs were included in the campaign and were evaluated across three engine load conditions using the CONVERGE CFD solver. The design variables included piston bowl geometry, injector specifications, and swirl ratio, and the objective variables were fuel consumption, criteria emissions, and mechanical design constraints. In this study, the two approaches were extensively investigated and applied to a common dataset. The response surface-based approach utilized a combination of three modeling techniques to construct response surfaces to enhance the performance of predictions.

Optical soot pyrometry is a mature experimental technique that has been applied to a broad range of combustion systems for measuring soot temperature and concentration. Even though the method is widely used and well documented, the line of sight nature of the technique makes the interpretation of its results challenging. Notably, gradients in temperature and soot concentration along the line of sight or across the field of view can introduce significant levels of uncertainty in the results. This paper presents a numerical study where the signal from the experimental two-color pyrometry technique in a marine diesel engine reference experiment is reconstructed employing computational fluid dynamics (CFD) and a detailed Line-by-Line (LBL) spectral radiation model. The analysis is aimed at qualitatively supporting interpretability of experimental observations.

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.

Achieving robust ignitability for compression ignition of diesel engines at cold conditions is traditionally challenging due to insufficient fuel vaporization, heavy wall impingement, and thick wall films. Gasoline compression ignition (GCI) has shown the potential to offer an enhanced NOx-particulate matter tradeoff with diesel-like fuel efficiency, but it is unknown how the volatility and reactivity of the fuel will affect ignition under very cold conditions. Therefore, it is important to investigate the impact of fuel physical and chemical properties on ignition under pressures and temperatures relevant to practical engine operating conditions during cold weather. In this paper, 0-D and 3-D computational fluid dynamics (CFD) simulations of GCI combustion at cold conditions were performed.

State of the art high-pressure fuel injectors offer the ability to inject multiple times per cycle, and can reach very low fuel amounts per injection event. This behaviour allows the application of pilot injections in diesel engine applications or dual fuel engines. In both diesel and dual fuel engines, the amount of pilot fuel affects the engine efficiency. The understanding of the underlying ignition mechanism of the pilot fuel is required to optimize injection parameters and the engines’ fuel consumption. The present work focuses on the differences of ignition mechanisms between long and short injections. The investigation has been performed numerically, using CFD with a well-proven combustion model. The setup used employs a well characterized single orifice injector, injecting into a high temperature, pressurized environment with a composition of 15% oxygen.

Large Eddy Simulations (LES) and tracer-based Laser-Induced Fluorescence (LIF) measurements were performed to study the dynamics of fuel wall-films on the piston top of an optically accessible, four-valve pent-roof GDI research engine for a total of eight operating conditions. Starting from a reference point, the systematic variations include changes in engine speed (600; 1,200 and 2,000 RPM) and load (1000 and 500 mbar intake pressure); concerning the fuel path the Start Of Injection (SOI=360°, 390° and 420° CA after gas exchange TDC) as well as the injection pressure (10, 20 and 35 MPa) were varied. For each condition, 40 experimental images were acquired phase-locked at 10° CA intervals after SOI, showing the wall-film dynamics in terms of spatial extent, thickness and temperature.

In this study, a novel 3D-CFD combustion model employing Flamelet Generated Manifolds (FGM) for dual fuel combustion was developed. Validation of the platform was carried out using recent experimental results from an optically accessible Rapid Compression Expansion Machine (RCEM). Methane and n-dodecane were used as model fuels to remove any uncertainties in terms of fuel composition. The model used a tabulated chemistry approach employing a reaction mechanism of 130 species and 2399 reactions and was able to capture non-premixed auto ignition of the pilot fuel as well as premixed flame propagation of the background mixture. The CFD model was found to predict well all phases of the dual fuel combustion process: I) the pilot fuel ignition delay, II) the Heat Release Rate of the partially premixed conversion of the micro pilot spray with entrained methane/air and III) the sustained background mixture combustion following the consumption of the spray plume.

Fuel stratification effects on the combustion and emissions behaviors for partially premixed compression ignition (PPCI) combustion of a high reactivity gasoline (research octane number of 80) was investigated using the third generation Gasoline Direct-Injection Compression Ignition (Gen3 GDCI) multi-cylinder engine. The PPCI combustion mode was achieved through a double injection strategy. The extent of in-cylinder fuel stratification was tailored by varying the start of second fuel injection timing (SOIsecond) while the first fuel injection event was held constant and occurred during the intake stroke. Based on the experimental results, three combustion characteristic zones were identified in terms of the SOIsecond - CA50 (crank angle at 50% cumulative heat release) relationship: (I) no response zone (HCCI-like combustion); (II) negative CA50 slope zone: (early PPCI mode); and (III) positive CA50 slope zone (late PPCI mode).

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.

Large Eddy Simulation (LES) of premixed turbulent combustion in a confined cylinder setup at engine relevant conditions has been carried out for three different initial turbulence intensities, mimicking different flame propagation regimes. Direct Numerical Simulation (DNS) of the setup under investigation provides the reference data to be compared against. The DNS fields have been filtered on the LES grid and are used as initial conditions for the LES at onset of combustion, guaranteeing a direct comparability of the single realizations between the modeled and reference data. Two different combustion models, the G-Equation and CMC-premixed (Conditional Moment Closure) are compared with respect to their predictive capabilities as well as their usability and computational cost. While the G-Equation is a widely adopted approach for industrial applications and usually relies on a tunable turbulent flame speed closure, the novel LES-CMC comes as a tuning parameter free model.

Most of the phenomena that occur during the high pressure cycle of a spark ignition engine are highly influenced by the gas temperature, turbulence intensity and turbulence length scale inside the cylinder. For a pre chamber gas engine, the small volume and the high surface-to-volume ratio of the pre chamber increases the relative significance of the gas-to-wall heat losses, the early flame kernel development and the wall induced quenching; all of these phenomena are associated up to a certain extent with the turbulence and temperature field inside the pre chamber. While three-dimensional (3D) computational fluid dynamics (CFD) simulations can capture complex phenomena inside the pre chamber with high accuracy, they have high computational cost. Quasi dimensional models, on the contrary, provide a computationally inexpensive alternative for simulating multiple operating conditions as well as different geometries.

Dual-fuel combustion is an attractive approach for utilizing alternative fuels such as natural gas in compression-ignition internal combustion engines. In this approach, pilot injection of a more reactive fuel provides a source of ignition for the premixed natural gas/air. The overall performance combines the high efficiency of a compression-ignition engine with the relatively low emissions associated with natural gas. However the combustion phenomena occurring in dual-fuel engines present a challenge for existing turbulent combustion models because, following ignition, flame propagates through a partially-reacted and inhomogeneous mixture of the two fuels. The objective of this study is to test a new modelling formulation that combines the ability of the Conditional Moment Closure (CMC) approach to describe autoignition of fuel sprays with the ability of the G-equation approach to describe the subsequent flame propagation.

The interaction of turbulent premixed methane combustion with the surrounding flow field can be studied using optically accessible test rigs such as a rapid compression expansion machine (RCEM). The high flexibility offered by such a test rig allows its operation at various thermochemical conditions at ignition. However, limitations inherent to such test rigs due to the absence of an intake stroke do not allow turbulence production as found in IC-engines. Hence, means to introduce turbulence need to be implemented and the relevant turbulence quantities have to be identified in order to enable comparability with engine relevant conditions. A dedicated high-pressure direct injection of air at the beginning of the compression phase is considered as a measure to generate adjustable turbulence intensities at spark timing and during the early flame propagation.

Engines with reduced emissions and improved efficiency are of high interest for road transport. However, achieving these two goals is challenging and various concepts such as PFI/DI/HCCI/PCCI are explored by engine manufacturers. The computational fluid dynamics is becoming an integral part of modern engine development programme because this method provides access to in-cylinder flow and thermo-chemical processes to develop a closer understanding to tailor tumble and swirling motions to construct green engines. The combustion modelling, its accuracy and robustness play a vital role in this. Out of many modelling methods proposed in the past flamelet based methods are quite attractive for SI engine application. In this study, FlaRe (Flamelets revised for physical consistencies) approach is used to simulate premixed combustion inside a gasoline PFI single-cylinder, four-stroke SI engine. This approach includes a parameter representing the effects of flame curvature on the burning rate.

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.

Modern Diesel engines have become ever more complex systems with many degrees of freedom. Simultaneously, with increasing computational power, simulations of engines have become more popular, and can be used to find the optimum set up of engine operation parameters which result in the desired point in the emission-efficiency trade off. With increasing number of engine operation parameter combinations, the number of calculations increase exponentially. Therefore, adequate models for combustion and emissions with limited calculation costs are required. For obvious reasons, the accuracy of the ignition timing is a key point for the following combustion and emission model quality. Furthermore, the combination of mixing and chemical processes during the ignition delay is very challenging to model in a fast way for a wide range of operation conditions.

This study investigates n-dodecane split injections of “Spray A” from the Engine Combustion Network (ECN) using two different turbulence treatments (RANS and LES) in conjunction with a Conditional Moment Closure combustion model (CMC). The two modeling approaches are first assessed in terms of vapor spray penetration evolutions of non-reacting split injections showing a clearly superior performance of the LES compared to RANS: while the former successfully reproduces the experimental results for both first and second injection events, the slipstream effect in the wake of the first injection jet is not accurately captured by RANS leading to an over-predicted spray tip penetration of the second pulse. In a second step, two reactive operating conditions with the same ambient density were investigated, namely one at a diesel-like condition (900K, 60bar) and one at a lower temperature (750K, 50bar).