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Low-temperature heat release (LTHR) in spark-ignited internal combustion engines is a critical step toward the occurrence of auto-ignition, which can lead to an undesirable phenomenon known as engine knock. Hence, correct predictions of LTHR are of utmost importance to improve the understanding of knock and enable techniques aimed at controlling it. While LTHR is typically obscured by the deflagration following the spark ignition, extremely late ignition timings can lead to LTHR occurrence prior to the spark, i.e., pre-spark heat release (PSHR). In this research, PSHR in a boosted direct-injection SI engine was numerically investigated using three-dimensional computational fluid dynamics (CFD). A hybrid approach was used, based on the G-equation model for representing the turbulent flame front and the multi-zone well-stirred reactor model for tracking the chemical reactions within the unburnt region.

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.

Accurate modeling of the internal flow and spray characteristics in fuel injectors is a critical aspect of direct injection engine design. However, such high-fidelity computational fluid dynamics (CFD) models are often computationally expensive due to the requirement of resolving fine temporal and spatial scales. This paper addresses the computational bottleneck issue by proposing a machine learning-based emulator framework, which learns efficient surrogate models for spatiotemporal flow distributions relevant for static coupling injection maps, namely total void fraction, velocity, and mass, within a design space of interest. Different design points involving variations of needle lift, fuel viscosity, and level of non-condensable gas in the fuel were explored in this study. An interpretable Bayesian learning strategy was employed to understand the effect of the design parameters on the void fraction fields at the exit of the injector orifice.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

A 500-hour test cycle has been used to evaluate the durability of a prototype high pressure common rail injection system operating up to 1800 bar with E10 gasoline. Some aspects of the original diesel based hardware design were optimized in order to accommodate an opposed-piston, two-stroke engine application and also to mitigate the impacts of exposure to gasoline. Overall system performance was maintained throughout testing as fueling rate and rail pressure targets were continuously achieved and no physical damage was observed in the low-pressure components. Injectors showed no deviation in their flow characteristics after exposure to gasoline and high resolution imaging of the nozzle spray holes and pilot valve assemblies did not indicate the presence of cavitation damage. The high pressure pump did not exhibit any performance degradation during gasoline testing and teardown analysis after 500 hours showed no evidence of cavitation erosion.

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.

In this study, three-dimensional large eddy simulations were performed to study the internal nozzle flow of the ECN Spray C diesel injector. Realistic nozzle geometry, full needle motion, and internal flow imaging data obtained from X-ray measurements were employed to initialize and validate the CFD model. The influence of injection pressure and fuel properties were investigated, and the effect of mesh size was discussed. The results agreed well with the experimental data of mass flow rate and correctly captured the flow structures inside the orifice. Simulations showed that the pressure drop near the sharp orifice inlet triggered flow separation, resulting in the ingestion of ambient gas into the orifice via a phenomenon known as hydraulic flip. At higher injection pressure, the pressure drop was more significant as the liquid momentum increased and the stream inertia was less prone to change its direction.

The occurrence of cavitation inside injectors is generally undesirable since it can cause material erosion and result in deviations from the expected injector performance. Previous numerical work employing an injector geometry measured with x-ray diagnostics and operating with a high-volatility straight-run gasoline (SRG) has shown that: (1) most of the cavitation is generally observed at low needle lifts, (2) needle motion is responsible for asymmetric structures in the internal flow as well as large pressure and velocity gradients that trigger phase transition at the orifice inlets, and (3) cavitation affects the injector discharge coefficient and distribution of injected fuel. To explore the potential for material damage within the injector orifices due to cavitation cloud collapse, the cavitation-induced erosion risk assessment (CIERA) tool has been applied for the first time to the realistic geometry of a heavy-duty injector using the CONVERGE software.

This study is a continuation of previous work assessing the robustness of a Cummins XPI common rail injection system operating with gasoline-like fuel. All the hardware from the original study was retained except for the high pressure pump head and check valves which were replaced due to cavitation damage. An additional 400 hour NATO cycle was run on the refurbished fuel system to achieve a total exposure time of 800 hours and detect any other significant failure modes. As in the initial investigation, fuel system parameters including pressures, temperatures and flow rates were logged on a test bench to monitor performance over time. Fuel and lubricant samples were taken every 50 hours to assess fuel consistency, metallic wear, and interaction between fuel and oil. High fidelity driving torque and flow measurements were made to compare overall system performance when operating with both diesel and light distillate fuel.

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.

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 necessity to study spray-wall interaction in internal combustion engines is driven by the evidence that fuel sprays impinge on chamber and piston surfaces resulting in the formation of wall films. This, in turn, may influence the air-fuel mixing and increase the hydrocarbon and particulate matter emissions. This work reports an experimental and numerical study on spray-wall impingement and liquid film formation in a constant volume combustion vessel. Diesel and n-heptane were selected as test fuels and injected from a side-mounted single-hole diesel injector at injection pressures of 120, 150, and 180 MPa on a flat transparent window. Ambient and plate temperatures were set at 423 K, the fuel temperature at 363 K, and the ambient densities at 14.8, 22.8, and 30 kg/m3. Simultaneous Mie scattering and schlieren imaging were carried out in the experiment to perform a visual tracking of the spray-wall interaction process from different perspectives.

Numerical modeling of fuel injection in internal combustion engines in a Lagrangian framework requires the use of a spray-wall interaction sub-model to correctly assess the effects associated with spray impingement. The spray impingement dynamics may influence the air-fuel mixing and result in increased hydrocarbon and particulate matter emissions. One component of a spray-wall interaction model is the splashed mass fraction, i.e. the amount of mass that is ejected upon impingement. Many existing models are based on relatively large droplets (mm size), while diesel and gasoline sprays are expected to be of micron size before splashing under high pressure conditions. It is challenging to experimentally distinguish pre- from post-impinged spray droplets, leading to difficulty in model validation.

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.

Combustion systems with advanced injection strategies have been extensively studied, but there still exists a significant fundamental knowledge gap on fuel spray interactions with the piston surface and chamber walls. This paper is meant to provide detailed data on spray-wall impingement physics and support the spray-wall model development. The experimental work of spray-wall impingement with non-vaporizing spray characterization, was carried out in a high pressure-temperature constant-volume combustion vessel. The simultaneous Mie scattering of liquid spray and schlieren of liquid and vapor spray were carried out. Diesel fuel was injected at a pressure of 1500 bar into ambient gas at a density of 22.8 kg/m3 with isothermal conditions (fuel, ambient, and plate temperatures of 423 K). A Lagrangian-Eulerian modeling approach was employed to characterize the spray-gas and spray-wall interactions in the CONVERGETM framework by means of a Reynolds-Averaged Navier-Stokes (RANS) formulation.

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.