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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 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.

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.

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

Higher carbon number alcohols offer an opportunity to meet the Renewable Fuel Standard (RFS2) and improve the energy content, petroleum displacement, and/or knock resistance of gasoline-alcohol blends from traditional ethanol blends such as E10 while maintaining desired and regulated fuel properties. Part II of this paper builds upon the alcohol selection, fuel implementation scenarios, criteria target values, and property prediction methodologies detailed in Part I. For each scenario, optimization schemes include maximizing energy content, knock resistance, or petroleum displacement. Optimum blend composition is very sensitive to energy content, knock resistance, vapor pressure, and oxygen content criteria target values. Iso-propanol is favored in both scenarios' suitable blends because of its high RON value.

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 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.

An experimental study and analysis was conducted to investigate cold start robustness of an ethanol flex-fuel spark ignition (SI) direct injection (DI) engine. Cold starting with ethanol fuel blends is a known challenge due to the fuel characteristics. The program was performed to investigate strategies to reduce the enrichment requirements for the first firing cycle during a cold start. In this study a single-cylinder SIDI research engine was used to investigate gasoline and E85 fuels which were tested with three piston configurations (CR11F, CR11B, CR15.5B - which includes changes in compression ratio and piston geometry), at three intake cam positions (95, 110, 125 °aTDC), and two fuel pressures (low: 0.4 MPa and high: 3.0 MPa) at 25°C±1°C engine and air temperature, for the first cycle of an engine start.

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.

Low temperature combustion through in-cylinder blending of fuels with different reactivity offers the potential to improve engine efficiency while yielding low engine-out NOx and soot emissions. A Navistar MaxxForce 13 heavy-duty compression ignition engine was modified to run with two separate fuel systems, aiming to utilize fuel reactivity to demonstrate a technical path towards high engine efficiency. The dual-fuel engine has a geometric compression ratio of 14 and uses sequential, multi-port-injection of a low reactivity fuel in combination with in-cylinder direct injection of diesel. Through control of in-cylinder charge reactivity and reactivity stratification, the engine combustion process can be tailored towards high efficiency and low engine-out emissions. Engine testing was conducted at 1200 rpm over a load sweep.

Estimating internal residual during engine operation is essential to robust control during startup, steady state, and transient operation. Internal residual has a significant effect on combustion flame propagation, combustion stability and emissions. Accurate residual estimate also provides a better foundation for optimizing open loop fuel control during startup, while providing a basis for reducing emissions during closed loop control. In this paper we develop an improved model to estimate residual gas fraction by means of isolation and characterization of the physical processes in the gas exchange. Examining existing residuals model as the base, we address their deficiencies making changes to appropriate terms to the model. Existing models do not work well under wide angle dual independent cam phasing. The improved residual estimation model is not limited by the initial data set used for its calibration and does not need cylinder pressure data.

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.

Reactivity Controlled Compression Ignition (RCCI) is a promising dual-fuel Low Temperature Combustion (LTC) mode with significant potential for reducing NOx and particulate emissions while improving or maintaining thermal efficiency compared to Conventional Diesel Combustion (CDC) engines. The large reactivity difference between diesel and Natural Gas (NG) fuels provides a strong control variable for phasing and shaping combustion heat release. In this work, the Brake Thermal Efficiencies (BTE), emissions and combustion characteristics of a light duty 1.9L, four-cylinder diesel engine operating in single fuel diesel mode and in Diesel-NG RCCI mode are investigated and compared. The engine was operated at speeds of 1300 to 2500 RPM and loads of 1 to 7 bar BMEP. Operation was limited to 10 bar/deg Maximum Pressure Rise Rate (MPRR) and 6% Coefficient of Variation (COV) of IMEP.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.

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.

The favorable physical properties of hydrogen (H2) make it an excellent alternative fuel for internal combustion (IC) engines and hence it is widely regarded as the energy carrier of the future. Hydrogen direct injection provides multiple degrees of freedom for engine optimization and influencing the in-cylinder combustion processes. This paper compares the results in the mixture formation and combustion behavior of a hydrogen direct-injected single-cylinder research engine using two different injector locations as well as various injector nozzle designs. For this study the research engine was equipped with a specially designed cylinder head that allows accommodating a hydrogen injector in a side location between the intake valves as well as in the center location adjacent to the spark plug.

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.

A wide variety of spray models and their associated sub-models exist to assist with numerical spray development studies in the many applicable areas viz., turbines, internal combustion engines etc. The accuracy of a simulation when compared to the experiments varies, as these models chosen are varied. Also, the computational grid plays a crucial role in model correctness; a grid-converged CFD study is more valuable and assists in proper validation at later stages. Of primary relevance to this paper are the combustion models for a grid-converged Lagrangian spray modeling scenario. CONVERGE CFD code is used for simulation of split injection diesel (n-heptane) sprays and a structured methodology, using RNG k-ε turbulence model, is followed to obtain a grid-converged solution for the key Computational Fluid Dynamics (CFD) parameters viz., grid size, injected parcels and spray break-up time constant.

Water spray characterization of a multi-hole injector under pressures and temperatures representative of engine-relevant conditions was investigated for naturally aspirated and boosted engine conditions. Experiments were conducted in an optically accessible pressure vessel using a high-speed Schlieren imaging to visualize the transient water spray. The experimental conditions included a range of injection pressures of 34, 68, and 102 bar and ambient temperatures of 30 - 200°C, which includes flash-boiling and non-flash-boiling conditions. Transient spray tip penetration and spray angle were characterized via image processing of raw Schlieren images using Matlab code. The CONVERGE CFD software was used to simulate the water spray obtained experimentally in the vessel. CFD parameters were tuned and validated against the experimental results of spray profile and spray tip penetration measured in the combustion vessel (CV).

High-speed spray-to-spray liquid impingement could be an effective phenomenon for the spray propagation and droplet vaporization. To achieve higher vaporization efficiency, impingement from two-hole nozzles is analyzed in this paper. This paper focuses on investigating vaporization mechanism as a function of the impingement location and the collision breakup process provided by two-hole impinging jet nozzles. CFD (Computational Fluid Dynamics) is adopted to do simulation. Lagrangian model is used to predict jet-to-jet impingement and droplet breakup conditions while KH-RT breakup and O'Rourke collision models are implemented for the simulation. The paper includes three parts: First, a single spray injected into an initially quiescent constant volume chamber using the Lagrangian approach is simulated to identify the breakup region, which will be considered as a reference to study two-hole impinging jet nozzles. Lagrangian simulation results would be validated via experimental results.