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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.

The pressing need to improve U.S. energy independence and reduce climate forcing fossil fuel emissions continues to motivate the development of high-efficiency internal combustion engines. A recent trend has been to downsize and turbocharge automotive spark-ignited engines coupled with direct fuel injection to improve engine efficiency while maintaining vehicle performance. In-line with recent trends in state-of-the-art engine technology, the focus of this study is lean and EGR dilute combustion in a gasoline direct injection (GDI) engine. The lean and dilute operating limits are defined by combustion stability typically in terms of COVIMEP so experiments were carried out on an automotive size single-cylinder research engine to characterize combustion stability. From a 20,000 cycle sequence analysis, lean operating conditions exhibit binary high- to low-IMEP cycle sequences. This may be because the cycle-to-cycle feedback mechanisms are physically limited to one or two cycles.

Dual-fuel combustion using liquid fuels with differing reactivity has been shown to achieve low-temperature combustion with moderate peak pressure rise rates, low soot and NOx emissions, and high indicated efficiency. Varying fractions of gasoline-type and diesel-type fuels enable operation across a range of low- and mid-load operating conditions. Expanding the operating range to cover the full operating range of a heavy-duty diesel engine, while maintaining the efficiency and emissions benefits, is a key objective. With dissimilar properties of the two utilized fuels lying at the heart of the dual-fuel concept, a tool for enabling this load range expansion is altering the properties of the two test fuels - this study focuses on altering the reactivity of the diesel fuel component. Tests were conducted on a 13L six-cylinder heavy-duty diesel engine modified to run dual-fuel combustion with port gasoline injection to supplement the direct diesel injection.

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.

Effectively obtaining physical parameters for vehicle dynamic model is the key to successfully performing any computer-based dynamic analysis, control strategy development or optimization. For a spring and lump mass vehicle model, which is a type of vehicle model widely used, its physical parameters include sprung mass, unsprung mass, inertial properties of the sprung mass, stiffness and damping coefficient of suspension and tire, etc. To minimize error, the paper proposes a method to estimate these parameters from vehicle modal parameters which are in turn obtained through full-car dynamic testing. To verify its effectiveness, a visual vehicle with a set of given parameters, build in the Adams(Automatic Dynamic Analysis of Mechanical Systems)/Car environment, is used to perform the dynamic testing and provide the testing data for the parameter estimation.

In recent years gasoline compression ignition (GCI) has been shown to offer an attractive combination of low criteria pollutants and high efficiency. However, enabling GCI across the full engine load map poses several challenges. At high load, the promotion of partial premixing of air and fuel is challenging due to the diminished ignition-delay characteristics at high temperatures, while under low load operations, maintaining combustion robustness is problematic due to the low reactivity of gasoline. Variable valve actuation (VVA) offers a means of addressing these challenges by providing flexibility in effective compression ratio. In this paper, the effects of VVA were studied at high loads in a prototype heavy-duty GCI engine using a gasoline research octane number (RON) 93 at a geometric compression ratio (CR) of 15.7. Both late intake valve closing (LIVC) and early intake valve closing (EIVC) strategies were analyzed as a measure to reduce the effective compression ratio.

This research numerically investigated the combustion process and exhaust emissions from a light-duty Gasoline Compression Ignition (GCI) engine operating at low load as well as medium load conditions using a commercial computational fluid dynamic (CFD) software Converge. The fuel injection strategies and thermal boundary conditions effects were examined to produce locally stratified and globally lean partially premixed compression ignition (PPCI) combustion. The effects of fuel injection pressure, number of injections, and the quantity of fuel injected in each pulse were examined and optimized for emissions and fuel consumption (FC) under the design constraints of 180 bar peak cylinder pressure (PCP) and 10 bar/° CA maximum pressure rise rate (MPRR).

Objective tools that can assess the demands associated with in-vehicle human machine interfaces (HMIs) could assist automotive engineers designing safer interaction. This paper presents empirical evidence supporting one objective assessment approach, which compares the demand associated with in-vehicle tasks to the demand associated with “benchmarking” or “comparison tasks”. In the presented study, there were two types of benchmarking tasks-a modified surrogate reference task (SuRT) and a delayed digit recall task (n-back task) - representing different levels of visual demand and cognitive demand respectively. Twenty-four participants performed these two types of benchmarking tasks as well as two radio tasks while driving a vehicle on a closed-loop test track. Response measures included physiological (heart rate), glance metrics, driving performance (steering entropy) and subjective workload ratings.

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).

Interest in natural gas as an alternative fuel source to petroleum fuels for light-duty vehicle applications has increased due to its domestic availability and stable price compared to gasoline. With its higher hydrogen-to-carbon ratio, natural gas has the potential to reduce engine out carbon dioxide emissions, which has shown to be a strong greenhouse gas contributor. For part-load conditions, the lower flame speeds of natural gas can lead to an increased duration in the inflammation process with traditional port-injection. Direct-injection of natural gas can increase in-cylinder turbulence and has the potential to reduce problems typically associated with port-injection of natural gas, such as lower flame speeds and poor dilution tolerance. A study was designed and executed to investigate the effects of direct-injection of natural gas at part-load conditions.

Understanding the short-lived structure of the plasma that forms between the electrodes of a spark plug is crucial to the development of improved ignition models for SI engines. However, measuring the amount of energy deposited in the gas directly and non-intrusively is difficult, due to the short time scales and small length scales involved. The breakdown of the spark gap occurs at nanosecond time scales, followed by an arc phase lasting a few microseconds. Finally, a glow discharge phase occurs over several milliseconds. It is during the arc and glow discharge phases that most of the heat transfer from the plasma to the electrodes and combustion gases occurs. Light emission can be used to measure an average temperature, but micron spatial resolution is required to make localized measurements.

The regulatory requirements to lower both greenhouse gases and criteria pollutants from heavy duty engines are driving new perspectives on the interaction between fuels and engines. Fuels that lower the burden on engine manufacturers to reach these goals may be of particular interest. Naphtha, a fuel with a higher volatility than diesel, but with the ability to be burned under traditional mixing-controlled combustion conditions is one such fuel. The higher volatility promotes fuel-air mixing and when combined with its typically lower aromatic content, leads to reduced soot emissions when compared directly to diesel. Naphtha also has potential to be less energy-intensive at the refinery level, and its use in transportation applications can potentially reduce CO2 emissions on a well-to-wheels basis.

Advanced internal combustion engines, although generally more efficient than conventional combustion engines, often encounter limitations in multi-cylinder applications due to variations in the combustion process. This study leverages experimental data from an inline 6-cylinder heavy-duty dual fuel engine equipped with a fully-flexible variable intake valve actuation system to study cylinder-to-cylinder variations in power production. The engine is operated with late intake valve closure timings in a dual-fuel combustion mode featuring a port-injection and a direct-injection fueling system in order to improve fuel efficiency and engine performance. Experimental results show increased cylinder-to-cylinder variation in IMEP as IVC timing moves from 570°ATDC to 610°ATDC, indicating an increasingly uneven fuel distribution between cylinders.

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.

The compression ratio is a strong lever to increase the efficiency of an internal combustion engine. However, among others, it is limited by the knock resistance of the fuel used. Natural gas shows a higher knock resistance compared to gasoline, which makes it very attractive for use in internal combustion engines. The current paper describes the knock behavior of two gasoline fuels, and specific incylinder blend ratios with one of the gasoline fuels and natural gas. The engine used for these investigations is a single cylinder research engine for light duty application which is equipped with two separate fuel systems. Both fuels can be used simultaneously which allows for gasoline to be injected into the intake port and natural gas to be injected directly into the cylinder to overcome the power density loss usually connected with port fuel injection of natural gas.

This paper describes the validation of a CFD code for mixture preparation in a direct injection hydrogen-fueled engine. The cylinder geometry is typical of passenger-car sized spark-ignited engines, with a centrally located injector. A single-hole and a 13-hole nozzle are used at about 100 bar and 25 bar injection pressure. Numerical results from the commercial code Fluent (v6.3.35) are compared to measurements in an optically accessible engine. Quantitative planar laser-induced fluorescence provides phase-locked images of the fuel mole-fraction, while single-cycle visualization of the early jet penetration is achieved by a high-speed schlieren technique. The characteristics of the computational grids are discussed, especially for the near-nozzle region, where the jets are under-expanded. Simulation of injection from the single-hole nozzle yields good agreement between numerical and optical results in terms of jet penetration and overall evolution.

Striving for sustainable transportation solutions, hydrogen is often identified as a promising energy carrier and internal combustion engines are seen as a cost effective consumer of hydrogen to facilitate the development of a large-scale hydrogen infrastructure. Driven by efficiency and emissions targets defined by the U.S. Department of Energy, a research team at Argonne National Laboratory has worked on optimizing a spark-ignited direct injection engine for hydrogen. Using direct injection improves volumetric efficiency and provides the opportunity to properly stratify the fuel-air mixture in-cylinder. Collaborative 3D-CFD and experimental efforts have focused on optimizing the mixture stratification and have demonstrated the potential for high engine efficiency with low NOx emissions. Performance of the hydrogen engine is evaluated in this paper over a speed range from 1000 to 3000 RPM and a load range from 1.7 to 14.3 bar BMEP.

The application of hydrogen (H2) as an internal combustion (IC) engine fuel has been under investigation for several decades. The favorable physical properties of hydrogen make it an excellent alternative fuel for fuel cells as well as IC engines and hence it is widely regarded as the energy carrier of the future. The potential of hydrogen as an IC engine fuel can be optimized by direct injection (DI) as it provides multiple degrees of freedom to influence the in-cylinder combustion processes and consequently the engine efficiency and exhaust emissions. This paper studies a single-hole nozzle and examines the effects of injection strategy on engine efficiency, combustion behavior and NOx emissions. The experiments for this study are done on a 0.5 liter single-cylinder research engine which is specifically designed for combustion studies and equipped with a cylinder head that allows side as well as central injector location.

Fuel effects on combustion characteristics, including combustion robustness/stability, for partially premixed compression ignition (PPCI) combustion was investigated using Delphi’s second-generation gasoline direct-injection compression ignition (Gen2 GDCI) multi-cylinder engine. Three high-reactivity RON 80 gasoline fuels were evaluated in this study. First, the effect of octane sensitivity (RON-MON) was investigated by comparing two non-oxygenated gasolines with octane sensitivities of 2.4 and 5.1. The octane sensitivity difference of the two fuels arose from different hydrocarbon compositions. Second, the effect of octane sensitivity origin was evaluated with two fuels having the same octane sensitivity of 2.4-one fuel was non-oxygenated, while the other one contains ethanol. The engine performance and emissions comparison was focused on part-load operations (1500 rpm, 6 bar IMEP and 800 rpm, 2 bar IMEP) that implemented PPCI low temperature combustion.