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Polymer electrolyte membrane (PEM) fuel cells will play a crucial role in the decarbonization of the transport sector, in particular for heavy duty applications. However, performance and durability of PEMFC stacks is still a concern especially when operated under high power density conditions, as required in order to improve the compactness and to reduce the cost of the system. In this context, the optimization of the geometry of hydrogen and air distributors represents a key factor to improve the distribution of the reactants on the active surface, in order to guarantee a proper water management and avoiding membrane dehydration.

The target of the upcoming automotive emission regulations is to promote a fast transition to near-zero emission vehicles. As such, the range of ambient and operating conditions tested in the homologation cycles is broadening. In this context, the proposed work aims to thoroughly investigate the potential of post-oxidation phenomena in reducing the light-off time of a conventional three-way catalyst. The study is carried out on a turbocharged four-cylinder gasoline engine by means of experimental and numerical activities. Post oxidation is achieved through the oxidation of unburned fuel in the exhaust line, exploiting a rich combustion and a secondary air injection dedicated strategy. The CFD methodology consists of two different approaches: the former relies on a full-engine mesh, the latter on a detailed analysis of the chemical reactions occurring in the exhaust line.

The work investigates the effect of different Iron and Manganese contents in ad-hoc cast specimens made from recycled EN AC-43200 alloy. Tensile tests and metallographic analyses coupled with energy dispersive X-ray spectroscopy measurements are carried out to elucidate the interplay between the microstructure and the quasi-static properties of the Aluminium-Silicon alloy under investigation. A strong correlation between the composition and morphology of Fe/Mn -based intermetallic precipitates and tensile properties is demonstrated. Moreover, it is found that specific intermetallic phases are present only for certain, relative and/or absolute contents of Fe and Mn.

Methanol has recently emerged as a promising fuel for internal combustion engines due to its multiple carbon-neutral production routes and advantageous properties when combusting. Methanol is intrinsically more suitable for spark-ignition (SI) operation thanks to its high octane number, but its potential in heavy-duty applications also encourages engine manufacturers in this field to retrofit their existing compression-ignition products into methanol/diesel dual-fuel (DF) operation. For both SI operation and DF operation, injecting methanol into the engine’s intake path at low pressure is a relatively simple and robust method to introduce methanol into the cylinders. However, the much higher heat of vaporization (HoV) of methanol compared to conventional SI fuels like gasoline can be a double-edged sword.

Turbulent Jet Ignition (TJI) represents one of the most effective solution to improve engine efficiency and to reduce fuel consumption and pollutants emission. Even if active prechambers allow a precise control of the air-fuel ratio close to the spark plug and the ignition of ultra-lean mixtures in the main chamber, passive prechambers represent a more attractive solution especially for passenger cars thanks to their simpler and cheaper configuration, which is easier to integrate into existing engines. The main challenge of passive prechambers is to find a geometry that allows to use TJI in the whole engine map, especially in the low load/speed region, without the use of a second sparkplug in the main chamber. To this end, this works reports a CFD study coupled with an experimental investigation to overcome this limitation.

In the upcoming decade sustainable powertrain technologies will seek for market entrance in the transport sector. One promising solution is the utilization of dual-fuel engines using renewable methanol ignited by a pilot diesel fuel. This approach allows the displacement of a significant portion of fossil diesel, thereby reducing greenhouse gas emissions. Additionally, this technology is, next to newbuilds, suited for retrofitting existing engines, while maintaining high efficiencies and lowering engine-out emissions. Various researchers have experimentally tested the effects of replacing diesel by methanol and have reported different boundaries for substituting diesel by methanol, including misfire, partial burn, knock and pre-ignition. However, little research has been conducted to explore ways to extend these substitution limits.

The use of renewable fuels such as hydrogen and methanol in marine engines is a promising way to reduce greenhouse gas emissions from maritime transport. Hydrogen and methanol can be used as the main fuel in dual-fuel engines. However, the co-combustion of hydrogen-diesel and methanol-diesel needs to be carefully studied. In the present work, the ignition delay (ID) and laminar burning velocity (LBV) for pilot-ignited dual fuel engine operation with hydrogen or methanol are studied. A constant volume batch reactor numerical setup is used in the open source Cantera code to calculate the effect of the premixed fuel on the ID of the pilot fuel. Also, Cantera is used to simulate a freely-propagating, adiabatic, 1-D flame to estimate the laminar flame speed of either hydrogen or methanol and how it is affected by the presence of pilot fuel. First, suitable chemical kinetic schemes are selected based on experimental data collected from the literature.

In the rapidly changing scenario of the energy transition, data-driven tools for kinetic mechanism development and testing can greatly support the evaluation of the combustion properties of new potential e-fuels. Despite the effectiveness of kinetic mechanism generation and optimization procedures and the increased availability of experimental data, integrated methodologies combining data analysis, kinetic simulations, chemical lumping, and kinetic mechanism optimization are still lacking. This paper presents an integrated workflow that combines recently developed automated tools for kinetic mechanism development and testing, from data collection to kinetic model reduction and optimization. The proposed methodology is applied to build a consistent, efficient, and well-performing kinetic mechanism for the combustion of oxymethylene ethers (OMEs), which are promising synthetic e-fuels for transportation.

In future decarbonized scenarios, hydrogen is widely considered as one of the best alternative fuels for internal combustion engines, allowing to achieve zero CO2 emissions at the tailpipe. However, NOx emissions represent the predominant pollutants and their production has to be controlled. In this work different strategies for the control and abatement of pollutant emissions on a H2-fueled high-performance V8 twin turbo 3.9L IC engine are tested. The characterization of pollutant production on a single-cylinder configuration is carried out by means of the 1D code Gasdyn, considering lean and homogeneous conditions. The NOx are extremely low in lean conditions with respect to the emissions legislation limits, while the maximum mass flow rate remains below the turbocharger technical constraint limit at λ=1 only.

Non-Road Mobile Machinery (NRMM) incorporates a wide variety of machines not intended for the transport of passengers or goods on the road. This includes small gardening equipment, construction, mining, agricultural, and forestry machinery up to locomotives and inland waterway vessels, mostly using an internal combustion engine. NRMM was often overlooked and neglected in the past when considering pollutant and greenhouse gas emissions. Due to their high diversity, they are hard to categorize, resulting in a lack of available data. As emissions from road transport are being tackled by regulations, the emissions of NRMM become an increasing part of total transport emissions. An alternative to fossil fuels will be required for the energy supply of NRMM to fully commit to the CO2 reduction goals, and to fulfil the future requirements of legislators and public opinion.

This work has the objective to present the extension of a novel quasi-dimensional model, developed to simulate the combustion process in diesel Compression Ignition (CI) engines, to describe this process when Dimethyl ether (DME) is used as fuel. DME is a promising fuel in heavy-duty CI engines application thanks to its high Cetane Number (CN), volatility, high reactivity, almost smokeless combustion, lower CO2 emission and the possibility to be produced with renewable energy sources. In this paper, a brief description of the thermodynamic model will be presented, with particular attention to the implementation of the Tabulated Kinetic Ignition (TKI) model, and how the various models interact to simulate the combustion process. The model has been validated against experimental data derived from constant-volume DME combustion, in this case the most important parameters analyzed and compared were the Ignition Delay (ID) and Flame Lift Off Length (FLOL).

In the search for sustainable transportation fuels that are not in competition with food production, considerable efforts are made in the development of so-called second-generation (2G) biofuels. This paper looks into the results of a novel 2G biofuel production technique that is based on a catalytic process that operates at low temperature and that converts woody biomass feedstock into a stable light naphtha. The process development is integrated in the Belgian federal government funded Ad-Libio project and the process outcome is mainly consisting of hydrocarbons containing five to six carbon atoms. Their composition can be altered, resulting in a large amount of different possible fuel blends. The ultimate goal is to produce a drop-in fuel that can be fully interchanged with the gasoline fuels in use today. This is a challenge, since the Ad-Libio fuel components differ significantly from gasoline fuel components.

Despite the increasing number of electrified vehicles the transportation system still largely depends on the use of fossil fuels. One way to more rapidly reduce the dependency on fossil fuels in transport is to replace them with biofuels. Evaluating the potential of different biofuels in different applications requires knowledge of their physicochemical properties. In chemistry, message passing neural networks (MPNNs) correlating the atoms and bonds of a molecule to properties have shown promising results in predicting the properties of individual chemical components. In this article a machine learning approach, developed from the message passing neural network called Chemprop, is evaluated for the prediction of multiple properties of organic molecules (containing carbon, nitrogen, oxygen and hydrogen). A novel approach using transfer learning based on estimated property values from theoretical estimation methods is applied.

Predictive combustion models are useful tools towards the development of clean and efficient engines operating with alternative fuels. This work intends to validate two different combustion models on compression-ignition engines fueled with Dimethyl Ether. Both approaches give a detailed characterization of the combustion kinetics, but they substantially differ in how the interaction between fluid-dynamics and chemistry is treated. The first one is single-flamelet Representative Interactive Flamelet, which considers turbulence-kinetic interaction but cannot correctly describe the stabilization of the flame. The second, named Tabulated Well Mixed, correctly accounts for local flow and mixture conditions but does not consider interaction between turbulence and chemistry. An experimental campaign was carried out on a heavy-duty truck engine running on DME at a constant load considering trade-off of EGR and SOI.

Increasingly stringent pollutant and CO2 emission standards require the car manufacturers to investigate innovative solutions to further improve the fuel economy and environmental impact of their fleets. Nowadays, NOx emissions standards are stringent for spark-ignition (SI) internal combustion engines (ICEs) and many techniques are investigated to limit these emissions. Among these, an extremely lean combustion has a large potential to simultaneously reduce the NOx raw emissions and the fuel consumption of SI ICEs. Engines with pre-chamber ignition system are promising solutions for realizing a high air-fuel ratio which is both ignitable and with an adequate combustion speed. In this work, the combustion characteristics of an active pre-chamber system are experimentally investigated using a single-cylinder research engine. The engine under exam is a large bore heavy-duty unit with an active pre-chamber fuelled with compressed natural gas.

An increasing need to lower greenhouse gas emissions, and so move away from fossil fuels like diesel and gasoline, has greatly increased the interest for methanol. Methanol can be produced from renewable sources and eliminate soot emissions from combustion engines [1]. Since compression ignition (CI) engines are used for the majority of commercial applications, research is intensifying into the use of methanol, as a replacement for diesel fuel, in CI engines. This includes work on dual-fuel set-ups, different fuel blends with methanol, ignition enhancers mixed with methanol, and partially premixed combustion (PPC) strategies with methanol. However, methanol is difficult to ignite, using compression alone, at low load conditions. The problem comes from methanol’s high octane number, low lower heating value and high heat of vaporization, which add up to a lot of heat being needed from the start to combust methanol [2].

The continuous pursuit of higher combustion efficiencies, as well as the possible usage of synthetic fuels with different properties than fossil-ones, require reliable and low-cost numerical approaches to support and speed-up engines industrial design. In this context, SI engines operated with homogeneous ultra-lean mixtures both characterized by a classical ignition configuration or equipped with an active prechamber represent the most promising solutions. In this work, for the classical ignition arrangement, a 3DCFD strategy to model the impact of the ignition system type on the CCV is developed using the RANS approach for turbulence modelling. The spark-discharge is modelled through a set of Lagrangian particles, whose velocity is modified with a zero-divergence perturbation at each discharge event, then evolved according to the Simplified Langevin Model (SLM) to simulate stochastic interactions with the surrounding gas flow.

In order to reduce the carbon footprint of the Internal Combustion Engine (ICE), biofuels have been in use for a number of years. One of the problems with first-generation (1G) biofuels however is their competition with food production. In search of second-generation (2G) biofuels, that are not in competition with food agriculture, a novel biorefinery process has been developed to produce biofuel from woody biomass sources. This novel technique, part of the Belgian federal government funded Ad-Libio project, uses a catalytic process that operates at low temperature and is able to convert 2G feedstock into a stable light naphtha. The bulk of the yield consists out of hydrocarbons containing five to six carbon atoms, along with a fraction of oxygenates and aromatics. The oxygen content and the aromaticity of the hydrocarbons can be varied, both of which have a significant influence on the fuel’s combustion and emission characteristics when used in Internal Combustion Engines.

The paper illustrates and validates a novel predictive combustion model for the estimation of performances and pollutant production in CI engines. The numerical methodology was developed by the authors for near real-time applications, while aiming at an accurate description of the air mixing process by means of a multi-zone approach of the air-fuel mass. Charge stratification is estimated via a 2D representation of the fuel spray distribution that is numerically derived by an axial one-dimensional control-volume description of the direct injection. The radial coordinate of each control volume is reconstructed a posteriori by means of a local distribution function. Fuel mass clustered in each zone is further split in ‘liquid’, ‘unburnt’ and ‘burnt’ sub-zones, given the local properties of the fuel spray control volumes with respect to space-time location of modelled ignition delay, liquid length, and flame lift-off.

To speed up the development of the next-generation combustion engines with renewable fuels, the importance of reliable and robust simulations cannot be overemphasized. Compared to gasoline, methanol is a promising fuel for spark-ignited engines due to its higher research octane number to resist auto-ignition, higher flame speed for faster combustion and higher heat of vaporization for intake charge cooling. These advantageous properties all contribute to higher thermal efficiency and lower knock tendency, and they need to be well-captured in the simulation environment in order to generate accurate predictions. In this paper, the sub-models which estimate the burning velocities and ignition delay of methanol are revisited. These building blocks are implemented and integrated in a quasi-dimensional simulation environment to predict the combustion behavior, which are subsequently validated against test data measured on both light-duty and heavy-duty engines.