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In pursuing sustainable automotive technologies, exploring alternative fuels for hybrid vehicles is crucial in reducing environmental impact and aligning with global carbon emission reduction goals. This work compares methanol and naphtha as potential suitable alternative fuels for running in a battery-driven light-duty hybrid vehicle by comparing their performance with the diesel baseline engine. This work employs a 0-D vehicle simulation model within the GT-Power suite to replicate vehicle dynamics under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC). The vehicle choice enables the assessment of a delivery application scenario using distinct payload capacities: 0%, 25%, 50%, and 100%. The model is fed with engine maps derived from previous experimental work conducted in the same engine, in which a full calibration was obtained that ensures the engine's operability in a wide region of rotational speed and loads.

Ammonia has emerged as a promising carbon-free alternative fuel for internal combustion engines (ICE), particularly in large-bore engine applications. However, integrating ammonia into conventional engines presents challenges, prompting the exploration of innovative combustion strategies like dual-fuel combustion. Nitrous oxide (N2O) emissions have emerged as a significant obstacle to the widespread adoption of ammonia in ICE. Various studies suggest that combining exhaust gas recirculation (EGR) with adjustments in inlet temperature and diesel injection timing can effectively mitigate nitrogen oxides (NOx) emissions across diverse operating conditions in dual-fuel diesel engines.

The increasing need to reduce greenhouse gas emissions and shift away from fossil fuels has raised an interest for methanol. Methanol can be produced from renewable sources and can drastically lower soot emissions from compression ignition engines (CI). As a result, research and development efforts have intensified focusing on the use of methanol as a replacement for diesel in CI engines. The issue with methanol lies in the fact that methanol is challenging to ignite through compression alone, particularly at low-load and cold starts conditions. This challenge arises from methanol's high octane number, low heating value, and high heat of vaporization, all of which collectively demand a substantial amount of heat for methanol to ignite through compression.

The growing demand to lower greenhouse gas emissions and transition from fossil fuels, has put methanol in the spotlight. Methanol can be produced from renewable sources and has the property of burning almost soot-free in compression ignition (CI) engines. Consequently, there has been a notable increase in research and development activities directed towards exploring methanol as a viable substitute for diesel fuel in CI engines. The challenge with methanol lies in the fact that it is difficult to ignite through compression alone, particularly in low-load and cold start conditions. This difficulty arises from methanol's high octane number, relatively low heating value, and high heat of vaporization, collectively demanding a considerable amount of heat for methanol to ignite through compression. Previous studies have addressed the use of a pilot injection in conjunction with a larger main injection to lower the required intake air temperature for methanol to combust at low loads.

Predicting and preventing combustion anomalies leads to safe and efficient operation of the hydrogen internal combustion engine. This research presents the application of three machine learning (ML) models – K-Nearest Neighbors (KNN), Random Forest (RF) and Logistic Regression (LR) – for the prediction of combustion anomalies in a hydrogen internal combustion engine. A small experimental dataset was used to train the models and posterior experiments were used to evaluate their performance and predicting capabilities (both in operating points -speed and load- within the training dataset and operating points in other areas of the engine map). KNN and RF exhibit superior accuracy in classifying combustion anomalies in the training and testing data, particularly in minimizing false negatives, which could have detrimental effects on the engine.

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.

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.

To mitigate climate change, it is essential that sustainable technologies emerge in the transport industry. One viable solution is the use of methanol or hydrogen combined with internal combustion engines (ICEs). The dual-fuel technology in particular, in which a diesel pilot ignites port fuel injected methanol or hydrogen, is of great interest to transition from diesel engines to ICEs using purely these fuels. This approach allows for a significant portion of fossil diesel to be replaced with sustainable methanol or hydrogen, while maintaining high efficiencies and the possibility to run solely on diesel if required. Additionally, lower engine-out pollutant emissions (NOx, soot) are produced. Although multiple experimental research results are available, numerical literature on both fuels in dual-fuel mode is scarce. Therefore, this study aims to develop a multi-zone dual-fuel combustion model for engine simulations.

Using renewable fuels is a reliable approach for decarbonization of combustion engines. iso-Butanol and n-butanol are known as longer chain alcohols and have the potential of being used as gasoline substitute or a renewable fraction of gasoline. The combustion behavior of renewable fuels in modern combustion engines and advanced combustion concepts is not well understood yet. Low-temperature combustion (LTC) is a concept that is a basis for some of the low emissions-high efficiency combustion technologies. Fuel ɸ-sensitivity is known as a key factor to be considered for tailoring fuels for these engines. The Lund ɸ-sensitivity method is an empirical test method for evaluation of the ɸ-sensitivity of liquid fuels and evaluate fuel behavior in thermal. iso-Butanol and n-butanol are two alcohols which like other alcohol exhibit nonlinear behavior when blended with (surrogate) gasoline in terms of RON and MON.

Methanol is currently being evaluated as a promising alternative fuel for internal combustion engines, due to being attainable by carbon neutral or negative pathways (renewable energy and carbon capture technology). The low ignitability of methanol has made it attractive mostly as a fuel for spark ignition engines, however the low sooting properties of the fuel could potentially reduce the NOx-soot tradeoff present in compression ignition engines. In this work, using a 4-cylinder engine with compression ratio modified from 16:1 to 19:1, methanol combustion is evaluated under five operating conditions in terms of fuel consumption, criteria pollutants, CO2 emissions and engine efficiency in addition to the qualitative assessment of the combustion stability. It was found that combustion is stable at medium to high loads, with medium load NOx emissions levels at least 30% lower than the original diesel engine and comparable emissions at maximum load conditions.

The worldwide adoption of renewable energy mandates, together with the widespread utilization of biofuels has created a sharp increase in the production of biodiesel (fatty acid alkyl esters). As a consequence, the production of glycerol, the main by-product of the transesterification of fatty acids, has increased accordingly, which has led to an oversupply of that compound on the markets. Therefore, in order to increase the sustainability of the biodiesel industry, alternative uses for glycerol need to be explored and the production of fuel additives is a good example of the so-called glycerol valorization. The goal of this study is therefore to evaluate the suitability of a number of glycerol-derived compounds as diesel fuel additives. Moreover, this work concerns the assessment of low-concentration blends of those glycerol derivatives with diesel fuel, which are more likely to conform to the existing fuel standards and be used in unmodified engines.

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.

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.

In several regions, such as Europe, California, among others, the switch to Electric Vehicles (EVs) has been heavily pushed by policymakers for their high powertrain efficiency and zero tailpipe emissions compared to conventional Internal Combustion Engine Vehicles (ICEVs). Consequently, only zero tailpipe emission vehicles will be sold in Europe from 2035 for the passenger cars and vans segment. But an EV does emit CO2 emissions across its life cycle, mainly during production, and the Well-to-Tank (WTT) phase, i.e., from the electricity generation used to charge the batteries. Nonetheless, due to the high efficiency of the electric powertrain, the energy consumption is significantly less, making the cost of operation significantly low for EVs. Thus, clean electricity grid and cheap energy costs can make EVs one of the best options for decarbonizing transportation systems.

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.

A modern diesel engine is a reliable and efficient mean of producing power. A way to reduce harmful exhaust and greenhouse gas (GHG) emissions and secure the sources of energy is to develop technology for an efficient diesel engine operation independent of fossil fuels. Renewable diesel fuels are compatible with diesel engines without any major modifications. Rapeseed oil methyl esters (RME) and other fatty acid methyl esters (FAME) are commonly used in low level blends with diesel. Lately, hydrotreated vegetable oil (HVO) produced from vegetable oil and waste fat has found its way into the automotive market, being approved for use in diesel engines by several leading vehicle manufacturers, either in its pure form or in a mixture with the fossil diesel to improve the overall environmental footprint. There is a lack of data on how renewable fuels change the semi-volatile organic fraction of exhaust emissions.

De-fossilization is an increasingly important trend in the energy sector. In the transport sector the de-fossilization efforts have been centered in promoting the electrification of vehicles, nonetheless other pathways, like the use of carbon neutral or carbon-offsetting fuels under current vehicle fleets, are also worth considering. Low-carbon fuels (LCF) can be synthetized from sources that can take advantage of the carbon already present in the atmosphere (either by technologies like direct carbon capture or biological processes like photosynthesis in biofuels) and use energy from renewable sources for the necessary industrial processes. Although, LCFs can be compared to fossil fuels as energy sources for internal combustion engines, their composition is not the same and their properties can modify the engine combustion and emissions.

Focusing on the dual-mode dual-fuel (DMDF) combustion concept, a combined optimization of the piston bowl geometry with the fuel injection strategy was conducted at low, mid, and high loads. By coupling the KIVA-3V code with the enhanced genetic algorithm (GA), a total of 14 parameters including the piston bowl geometric parameters and the injection parameters were optimized with the objective of meeting Euro VI regulations while improving the fuel efficiency. The optimal piston bowl shape coupled with the corresponding injection strategy was summarized and integrated at various loads. Furthermore, the effects of the key geometric parameters were investigated in terms of organizing the in-cylinder flow, influencing the energy distribution, and affecting the emissions. The results indicate that the behavior of the DMDF combustion mode is further enhanced in the aspects of improving the fuel economy and controlling the emissions after the bowl geometry optimization.

Fleet electrification has been demonstrated as a feasible solution to decarbonize the heavy-duty transportation sector. The combination of hybridization and advanced combustion concepts may provide further advantages by also introducing reductions on criteria pollutants such as nitrogen oxides and soot. In this scenario, the interplay among the different energy paths must be understood and quantified to extract the full potential of the powertrain. One of the key devices in such powertrains is the battery, which involves different aspects regarding operation, safety, and degradation. Despite this complexity, most of the models still rely on resistance-capacity models to describe the battery operation. These models may lead to unpractical results since the current flow is governed by limiters rather than physical laws. Additionally, phenomena related with battery degradation, which decreases the nominal capacity and enhances the heat generation are also not considered in this approach.

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.