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Opposed-piston two-stroke engines offer numerous advantages over conventional four-stroke engines, both in terms of fundamental principles and technical aspects. The reduced heat losses and large volume-to-surface area ratio inherently result in a high thermodynamic efficiency. Additionally, the mechanical design is simpler and requires fewer components compared to conventional four-stroke engines. When combining this engine concept with alternative fuels such as hydrogen and pre-chamber technology, a potential route for carbon-neutral powertrains is observed. To ensure safe engine operation using hydrogen as fuel, it is crucial to consider strict safety measures to prevent issues such as knock, pre-ignition, and backfiring. One potential solution to these challenges is the use of direct injection, which has the potential to improve engine efficiency and expand the range of load operation.

The hydrogen engine is one of the promising technologies that enables carbon-neutral mobility, especially in heavy-duty on- or off-road applications. In this paper, a methodological procedure for the design of the combustion system of a hydrogen-fueled, direct injection spark ignited commercial vehicle engine is described. In a preliminary step, the ability of the commercial 3D computational fluid dynamics (CFD) code AVL FIRE classic to reproduce the characteristics of the gas jet, introduced into a quiescent environment by a dedicated H2 injector, is established. This is based on two parts: Temporal and numerical discretization sensitivity analyses ensure that the spatial and temporal resolution of the simulations is adequate, and comparisons to a comprehensive set of experiments demonstrate the accuracy of the simulations. The measurements used for this purpose rely on the well-known schlieren technique and use helium as a safe substitute for H2.

Ducted Fuel Injection (DFI) engines have emerged as a promising technology in the pursuit of a clean and efficient combustion process. This article aims at elucidating the effect of piston geometry on the engine performance and emissions of a metal DFI engine. Three different types of pistons were investigated and the main piston design features including the piston bowl diameter, piston bowl slope angle, duct angle and the injection nozzle position were examined. To achieve the target, computational fluid dynamics (CFD) simulations were conducted coupled to a reduced chemical kinetics mechanism. Extensive validations were performed against the measured data from a conventional diesel engine. To calibrate the soot model, genetic algorithm and machine learning methods were utilized. The simulation results highlight the pivotal role played by piston bowl diameter and fuel injection angle in controlling soot emissions of a DFI engine.

Heavy duty truck engines are quite difficult to electrify, due to the large amount of energy required on-board, in order to achieve a range comparable to that of diesels. This paper considers a commercial 6-cylinder engine with a displacement of 12.8 L, developed in two different versions. As a standard diesel, the engine is able to deliver more than 420 kW at 1800 rpm, whereas in the CNG configuration the maximum power output is 330 kW at 1800 rpm. Maintaining the same combustion chamber design of the last version, a theoretical study is carried out in order to run the engine on Hydrogen, compressed at 700 bar. The study is based on GT-Power simulations, adopting a predictive combustion model, calibrated with experimental results. The study shows that the implementation of a combustion system running on lean mixtures of Hydrogen, permits to cancel the emissions of CO2, while maintaining the same power output of the CNG engine.

In recent years, the urgent need to fully exploit the fuel economy potential of the Electrified Vehicles (xEVs) through the optimal design of their Energy Management System (EMS) have led to an increasing interest in Machine Learning (ML) techniques. Among them, Reinforcement Learning (RL) seems to be one of the most promising approaches thanks to its peculiar structure, in which an agent is able to learn the optimal control strategy through the feedback received by a direct interaction with the environment. Therefore, in this study, a new Soft Actor-Critic agent (SAC), which exploits a stochastic policy, was implemented on a digital twin of a state-of-the-art diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. The SAC agent was trained to enhance the fuel economy of the PHEV while guaranteeing its battery charge sustainability.

Fossil fuels such as natural gas used in engines still play the most important role worldwide despite such measures as the German energy transition which however is also exacerbating climate change as a result of carbon dioxide emissions. One way of reducing carbon dioxide emissions is the choice of energy sources and with it a more favourable chemical composition. Natural gas, for instance, which consist mainly of methane, has the highest hydrogen to carbon ratio of all hydrocarbons, which means that carbon dioxide emissions can be reduced by up to 35% when replacing diesel with natural gas. Although natural gas engines show an overall low CO2 and pollutant emissions level, methane slip due to incomplete combustion occurs, causing methane emissions with a more than 20 higher global warming potential than CO2.

This study explores the feasibility of using a sustainable lignin-based fuel, consisting of 44 % lignin, 50 % ethanol, and 6 % water, in conventional compression ignition (CI) marine engines. Through experimental evaluations on a modified small-bore CI engine, we identified the primary challenges associated with lignin-based fuel, including engine startup and shutdown issues due to solvent evaporation and lignin solidification inside the fuel system, and deposit formation on cylinder walls leading to piston ring seizure. To address these issues, we developed a fuel switching system transitioning from lignin-based fuel to cleaning fuel with 85 vol% of acetone, 10 vol% of water and 5 vol% of ignition improving additive, effectively preventing system clogs.

Nowadays, the push for more ecological low-carbon propulsion systems is high in all mobility sectors, including the recreational or light-commercial boating, where propulsion is usually provided by internal combustion engines derived from road applications. In this work, the effects of replacing conventional fossil-derived B7 diesel with Hydrotreated Vegetable Oil (HVO) were experimentally investigated in a modern Medium-Duty Engine, using the advanced biofuel as drop-in and testing according to the ISO 8178 marine standard. The compounded results showed significant benefits in terms of NOx, Soot, mass fuel consumption and WTW CO2 thanks to the inner properties of the aromatic-free, hydrogen-rich renewable fuel, with no impact on the engine power and minimal deterioration of the volumetric fuel economy.

Water management in PEMFC power generation systems is a key point to guarantee optimal performances and durability. It is known that a poor water management has a direct impact on PEMFC voltage, both in drying and flooding conditions: furthermore, water management entails phenomena from micro-scale, i.e., formation and water transport within membrane, to meso-scale, i.e., water capillary transport inside the GDL, up to the macro-scale, i.e., water droplet formation and removal from the GFC. Water transport mechanisms through the membrane are well known in literature, but typically a high computational burden is requested for their proper simulation. To deal with this issue, the authors have developed an analytical model for the water membrane content simulation as function of stack temperature and current density, for fast on-board monitoring and control purposes, with good fit with literature data.