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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.

The global transportation industry, and road freight in particular, faces formidable challenges in reducing Greenhouse Gas (GHG) emissions; both Europe and the US have already enabled legislation with CO2 / GHG reduction targets. In Europe, targets are set on a fleet level basis: a CO2 baseline has already been established using Heavy Duty Vehicle (HDV) data collected and analyzed by the European Environment Agency (EEA) in 2019/2020. This baseline data has been published as the reference for the required CO2 reductions. More recently, the EU has proposed a Zero Emissions Vehicle definition of 3g CO2/t-km. The Zero Emissions Vehicle (ZEV) designation is expected to be key to a number of market instruments that improve the economics and practicality of hydrogen trucks. This paper assesses the permissible amount of carbon-based fuel in hydrogen fueled vehicles – the Pilot Energy Ratio (PER) – for each regulated subgroup of HDVs in the baseline data set.

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.

In response to global climate change, there is a widespread push to reduce carbon emissions in the transportation sector. For the difficult to decarbonize heavy-duty (HD) vehicle sector, lower carbon intensity fuels can offer a low-cost, near-term solution for CO2 reduction. The use of natural gas can provide such an alternative for HD vehicles while the increasing availability of renewable natural gas affords the opportunity for much deeper reductions in net-CO2 emissions. With this in consideration, the US National Renewable Energy Laboratory launched the Natural Gas Vehicle Research and Development Project to stimulate advancements in technology and availability of natural gas vehicles. As part of this program, Southwest Research Institute developed a hybrid-electric medium-HD vehicle (class 6) to demonstrate a substantial CO2 reduction over the baseline diesel vehicle and ultra-low NOx emissions.

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.