Compression ignition (CI) engines are widely used in modern society, but they are also recognized as a significative source of harmful and human hazard emissions such as particulate matter (PM) and nitrogen oxides (NOx). Moreover, the combustion of fossil fuels is related to the growing amount of greenhouse gas (GHG) emissions, such as carbon dioxide (CO₂). Stringent emission regulatory programs, the transition to cleaner and more advanced powertrains and the use of lower carbon fuels are driving forces for the improvement of diesel engines in terms of overall efficiency and engine-out emissions. Ethanol, a light alcohol and lower carbon fuel, is a promising alternative fuel applicable in the dual-fuel (DF) combustion mode to mitigate CO₂ and also engine-out PM emissions. In this context, this work aims to assess the maximum fuel substitution ratio (FSR) and the impact on CO₂ and PM emissions of different nozzle holes number injectors, 7 and 9, in the DF operating mode. The analysis was conducted within engine working constraints and considered the influence on maximum FSR of calibration parameters, such as combustion phasing, rail pressure, injection pattern and exhaust gas recirculation (EGR). The experimental tests were carried out on a single-cylinder light-duty CI engine with ethanol introduced via port fuel injection (PFI) and direct injection of diesel in two operating points, 1500 and 2000 rpm and at 5 and 8 bar of brake mean effective pressure (BMEP), respectively. Noise and the coefficient of variation in indicated mean effective pressure (COV_IMEP) limits have been chosen as practical constraints. In particular, the experimental analysis assesses for each parameter or their combination the highest ethanol fraction that can be injected. To discriminate the effect on ethanol fraction and the combustion process of each parameter, a one-at-a-time-factor approach was used. The results show that, in both operating points, the EGR reduces the maximum ethanol fraction injectable; nevertheless, the ethanol addition leads to outstanding improvement in terms of engine-out PM. The adoption of a 9 hole diesel injector, for lower load, allows reaching a higher fraction of ethanol in all test conditions with an improvement in combustion noise, on average 3 dBA, while near-zero PM emissions and a reduction can be noticed, on the average of 1 g/kWh, and CO₂ compared with the fewer nozzle holes case. Increasing the load insensitivity to different holes number was observed.

The transport sector is tackling the challenge of reducing vehicle pollutant emissions and carbon footprints by means of a shift to electrified powertrains, i.e., battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). However, electrified vehicles pose new issues associated with the design and energy management for the efficient use of onboard energy storage systems (ESSs). Thus, strong attention should be devoted to ensuring the safety and efficient operation of the ESSs. In this framework, a dedicated battery management system (BMS) is required to contemporaneously optimize the battery’s state of charge (SoC) and to increase the battery’s lifespan through tight control of its state of health (SoH). Despite the advancements in the modern onboard BMS, more detailed data-driven algorithms for SoC, SoH, and fault diagnosis cannot be implemented due to limited computing capabilities. To overcome such limitations, the conceptualization and/or implementation of BMS in-cloud applications are under investigation. The present study hence aims to produce a new and comprehensive review of the advancements in battery management solutions in terms of functionality, usability, and drawbacks, with specific attention to cloud-based BMS solutions as well as SoC and SoH prediction and estimation. Current gaps and challenges are addressed considering V2X connectivity to fully exploit the latest cloud-based solutions.

Internal combustion engine-driven railway vehicles play an important role in the sector even today, due to the incomplete electrification of railway routes. However, stringent COP26 environmental rules are driving manufacturers and the scientific community to study more complex or alternative propulsion systems. Therefore, the design of new powertrains is becoming more challenging. Affordable, along with robust, development tools are fundamental for their development and optimization. In this framework, numerical simulation can represent an effective instrument to face these requirements. The proposed study assesses the accuracy of different modelling approaches for the same engine. In particular, a detailed 1D model, a simplified 1D model and a map-based model are compared. Although studies on engine simulation are available in the technical literature, the novelty introduced with this work is the assessment of accuracy and computational times of the engine models, considered by performing the new emission standard Non-Road Transient Cycle (NRTC), which is applied to a specific field such as Heavy Duty (HD) Compression Ignition (CI) engines for railway applications. This study provides new and quantitative results rarely available in the specific literature. The results show that the simplest model, despite its lower accuracy, maintains good predictive results in terms of cumulative fuel consumption and cumulative nitric oxide (NO_x) emissions over the cycle considered. In particular, the difference in terms of fuel consumption for the map-based model is within 5% compared with the more detailed models. Moreover, the computational effort required by the simplest model is three orders of magnitude lower compared with the more detailed model. Therefore, as the simulation run-time is the priority, the simplest modeling approach is suitable for the evaluation of the global performance, in view of a more complex systems simulation, such as a hybrid powertrain.