• Energy Research

<div class="section abstract"><div class="htmlview paragraph">The transport sector is experiencing a shift to zero-carbon powertrains driven by aggressive international policies aiming to fight climate change. Battery electric vehicles (BEVs) will play the main role in passenger car applications, while diversified solutions are under investigation for the heavy-duty sector. Within this framework, Light Commercial Vehicles (LCVs) impact is not negligible and accountable for about 2.5% of greenhouse gas (GHG) emissions in Europe. In this regard, few LCV comparative assessments on green powertrains are available in the scientific literature and justified by the fact that several factors and limitations should be considered and addressed to define optimal powertrain solutions for specific use cases. The proposed research study deals with a comparative numerical assessment of different zero-carbon powertrain solutions for LCV. BEVs are compared to hydrogen-based fuel cells (FC) and internal combustion engines (ICE) powered vehicles. The analysis is conducted through specifically developed vehicle models. Vehicle performance in terms of energy efficiency, well-to-wheel GHG, range, payload, and total cost of ownership (TCO) are compared. Optimal powertrain configurations based on predefined vehicle ranges have been identified, and the impact of various cost scenarios has been analyzed. The most influencing factors on TCO have been identified, and a sensitivity analysis has been carried out. The numerical tool developed, and the methodology adopted allows the definition of the domains in which one solution prevails over the others in terms of vehicle range, fuel, and electricity cost.</div></div>

Hybrid Polygeneration Energy Systems (HPES) can be effective solutions to reach COP26 goals. In particular, Combined Heat and Power (CHP) systems can increase the total system efficiency when both electrical and thermal power are required. The integration of a Battery Energy Storage System (BESS) can further improve the plant efficiency and economy, assuring higher operational flexibility. Configuration, sizing and control strategy definition are of primary concern for these systems when the best possible performances are sought. This work aims to quantitatively assess the importance of the adopted control strategy in the operation and performance of a possible sub-system of a grid-connected Hybrid Polygeneration Energy Systems (HPES), consisting in this study of a CHP plant assisted by a BESS. A simulation code of the plant from an energetic point of view was used, and the main economic indicator was also calculated according to the legislative reference scenario. Then a Prescient Model Predictive Control (MPC) was coded to achieve near-optimal plant operation, using a novel system state description to reduce the computational burden linked to the Optimal Control Problem (OCP) solution. The BESS system was modelled, including cycle battery ageing. Subsequently, the performances of the adopted prescient MPC have been compared to the previous results given by a multi-objective plant sizing with a rule-based control. The results show that the control strategy can enhance the performance of the CHP system, achieving remarkable overall better performances, with up to 12% higher Primary Energy Savings. Moreover, the research findings highlight how the proposed control variable ensure a reduction of the computational time by more than 70%, also improving the quality of the found solutions to the OCP. The results also suggest that proper control strategies should be adopted even in a preliminary optimal sizing phase of the CHP plant, since there is a large room of improvement in predicting the achievable plant performance when more basic rule-based control strategies are overcome and replaced by MPC.

The increasing concern of global warming due to the ever-increasing amount of greenhouse gases (GHG) such as carbon dioxide (CO2) and pollutant emissions induces regulatory authorities to stricter emission legislation in the transportation sector. In this context, renewable fuels, such as methanol and ethanol, are considered a promising solution to mitigate the carbon footprint and reduce engine-out emissions. Based on the several studies published in the specific literature, this work aims to summarise and normalize the main outcomes, highlighting the pro and cons of exerting alcohol fuels in compression ignition engines through a critical literature review for helping the researchers, who start to work on these applications. Both dual-fuel and direct-injection fuelling concepts of diesel and alcohol (ethanol and methanol) in compression ignition engines are discussed. Analyses on the combustion, emissions and performance and CO2 are carried out. Depending on the fuel supply method and the engine type, the use of alcohol fuels performs differently in terms of emissions and engine performance. Dual Fuel combustion mode, port fuel injected alcohol, and direct-injected diesel emits higher HC and CO, while diesel-alcohol blends perform as diesel. Generally, the blends characterized by lower alcohol concentration than dual-fuel perform higher indicated thermal efficiencies. Significant benefits on NOx-soot trade-offs are observed, independently on the fuelling mode, NOx concentration, and engine type by using alcohols. The soot reduction reaches values up to 70%, and the lower carbon content of alcohols fuel reduces the CO2 up to 15%.

Advanced Driver-Assistance Systems (ADASs) are currently gaining particular attention in the automotive field, as enablers for vehicle energy consumption, safety, and comfort enhancement. Compelling evidence is in fact provided by the variety of related studies that are to be found in the literature. Moreover, considering the actual technology readiness, larger opportunities might stem from the combination of ADASs and vehicle connectivity. Nevertheless, the definition of a suitable control system is not often trivial, especially when dealing with multiple-objective problems and dynamics complexity. In this scenario, even though diverse strategies are possible (e.g., Equivalent Consumption Minimization Strategy, Rule-based strategy, etc.), the Model Predictive Control (MPC) turned out to be among the most effective ones in fulfilling the aforementioned tasks. Hence, the proposed study is meant to produce a comprehensive review of MPCs applied to scenarios where ADASs are exploited and aims at providing the guidelines to select the appropriate strategy. More precisely, particular attention is paid to the prediction phase, the objective function formulation and the constraints. Subsequently, the interest is shifted to the combination of ADASs and vehicle connectivity to assess for how such information is handled by the MPC. The main results from the literature are presented and discussed, along with the integration of MPC in the optimal management of higher level connection and automation. Current gaps and challenges are addressed to, so as to possibly provide hints on future developments.

Carbon dioxide (CO2), nitrogen oxides (NOx) and soot emissions are primary concerns and the most investigated topics in the automotive sector. Indeed, recent governments directives push toward carbon-neutral mobility by 2050. In this framework, zero-carbon fuels, as hydrogen, or renewable low carbon alcohol fuels, play a fundamental role. To this aim, in this chapter, the main results on largely used alcohol fuels application in spark-ignition (SI) engines are discussed. Aspects inherent ethanol and methanol production processes, chemical-physical properties and their application in SI engines are presented. Different engine fuelling strategies, dual fuel and blend are analysed. Alcohols have higher enthalpies of vaporisation and research octane number (RON) values as well as excellent anti-knock ability compared to gasoline. This effect enhances in dual fuel mode. Ethanol and methanol have higher thermodynamic conversion efficiencies than gasoline combustion. Cycle to cycle variation is in line with gasoline values. In general, NOx decreases with alcohol fuels, and the best results are achieved in blend mode with a reduction of up to 30% with methanol compared to gasoline. Independently of the fuelling mode, significant benefits on particle number emissions are observed by using alcohol fuels. Carbon monoxide (CO) and hydrocarbons (HC) emission trends strongly depend on fuelling mode and engine operating conditions. Additionally, the lower carbon content of alcohol fuels reduces the CO2 emissions up to 10% compared to reference gasoline.