Do Global CO2 Emissions from Fossil-Fuel Consumption Exhibit Long Memory? A Fractional Integration Analysis

In this article we use an autoregressive fractionally integrated moving average approach to measure the degree of fractional integration of aggregate world CO2 emissions and its five components – coal, oil, gas, cement, and gas flaring. We find that all variables are stationary and mean reverting, but exhibit long-term memory. Our results suggest that both coal and oil combustion emissions have the weakest degree of long-range dependence, while emissions from gas and gas flaring have the strongest. With evidence of long memory, we conclude that transitory policy shocks are likely to have long-lasting effects, but not permanent effects. Accordingly, permanent effects on CO2 emissions require a more permanent policy stance. In this context, if one were to rely only on testing for stationarity and non-stationarity, one would likely conclude in favour of non-stationarity, and therefore that even transitory policy shocks

Powertrain Architectures and Technologies for New Emission and Fuel Consumption Standards

New powertrain design is highly influenced by CO2 and pollutant limits defined by legislations, the demand of fuel economy in for real conditions, high performances and acceptable cost. To reach the requirements coming from both end-users and legislations, several powertrain architectures and engine technologies are possible (e.g. SI or CI engines), with many new technologies, new fuels, and different degree of electrification. The benefits and costs given by the possible architectures and technology mix must be accurately evaluated by means of objective procedures and tools in order to choose among the best alternatives. This work presents a basic design methodology and a comparison at concept level of the main powertrain architectures and technologies that are currently being developed, considering technical benefits and their cost effectiveness. The analysis is carried out on the basis of studies from the technical literature, integrating missing data with evaluations performed by means of powertrain-vehicle simplified models, considering the most important powertrain architectures. Technology pathways for passenger cars up to 2025 and beyond have been defined. After that, with support of more detailed models and experimentations, the investigation has been focused on the more promising technologies to improve internal combustion engine, such as: water injection, low temperature combustions and heat recovery systems.

Nanocarbon-Supported Electrocatalysts for the Alkaline Water Splitting and Fuel Cells

Electrocatalysts play a significant role in the processes of electrochemical energy conversion. This thesis focuses on the preparation of carbon-supported nanomaterials and their application as electrocatalysts for alkaline water electrocatalysis and fuel cell. A general synthetic route was developed, i.e., species intercalate into carbon layers of graphite forming graphite intercalation compound, followed by dispersion producing graphenide solution, which then as reduction agent reacts with different metal sources generating the final materials. The first metal precursor used was non-noble metal iron salt, which generated iron (oxide) nanoparticles finely dispersed on carbon layers in the final composite materials. Meanwhile, graphite starting materials differing in carbon layer size were utilized, which would diversify corresponding graphenide solutions, and further produce various nanomaterials. The characterization results showed that iron (oxide) nanoparticles varying in size were obtained, and the size was determined by the starting graphite material. It was found that they were electrocatalytically active for oxygen reactions. In particular, the one with small iron (oxide) nanoparticles showed excellent electrocatalytic activity for both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Afterwards, the metal precursor was tuned from non-noble metal salt to noble metal salt. It was confirmed that carbon-supported Rh, Pt, and RhPt (oxide) nanoparticle composite materials were also successfully obtained from the reaction between graphenide solution and corresponding noble metal precursor. The electrochemical measurements showed that the prepared noble metal-based nanomaterials were quite effective for hydrogen evolution reaction (HER) electrocatalysis, and the Rh sample could also display excellent electrocatalytic property towards OER. Moreover, by this synthetic approach carbon-supported noble metal Pt and non-noble metal nickel (Ni) composite material was also prepared. Therefore, the utilization efficiency of noble metal could be improved. The prepared NiPt sample displayed a property close to benchmark HER electrocatalyst.

Investigation of innovative combustion systems for reduced fuel consumption and increased specific power production

This work resumes a wide variety of research activities carried out with the main objective of increasing the efficiency and reducing the fuel consumption of Gasoline Direct Injection engines, especially under high loads. For this purpose, two main innovative technologies have been studied, Water Injection and Low-Pressure Exhaust Gas Recirculation, which help to reduce the temperature of the gases inside the combustion chamber and thus mitigate knock, being this one of the main limiting factors for the efficiency of modern downsized engines that operate at high specific power. A prototypal Port Water Injection system was developed and extensive experimental work has been carried out, initially to identify the benefits and limitations of this technology. This led to the subsequent development and testing of a combustion controller, which has been implemented on a Rapid Control Prototyping environment, capable of managing water injection to achieve knock mitigation and a more efficient combustion phase. Regarding Low-Pressure Exhaust Gas Recirculation, a commercial engine that was already equipped with this technology was used to carry out experimental work in a similar fashion to that of water injection. Another prototypal water injection system has been mounted to this second engine, to be able to test both technologies, at first separately to compare them on equal conditions, and secondly together in the search of a possible synergy. Additionally, based on experimental data from several engines that have been tested during this study, including both GDI and GCI engines, a real-time model (or virtual sensor) for the estimation of the maximum in-cylinder pressure has been developed and validated. This parameter is of vital importance to determine the speed at which damage occurs on the engine components, and therefore to extract the maximum performance without inducing permanent damages.

Development of numerical methodologies to predict the liquid fuel sprays - wall interaction to optimize the mixing process of direct injection spark ignition engines

Nowadays the development of new Internal Combustion Engines is mainly driven by the need to reduce tailpipe emissions of pollutants, Green-House Gases and avoid the fossil fuels wasting. The design of dimension and shape of the combustion chamber together with the implementation of different injection strategies e.g., injection timing, spray targeting, higher injection pressure, play a key role in the accomplishment of the aforementioned targets. As far as the match between the fuel injection and evaporation and the combustion chamber shape is concerned, the assessment of the interaction between the liquid fuel spray and the engine walls in gasoline direct injection engines is crucial. The use of numerical simulations is an acknowledged technique to support the study of new technological solutions such as the design of new gasoline blends and of tailored injection strategies to pursue the target mixture formation. The current simulation framework lacks a well-defined best practice for the liquid fuel spray interaction simulation, which is a complex multi-physics problem. This thesis deals with the development of robust methodologies to approach the numerical simulation of the liquid fuel spray interaction with walls and lubricants. The accomplishment of this task was divided into three tasks: i) setup and validation of spray-wall impingement three-dimensional CFD spray simulations; ii) development of a one-dimensional model describing the liquid fuel – lubricant oil interaction; iii) development of a machine learning based algorithm aimed to define which mixture of known pure components mimics the physical behaviour of the real gasoline for the simulation of the liquid fuel spray interaction.

Catalytic reduction of levulinic acid derivatives to bio-fuel components

Levulinic Acid and its esters are polyfunctional molecules obtained by biomass conversion. The most investigated strategy for the valorization of LA is its hydrogenation towards fuel additives, solvents and other added-value bio-based chemicals and, in this context, heterogeneous and homogeneous catalysts are widely used. Most commonly, it is typically performed with molecular hydrogen (H2) in batch systems, with high H2 pressures and noble metal catalysts. Several works reported the batch liquid-phase hydrogenation of LA and its esters by heterogenous catalysts which contained support with Brønsted acidity in order to obtain valeric acid and its esters. Furthermore, bimetallic and monometallic systems composed by both a metal for hydrogen activation and a promoter were demonstrated to be suitable catalysts for reduction of carboxylic group. However, there were no studies in the literature reporting the hydrogenation of alkyl levulinates to 1-pentanol (1-PAO). Therefore, bimetallic and monometallic catalysts were tested for one-pot hydrogenation of methyl levulinate to 1-PAO. Re-based catalysts were investigated, this way proving the crucial role of the support for promoting the ring-opening of GVL and its consecutive reduction to valeric compounds. All the reactions were performed in neat without the need of any additional solvents. In these conditions, bimetallic Re-Ru-O/HZSM-5 afforded methyl valerate and valeric acid (VA) with a productivity of 512 mmol gmetal-1 h-1, one of the highest reported in literature to date. Rhenium can also promote the reduction of valeric acid/esters to PV through the formation of 1-pentanol and its efficient esterification/transesterification with the starting material. However, it was proved that Re-based catalysts may undergo leaching of active phase in presence of carboxylic acids, especially by working in neat with VA. Furthermore, the over-reduction of rhenium affects catalytic performance, suggesting not only that a pre-reduction step is unnecessary but also that it could be detrimental for catalyst’s activity.

Performance assessment of vehicular connectivity in hybrid electric vehicles for fuel and emissions reduction

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of global warming. Recently, several metropolitan cities introduced Zero-Emissions Zones where the use of the Internal Combustion Engine is forbidden to reduce localized pollutants emissions. This is particularly problematic for Plug-in Hybrid Electric Vehicles, which usually work in depleting mode. In order to address these issues, the present thesis presents a viable solution by exploiting vehicular connectivity to retrieve navigation data of the urban event along a selected route. The battery energy needed, in the form of a minimum State of Charge (SoC), is calculated by a Speed Profile Prediction algorithm and a Backward Vehicle Model. That value is then fed to both a Rule-Based Strategy, developed specifically for this application, and an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS). The effectiveness of this approach has been tested with a Connected Hardware-in-the-Loop (C-HiL) on a driving cycle measured on-road, stimulating the predictions with multiple re-routings. However, even if hybrid electric vehicles have been recognized as a valid solution in response to increasingly tight regulations, the reduced engine load and the repeated engine starts and stops may reduce substantially the temperature of the exhaust after-treatment system (EATS), leading to relevant issues related to pollutant emission control. In this context, electrically heated catalysts (EHCs) represent a promising solution to ensure high pollutant conversion efficiency without affecting engine efficiency and performance. This work aims at studying the advantages provided by the introduction of a predictive EHC control function for a light-duty Diesel plug-in hybrid electric vehicle (PHEV) equipped with a Euro 7-oriented EATS. Based on the knowledge of future driving scenarios provided by vehicular connectivity, engine first start can be predicted and therefore an EATS pre-heating phase can be planned.

Development of multicomponent models for the prediction of lubricant oil-fuel dilution in internal combustion engines

The current environmental crisis is forcing the automotive industry to face tough challenges for the Internal Combustion Engines development in order to reduce the emissions of pollutants and Greenhouse gases. In this context, in the last decades, the main technological solutions adopted by the manufacturers have been the direct injection and the engine downsizing, which led to the rising of new concerns related to the fuel-cylinder walls physical interaction. The fuel spray possibly impacts the cylinder liner wall, which is wetted by the lubricant oil thus causing the derating of the lubricant properties, increasing the oil consumption, and contaminating the lubricant oil in the crankcase. Also, concerning hydrogen fuelled internal combustion engines, it is likely that the high near-wall temperature, which is typical of the hydrogen flame, results in the evaporation of a portion of the lubricant oil, increasing its consumption. With regards on the innovative combustion systems and their control strategies, optical accessible engines are fundamental tools for experimental investigations on such combustion systems. Though, due to the optical measurement line, optical engines suffer from a high level of blow-by, which must be accounted for. In light of the above, this thesis work aims to develop numerical methodologies with the aim to build useful tools for supporting the design of modern engines. In particular, a one-dimensional modelling of the lubricant oil-fuel dilution and oil evaporation has been performed and coupled with an optimization algorithm to achieve a lubricant oil surrogate. Then, a quasi-dimensional blow-by model has been developed and validated against experimental data. Such model, has been coupled with CFD 3D simulations and directly implemented in CFD 3D. Finally, CFD 3D simulations coupled with the VOF method have been performed in order to validate a methodology for studying the impact of a liquid droplet on a solid surface.