Securitization and Special Purpose Vehicles in an International Setting: a Systemic View

The present work tries to display a comprehensive and comparative study of the different legal and regulatory problems involved in international securitization transactions. First, an introduction to securitization is provided, with the basic elements of the transaction, followed by the different varieties of it, including dynamic securitization and synthetic securitization structures. Together with this introduction to the intricacies of the structure, a insight into the influence of securitization in the financial and economic crisis of 2007-2009 is provided too; as well as an overview of the process of regulatory competition and cooperation that constitutes the framework for the international aspects of securitization. The next Chapter focuses on the aspects that constitute the foundations of structured finance: the inception of the vehicle, and the transfer of risks associated to the securitized assets, with particular emphasis on the validity of those elements, and how a securitization transaction could be threatened at its root. In this sense, special importance is given to the validity of the trust as an instrument of finance, to the assignment of future receivables or receivables in block, and to the importance of formalities for the validity of corporations, trusts, assignments, etc., and the interaction of such formalities contained in general corporate, trust and assignment law with those contemplated under specific securitization regulations. Then, the next Chapter (III) focuses on creditor protection aspects. As such, we provide some insights on the debate on the capital structure of the firm, and its inadequacy to assess the financial soundness problems inherent to securitization. Then, we proceed to analyze the importance of rules on creditor protection in the context of securitization. The corollary is in the rules in case of insolvency. In this sense, we divide the cases where a party involved in the transaction goes bankrupt, from those where the transaction itself collapses. Finally, we focus on the scenario where a substance over form analysis may compromise some of the elements of the structure (notably the limited liability of the sponsor, and/or the transfer of assets) by means of veil piercing, substantive consolidation, or recharacterization theories. Once these elements have been covered, the next Chapters focus on the regulatory aspects involved in the transaction. Chapter IV is more referred to “market” regulations, i.e. those concerned with information disclosure and other rules (appointment of the indenture trustee, and elaboration of a rating by a rating agency) concerning the offering of asset-backed securities to the public. Chapter V, on the other hand, focuses on “prudential” regulation of the entity entrusted with securitizing assets (the so-called Special Purpose vehicle), and other entities involved in the process. Regarding the SPV, a reference is made to licensing requirements, restriction of activities and governance structures to prevent abuses. Regarding the sponsor of the transaction, a focus is made on provisions on sound originating practices, and the servicing function. Finally, we study accounting and banking regulations, including the Basel I and Basel II Frameworks, which determine the consolidation of the SPV, and the de-recognition of the securitized asset from the originating company’s balance-sheet, as well as the posterior treatment of those assets, in particular by banks. Chapters VI-IX are concerned with liability matters. Chapter VI is an introduction to the different sources of liability. Chapter VII focuses on the liability by the SPV and its management for the information supplied to investors, the management of the asset pool, and the breach of loyalty (or fiduciary) duties. Chapter VIII rather refers to the liability of the originator as a result of such information and statements, but also as a result of inadequate and reckless originating or servicing practices. Chapter IX finally focuses on third parties entrusted with the soundness of the transaction towards the market, the so-called gatekeepers. In this respect, we make special emphasis on the liability of indenture trustees, underwriters and rating agencies. Chapters X and XI focus on the international aspects of securitization. Chapter X contains a conflicts of laws analysis of the different aspects of structured finance. In this respect, a study is made of the laws applicable to the vehicle, to the transfer of risks (either by assignment or by means of derivatives contracts), to liability issues; and a study is also made of the competent jurisdiction (and applicable law) in bankruptcy cases; as well as in cases where a substance-over-form is performed. Then, special attention is also devoted to the role of financial and securities regulations; as well as to their territorial limits, and extraterritoriality problems involved. Chapter XI supplements the prior Chapter, for it analyzes the limits to the States’ exercise of regulatory power by the personal and “market” freedoms included in the US Constitution or the EU Treaties. A reference is also made to the (still insufficient) rules from the WTO Framework, and their significance to the States’ recognition and regulation of securitization transactions.

Optimal Supervisory Control of Hybrid Vehicles

Hybrid vehicles (HV), comprising a conventional ICE-based powertrain and a secondary energy source, to be converted into mechanical power as well, represent a well-established alternative to substantially reduce both fuel consumption and tailpipe emissions of passenger cars. Several HV architectures are either being studied or already available on market, e.g. Mechanical, Electric, Hydraulic and Pneumatic Hybrid Vehicles. Among the others, Electric (HEV) and Mechanical (HSF-HV) parallel Hybrid configurations are examined throughout this Thesis. To fully exploit the HVs potential, an optimal choice of the hybrid components to be installed must be properly designed, while an effective Supervisory Control must be adopted to coordinate the way the different power sources are managed and how they interact. Real-time controllers can be derived starting from the obtained optimal benchmark results. However, the application of these powerful instruments require a simplified and yet reliable and accurate model of the hybrid vehicle system. This can be a complex task, especially when the complexity of the system grows, i.e. a HSF-HV system assessed in this Thesis. The first task of the following dissertation is to establish the optimal modeling approach for an innovative and promising mechanical hybrid vehicle architecture. It will be shown how the chosen modeling paradigm can affect the goodness and the amount of computational effort of the solution, using an optimization technique based on Dynamic Programming. The second goal concerns the control of pollutant emissions in a parallel Diesel-HEV. The emissions level obtained under real world driving conditions is substantially higher than the usual result obtained in a homologation cycle. For this reason, an on-line control strategy capable of guaranteeing the respect of the desired emissions level, while minimizing fuel consumption and avoiding excessive battery depletion is the target of the corresponding section of the Thesis.

Modelling and Optimization of Energy Management Strategies for Hybrid Vehicles

In the last decades the automotive sector has seen a technological revolution, due mainly to the more restrictive regulation, the newly introduced technologies and, as last, to the poor resources of fossil fuels remaining on Earth. Promising solution in vehicles’ propulsion are represented by alternative architectures and energy sources, for example fuel-cells and pure electric vehicles. The automotive transition to new and green vehicles is passing through the development of hybrid vehicles, that usually combine positive aspects of each technology. To fully exploit the powerful of hybrid vehicles, however, it is important to manage the powertrain’s degrees of freedom in the smartest way possible, otherwise hybridization would be worthless. To this aim, this dissertation is focused on the development of energy management strategies and predictive control functions. Such algorithms have the goal of increasing the powertrain overall efficiency and contextually increasing the driver safety. Such control algorithms have been applied to an axle-split Plug-in Hybrid Electric Vehicle with a complex architecture that allows more than one driving modes, including the pure electric one. The different energy management strategies investigated are mainly three: the vehicle baseline heuristic controller, in the following mentioned as rule-based controller, a sub-optimal controller that can include also predictive functionalities, referred to as Equivalent Consumption Minimization Strategy, and a vehicle global optimum control technique, called Dynamic Programming, also including the high-voltage battery thermal management. During this project, different modelling approaches have been applied to the powertrain, including Hardware-in-the-loop, and diverse powertrain high-level controllers have been developed and implemented, increasing at each step their complexity. It has been proven the potential of using sophisticated powertrain control techniques, and that the gainable benefits in terms of fuel economy are largely influenced by the chose energy management strategy, even considering the powerful vehicle investigated.

Modeling of Electric Hybrid Vehicles based on Innovative Energy Storage Technologies for Super Sports Cars Applications

Today, the contribution of the transportation sector on greenhouse gases is evident. The fast consumption of fossil fuels and its impact on the environment has given a strong impetus to the development of vehicles with better fuel economy. Hybrid electric vehicles fit into this context with different targets, starting from the reduction of emissions and fuel consumption, but also for performance and comfort enhancement. Vehicles exist with various missions; super sport cars usually aim to reach peak performance and to guarantee a great driving experience to the driver, but great attention must also be paid to fuel consumption. According to the vehicle mission, hybrid vehicles can differ in the powertrain configuration and the choice of the energy storage system. Lamborghini has recently invested in the development of hybrid super sport cars, due to performance and comfort reasons, with the possibility to reduce fuel consumption. This research activity has been conducted as a joint collaboration between the University of Bologna and the sportscar manufacturer, to analyze the impact of innovative energy storage solutions on the hybrid vehicle performance. Capacitors have been studied and modeled to analyze the pros and cons of such solution with respect to batteries. To this aim, a full simulation environment has been developed and validated to provide a concept design tool capable of precise results and able to foresee the longitudinal performance on regulated emission cycles and real driving conditions, with a focus on fuel consumption. In addition, the target of the research activity is to deepen the study of hybrid electric super sports cars in the concept development phase, focusing on defining the control strategies and the energy storage system’s technology that best suits the needs of the vehicles. This dissertation covers the key steps that have been carried out in the research project.

Automotive Radars:towards smarter vehicles

Radars are expected to become the main sensors in various civilian applications, especially for autonomous driving. Their success is mainly due to the availability of low cost integrated devices, equipped with compact antenna arrays, and computationally efficient signal processing techniques. This thesis focuses on the study and the development of different deterministic and learning based techniques for colocated multiple-input multiple-output (MIMO) radars. In particular, after providing an overview on the architecture of these devices, the problem of detecting and estimating multiple targets in stepped frequency continuous wave (SFCW) MIMO radar systems is investigated and different deterministic techniques solving it are illustrated. Moreover, novel solutions, based on an approximate maximum likelihood approach, are developed. The accuracy achieved by all the considered algorithms is assessed on the basis of the raw data acquired from low power wideband radar devices. The results demonstrate that the developed algorithms achieve reasonable accuracies, but at the price of different computational efforts. Another important technical problem investigated in this thesis concerns the exploitation of machine learning and deep learning techniques in the field of colocated MIMO radars. In this thesis, after providing a comprehensive overview of the machine learning and deep learning techniques currently being considered for use in MIMO radar systems, their performance in two different applications is assessed on the basis of synthetically generated and experimental datasets acquired through a commercial frequency modulated continuous wave (FMCW) MIMO radar. Finally, the application of colocated MIMO radars to autonomous driving in smart agriculture is illustrated.

Development of predictive energy management strategies for hybrid electric vehicles supported by connectivity

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of the global warming. In this context, the transportation sector plays a vital role, since it is responsible for a large part of carbon dioxide production. In order to address these issues, the present thesis deals with the development of advanced control strategies for the energy efficiency optimization of plug-in hybrid electric vehicles (PHEVs), supported by the prediction of future working conditions of the powertrain. In particular, a Dynamic Programming algorithm has been developed for the combined optimization of vehicle energy and battery thermal management. At this aim, the battery temperature and the battery cooling circuit control signal have been considered as an additional state and control variables, respectively. Moreover, an adaptive equivalent consumption minimization strategy (A-ECMS) has been modified to handle zero-emission zones, where engine propulsion is not allowed. Navigation data represent an essential element in the achievement of these tasks. With this aim, a novel simulation and testing environment has been developed during the PhD research activity, as an effective tool to retrieve routing information from map service providers via vehicle-to-everything connectivity. Comparisons between the developed and the reference strategies are made, as well, in order to assess their impact on the vehicle energy consumption. All the activities presented in this doctoral dissertation have been carried out at the Green Mobility Research Lab} (GMRL), a research center resulting from the partnership between the University of Bologna and FEV Italia s.r.l., which represents the industrial partner of the research project.

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.