Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

Comparison between 5G private network and Wifi6 in industrial environment

Industry 4.0 refers to the 4th industrial revolution and at its bases, we can see the digitalization and the automation of the assembly line. The whole production process has improved and evolved thanks to the advances made in networking, and AI studies, which include of course machine learning, cloud computing, IoT, and other technologies that are finally being implemented into the industrial scenario. All these technologies have in common a need for faster, more secure, robust, and reliable communication. One of the many solutions for these demands is the use of mobile communication technologies in the industrial environment, but which technology is better suited for these demands? Of course, the answer isn’t as simple as it seems. The 4th industrial revolution has a never seen incomparable potential with respect to the previous ones, every factory, enterprise, or company have different network demands, and even in each of these infrastructures, the demands may diversify by sector, or by application. For example, in the health care industry, there may be e a need for increased bandwidth for the analysis of high-definition videos or, faster speeds in order to have analytics occur in real-time, and again another application might be higher security and reliability to protect patients’ data. As seen above, choosing the right technology for the right environment and application, considers many things, and the ones just stated are but a speck of dust with respect to the overall picture. In this thesis, we will investigate a comparison between the use of two of the available technologies in use for the industrial environment: Wi-Fi 6 and 5G Private Networks in the specific case of a steel factory.

Structure learning of graphical models for task-oriented robot grasping

In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.

Computing primal solutions with exact arithmetics in SCIP.

The research for exact solutions of mixed integer problems is an active topic in the scientific community. State-of-the-art MIP solvers exploit a floating- point numerical representation, therefore introducing small approximations. Although such MIP solvers yield reliable results for the majority of problems, there are cases in which a higher accuracy is required. Indeed, it is known that for some applications floating-point solvers provide falsely feasible solutions, i.e. solutions marked as feasible because of approximations that would not pass a check with exact arithmetic and cannot be practically implemented. The framework of the current dissertation is SCIP, a mixed integer programs solver mainly developed at Zuse Institute Berlin. In the same site we considered a new approach for exactly solving MIPs. Specifically, we developed a constraint handler to plug into SCIP, with the aim to analyze the accuracy of provided floating-point solutions and compute exact primal solutions starting from floating-point ones. We conducted a few computational experiments to test the exact primal constraint handler through the adoption of two main settings. Analysis mode allowed to collect statistics about current SCIP solutions' reliability. Our results confirm that floating-point solutions are accurate enough with respect to many instances. However, our analysis highlighted the presence of numerical errors of variable entity. By using the enforce mode, our constraint handler is able to suggest exact solutions starting from the integer part of a floating-point solution. With the latter setting, results show a general improvement of the quality of provided final solutions, without a significant loss of performances.

On the Design of a Boolean-network Robot Swarm: Collective Recognition of Ground Patterns.

Uno dei principali ambiti di ricerca dell’intelligenza artificiale concerne la realizzazione di agenti (in particolare, robot) in grado di aiutare o sostituire l’uomo nell’esecuzione di determinate attività. A tal fine, è possibile procedere seguendo due diversi metodi di progettazione: la progettazione manuale e la progettazione automatica. Quest’ultima può essere preferita alla prima nei contesti in cui occorra tenere in considerazione requisiti quali flessibilità e adattamento, spesso essenziali per lo svolgimento di compiti non banali in contesti reali. La progettazione automatica prende in considerazione un modello col quale rappresentare il comportamento dell’agente e una tecnica di ricerca (oppure di apprendimento) che iterativamente modifica il modello al fine di renderlo il più adatto possibile al compito in esame. In questo lavoro, il modello utilizzato per la rappresentazione del comportamento del robot è una rete booleana (Boolean network o Kauffman network). La scelta di tale modello deriva dal fatto che possiede una semplice struttura che rende agevolmente studiabili le dinamiche tuttavia complesse che si manifestano al suo interno. Inoltre, la letteratura recente mostra che i modelli a rete, quali ad esempio le reti neuronali artificiali, si sono dimostrati efficaci nella programmazione di robot. La metodologia per l’evoluzione di tale modello riguarda l’uso di tecniche di ricerca meta-euristiche in grado di trovare buone soluzioni in tempi contenuti, nonostante i grandi spazi di ricerca. Lavori precedenti hanno gia dimostrato l’applicabilità e investigato la metodologia su un singolo robot. Lo scopo di questo lavoro è quello di fornire prova di principio relativa a un insieme di robot, aprendo nuove strade per la progettazione in swarm robotics. In questo scenario, semplici agenti autonomi, interagendo fra loro, portano all’emergere di un comportamento coordinato adempiendo a task impossibili per la singola unità. Questo lavoro fornisce utili ed interessanti opportunità anche per lo studio delle interazioni fra reti booleane. Infatti, ogni robot è controllato da una rete booleana che determina l’output in funzione della propria configurazione interna ma anche dagli input ricevuti dai robot vicini. In questo lavoro definiamo un task in cui lo swarm deve discriminare due diversi pattern sul pavimento dell’arena utilizzando solo informazioni scambiate localmente. Dopo una prima serie di esperimenti preliminari che hanno permesso di identificare i parametri e il migliore algoritmo di ricerca, abbiamo semplificato l’istanza del problema per meglio investigare i criteri che possono influire sulle prestazioni. E’ stata così identificata una particolare combinazione di informazione che, scambiata localmente fra robot, porta al miglioramento delle prestazioni. L’ipotesi è stata confermata applicando successivamente questo risultato ad un’istanza più difficile del problema. Il lavoro si conclude suggerendo nuovi strumenti per lo studio dei fenomeni emergenti in contesti in cui le reti booleane interagiscono fra loro.

Design of an innovative electric vehicle simulator for Charging Systems' End-of-Line Testing

The trend related to the turnover of internal combustion engine vehicles with EVs goes by the name of electrification. The push electrification experienced in the last decade is linked to the still ongoing evolution in power electronics technology for charging systems. This is the reason why an evolution in testing strategies and testing equipment is crucial too. The project this dissertation is based on concerns the investigation of a new EV simulator design. that optimizes the structure of the testing equipment used by the company who commissioned this work. Project requirements can be summarized in the following two points: space occupation reduction and parallel charging implementation. Some components were completely redesigned, and others were substituted with equivalent ones that could perform the same tasks. In this way it was possible to reduce the space occupation of the simulator, as well as to increase the efficiency of the testing device. Moreover, the possibility of conjugating different charging simulations could be investigated by parallelly launching two testing procedures on a unique machine, properly predisposed for supporting the two charging protocols used. On the back of the results achieved in the body of this dissertation, a new design for the EV simulator was proposed. In this way, space reduction was obtained, and space occupation efficiency was improved with the proposed new design. The testing device thus resulted to be way more compact, enabling to gain in safety and productivity, along with a 25% cost reduction. Furthermore, parallel charging was implemented in the proposed new design since the conducted tests clearly showed the feasibility of parallel charging sessions. The results presented in this work can thus be implemented to build the first prototype of the new EV simulator.

Supporto alla creazione di un ecosistema di aziende: change management e design thinking - il caso Centergross

Il lavoro tratta la progettazione di un intervento tecnologico e organizzativo in grado di guidare la creazione di un ecosistema di imprese per un distretto commerciale: Centergross (Funo d’Argelato, Bologna). Tale lavoro è stato preparato durante un periodo di Stage della durata di cinque mesi effettuato presso Epoca S.r.l (Bologna) a seguito della necessità, riscontrata dalla direzione del distretto, di ripensare il proprio modello di business. L’obiettivo del progetto di intervento di Epoca è quello di supportare il distretto in questa fase di cambiamento, da “condominio” di imprese autonome a ecosistema, grazie all’identificazione e alla realizzazione di strumenti organizzativi e tecnologici che possano costruire opportunità di sinergie, aumentare la completezza dell’offerta e sfruttare economie di scopo. Per questo è stato realizzato un nuovo sistema informatico (social network e applicazione mobile) in grado di supportare la strategia ed evolvere con essa. La tesi si struttura in tre parti. Nella prima parte, attraverso un’indagine della letteratura di riferimento, si sono indagati i principali modelli di cambiamento organizzativo e il ruolo dei sistemi informativi all’interno delle organizzazione. Un approfondimento circa gli approcci, i processi e la gestione del cambiamento in relazione all’introduzione di un nuovo sistema informativo all’interno delle organizzazioni con riferimento alle tematiche del Business Process Reengineering. La seconda parte è dedicata all’evoluzione del Web con la rivoluzione culturale causata dagli strumenti del web partecipativo, semantico e potenziato: social network e applicazione mobile nello specifico; e all’approccio di progettazione: il Design Thinking. Una tecnica che si prefigge di: trovare il miglior fit fra obiettivi, risorse e tecnologie disponibili; favorire lo sviluppo di nuove idee innovative entrando in empatia con il contesto del problema proponendo soluzioni centrate sui bisogni degli utenti. L’ultima parte del lavoro consiste nella descrizione del caso. Vengono presentate la fase di analisi della situazione attuale e i successivi step di progettazione del sistema informatico: la definizione dei prototipi, la popolazione del database, il modello di dominio, le interfacce utente e le esperienze di navigazione all’interno della piattaforma software proposta. L’approccio prevede che il progetto proceda per iterazioni successive e un adattamento continuo alle esigenze del cliente.

Design and implementation of a testbed for data distribution management

Data Distribution Management (DDM) is a core part of High Level Architecture standard, as its goal is to optimize the resources used by simulation environments to exchange data. It has to filter and match the set of information generated during a simulation, so that each federate, that is a simulation entity, only receives the information it needs. It is important that this is done quickly and to the best in order to get better performances and avoiding the transmission of irrelevant data, otherwise network resources may saturate quickly. The main topic of this thesis is the implementation of a super partes DDM testbed. It evaluates the goodness of DDM approaches, of all kinds. In fact it supports both region and grid based approaches, and it may support other different methods still unknown too. It uses three factors to rank them: execution time, memory and distance from the optimal solution. A prearranged set of instances is already available, but we also allow the creation of instances with user-provided parameters. This is how this thesis is structured. We start introducing what DDM and HLA are and what do they do in details. Then in the first chapter we describe the state of the art, providing an overview of the most well known resolution approaches and the pseudocode of the most interesting ones. The third chapter describes how the testbed we implemented is structured. In the fourth chapter we expose and compare the results we got from the execution of four approaches we have implemented. The result of the work described in this thesis can be downloaded on sourceforge using the following link: https://sourceforge.net/projects/ddmtestbed/. It is licensed under the GNU General Public License version 3.0 (GPLv3).

Computer aided design and finite element modeling to predict bulk mechanical properties of bone scaffolds using triply periodic minimal surfaces (progettazione assistita al calcolatore ed analisi con il metodo degli elementi finiti per predire il comportamento meccanico di scaffolds ossei creati con l'uso di superfici minime periodiche in tre direzioni)

The aim of Tissue Engineering is to develop biological substitutes that will restore lost morphological and functional features of diseased or damaged portions of organs. Recently computer-aided technology has received considerable attention in the area of tissue engineering and the advance of additive manufacture (AM) techniques has significantly improved control over the pore network architecture of tissue engineering scaffolds. To regenerate tissues more efficiently, an ideal scaffold should have appropriate porosity and pore structure. More sophisticated porous configurations with higher architectures of the pore network and scaffolding structures that mimic the intricate architecture and complexity of native organs and tissues are then required. This study adopts a macro-structural shape design approach to the production of open porous materials (Titanium foams), which utilizes spatial periodicity as a simple way to generate the models. From among various pore architectures which have been studied, this work simulated pore structure by triply-periodic minimal surfaces (TPMS) for the construction of tissue engineering scaffolds. TPMS are shown to be a versatile source of biomorphic scaffold design. A set of tissue scaffolds using the TPMS-based unit cell libraries was designed. TPMS-based Titanium foams were meant to be printed three dimensional with the relative predicted geometry, microstructure and consequently mechanical properties. Trough a finite element analysis (FEA) the mechanical properties of the designed scaffolds were determined in compression and analyzed in terms of their porosity and assemblies of unit cells. The purpose of this work was to investigate the mechanical performance of TPMS models trying to understand the best compromise between mechanical and geometrical requirements of the scaffolds. The intention was to predict the structural modulus in open porous materials via structural design of interconnected three-dimensional lattices, hence optimising geometrical properties. With the aid of FEA results, it is expected that the effective mechanical properties for the TPMS-based scaffold units can be used to design optimized scaffolds for tissue engineering applications. Regardless of the influence of fabrication method, it is desirable to calculate scaffold properties so that the effect of these properties on tissue regeneration may be better understood.

Design and implementation of an anonymous peer-to-peer iaas cloud

Cloud services are becoming ever more important for everyone's life. Cloud storage? Web mails? Yes, we don't need to be working in big IT companies to be surrounded by cloud services. Another thing that's growing in importance, or at least that should be considered ever more important, is the concept of privacy. The more we rely on services of which we know close to nothing about, the more we should be worried about our privacy. In this work, I will analyze a prototype software based on a peer to peer architecture for the offering of cloud services, to see if it's possible to make it completely anonymous, meaning that not only the users using it will be anonymous, but also the Peers composing it will not know the real identity of each others. To make it possible, I will make use of anonymizing networks like Tor. I will start by studying the state of art of Cloud Computing, by looking at some real example, followed by analyzing the architecture of the prototype, trying to expose the differences between its distributed nature and the somehow centralized solutions offered by the famous vendors. After that, I will get as deep as possible into the working principle of the anonymizing networks, because they are not something that can just be 'applied' mindlessly. Some de-anonymizing techniques are very subtle so things must be studied carefully. I will then implement the required changes, and test the new anonymized prototype to see how its performances differ from those of the standard one. The prototype will be run on many machines, orchestrated by a tester script that will automatically start, stop and do all the required API calls. As to where to find all these machines, I will make use of Amazon EC2 cloud services and their on-demand instances.

Design of an indirectly fired gas turbine integrated with an organic rankine cycle unit for combined heat and power production

In the last years, the European countries have paid increasing attention to renewable sources and greenhouse emissions. The Council of the European Union and the European Parliament have established ambitious targets for the next years. In this scenario, biomass plays a prominent role since its life cycle produces a zero net carbon dioxide emission. Additionally, biomass can ensure plant operation continuity thanks to its availability and storage ability. Several conventional systems running on biomass are available at the moment. Most of them are performant either in the large-scale or in the small power range. The absence of an efficient system on the small-middle scale inspired this thesis project. The object is an innovative plant based on a wet indirectly fired gas turbine (WIFGT) integrated with an organic Rankine cycle (ORC) unit for combined heat and power production. The WIFGT is a performant system in the small-middle power range; the ORC cycle is capable of giving value to low-temperature heat sources. Their integration is investigated in this thesis with the aim of carrying out a preliminary design of the components. The targeted plant output is around 200 kW in order not to need a wide cultivation area and to avoid biomass shipping. Existing in-house simulation tools are used: They are adapted to this purpose. Firstly the WIFGT + ORC model is built; Zero-dimensional models of heat exchangers, compressor, turbines, furnace, dryer and pump are used. Different fluids are selected but toluene and benzene turn out to be the most suitable. In the indirectly fired gas turbine a pressure ratio around 4 leads to the highest efficiency. From the thermodynamic analysis the system shows an electric efficiency of 38%, outdoing other conventional plants in the same power range. The combined plant is designed to recover thermal energy: Water is used as coolant in the condenser. It is heated from 60°C up to 90°C, ensuring the possibility of space heating. Mono-dimensional models are used to design the heat exchange equipment. Different types of heat exchangers are chosen depending on the working temperature. A finned-plate heat exchanger is selected for the WIFGT heat transfer equipment due to the high temperature, oxidizing and corrosive environment. A once-through boiler with finned tubes is chosen to vaporize the organic fluid in the ORC. A plate heat exchanger is chosen for the condenser and recuperator. A quasi-monodimensional model for single-stage axial turbine is implemented to design both the WIFGT and the ORC turbine. The system simulation after the components design shows an electric efficiency around 34% with a decrease by 10% compared to the zero-dimensional analysis. The work exhibits the system potentiality compared to the existing plants from both technical and economic point of view.

Design and implementation of a Reinforcement Learning framework for iOS devices

Reinforcement Learning is an increasingly popular area of Artificial Intelligence. The applications of this learning paradigm are many, but its application in mobile computing is in its infancy. This study aims to provide an overview of current Reinforcement Learning applications on mobile devices, as well as to introduce a new framework for iOS devices: Swift-RL Lib. This new Swift package allows developers to easily support and integrate two of the most common RL algorithms, Q-Learning and Deep Q-Network, in a fully customizable environment. All processes are performed on the device, without any need for remote computation. The framework was tested in different settings and evaluated through several use cases. Through an in-depth performance analysis, we show that the platform provides effective and efficient support for Reinforcement Learning for mobile applications.

Neural Network Based UAV Fault Tolerant Control with Aerodynamic Disturbance Estimation and Compensation

In this thesis, the problem of controlling a quadrotor UAV is considered. It is done by presenting an original control system, designed as a combination of Neural Networks and Disturbance Observer, using a composite learning approach for a system of the second order, which is a novel methodology in literature. After a brief introduction about the quadrotors, the concepts needed to understand the controller are presented, such as the main notions of advanced control, the basic structure and design of a Neural Network, the modeling of a quadrotor and its dynamics. The full simulator, developed on the MATLAB Simulink environment, used throughout the whole thesis, is also shown. For the guidance and control purposes, a Sliding Mode Controller, used as a reference, it is firstly introduced, and its theory and implementation on the simulator are illustrated. Finally the original controller is introduced, through its novel formulation, and implementation on the model. The effectiveness and robustness of the two controllers are then proven by extensive simulations in all different conditions of external disturbance and faults.