Multitemporal analysis of satellite imagery: implementation of a land evolution model in ALCS (ATSR LAND CLASSIFICATION SYSTEM)

In this report it was designed an innovative satellite-based monitoring approach applied on the Iraqi Marshlands to survey the extent and distribution of marshland re-flooding and assess the development of wetland vegetation cover. The study, conducted in collaboration with MEEO Srl , makes use of images collected from the sensor (A)ATSR onboard ESA ENVISAT Satellite to collect data at multi-temporal scales and an analysis was adopted to observe the evolution of marshland re-flooding. The methodology uses a multi-temporal pixel-based approach based on classification maps produced by the classification tool SOIL MAPPER ®. The catalogue of the classification maps is available as web service through the Service Support Environment Portal (SSE, supported by ESA). The inundation of the Iraqi marshlands, which has been continuous since April 2003, is characterized by a high degree of variability, ad-hoc interventions and uncertainty. Given the security constraints and vastness of the Iraqi marshlands, as well as cost-effectiveness considerations, satellite remote sensing was the only viable tool to observe the changes taking place on a continuous basis. The proposed system (ALCS – AATSR LAND CLASSIFICATION SYSTEM) avoids the direct use of the (A)ATSR images and foresees the application of LULCC evolution models directly to „stock‟ of classified maps. This approach is made possible by the availability of a 13 year classified image database, conceived and implemented in the CARD project (http://earth.esa.int/rtd/Projects/#CARD).The approach here presented evolves toward an innovative, efficient and fast method to exploit the potentiality of multi-temporal LULCC analysis of (A)ATSR images. The two main objectives of this work are both linked to a sort of assessment: the first is to assessing the ability of modeling with the web-application ALCS using image-based AATSR classified with SOIL MAPPER ® and the second is to evaluate the magnitude, the character and the extension of wetland rehabilitation.

Virtual Calibration of CO2 and Pollutant Emissions of a High-Performance PHEV using Model-in-the-Loop Methodology

The study analyses the calibration process of a newly developed high-performance plug-in hybrid electric passenger car powertrain. The complexity of modern powertrains and the more and more restrictive regulations regarding pollutant emissions are the primary challenges for the calibration of a vehicle’s powertrain. In addition, the managers of OEM need to know as earlier as possible if the vehicle under development will meet the target technical features (emission included). This leads to the necessity for advanced calibration methodologies, in order to keep the development of the powertrain robust, time and cost effective. The suggested solution is the virtual calibration, that allows the tuning of control functions of a powertrain before having it built. The aim of this study is to calibrate virtually the hybrid control unit functions in order to optimize the pollutant emissions and the fuel consumption. Starting from the model of the conventional vehicle, the powertrain is then hybridized and integrated with emissions and aftertreatments models. After its validation, the hybrid control unit strategies are optimized using the Model-in-the-Loop testing methodology. The calibration activities will proceed thanks to the implementation of a Hardware-in-the-Loop environment, that will allow to test and calibrate the Engine and Transmission control units effectively, besides in a time and cost saving manner.

Development of a Predictive Control Function for a Plug-in Hybrid Electric Vehicle with Electrically-heated Catalyst

This master thesis work is focused on the development of a predictive EHC control function for a diesel plug-in hybrid electric vehicle equipped with a EURO 7 compliant exhaust aftertreatment system (EATS), with the purpose of showing the advantages provided by the implementation of a predictive control strategy with respect to a rule-based one. A preliminary step will be the definition of an accurate powertrain and EATS physical model, starting from already existing and validated applications. Then, a rule-based control strategy managing the torque split between the electric motor (EM) and the internal combustion engine (ICE) will be developed and calibrated, with the main target of limiting tailpipe NOx emission by taking into account EM and ICE operating conditions together with EATS conversion efficiency. The information available from vehicle connectivity will be used to reconstruct the future driving scenario, also referred to as electronic horizon (eHorizon), and in particular to predict ICE first start. Based on this knowledge, an EATS pre-heating phase can be planned to avoid low pollutant conversion efficiencies, thus preventing high NOx emission due to engine cold start. Consequently, the final NOx emission over the complete driving cycle will be strongly reduced, allowing to comply with the limits potentially set by the incoming EURO 7 regulation. Moreover, given the same NOx emission target, the gain achieved thanks to the implementation of an EHC predictive control function will allow to consider a simplified EATS layout, thus reducing the related manufacturing cost. The promising results achieved in terms of NOx emission reduction show the effectiveness of the application of a predictive control strategy focused on EATS thermal management and highlight the potential of a complete integration and parallel development of involved vehicle physical systems, control software and connectivity data management.

Implementation of a non ground meta interpreter for defeasible logic

Human reasoning is a fascinating and complex cognitive process that can be applied in different research areas such as philosophy, psychology, laws and financial. Unfortunately, developing supporting software (to those different areas) able to cope such as complex reasoning it’s difficult and requires a suitable logic abstract formalism. In this thesis we aim to develop a program, that has the job to evaluate a theory (a set of rules) w.r.t. a Goal, and provide some results such as “The Goal is derivable from the KB5 (of the theory)”. In order to achieve this goal we need to analyse different logics and choose the one that best meets our needs. In logic, usually, we try to determine if a given conclusion is logically implied by a set of assumptions T (theory). However, when we deal with programming logic we need an efficient algorithm in order to find such implications. In this work we use a logic rather similar to human logic. Indeed, human reasoning requires an extension of the first order logic able to reach a conclusion depending on not definitely true6 premises belonging to a incomplete set of knowledge. Thus, we implemented a defeasible logic7 framework able to manipulate defeasible rules. Defeasible logic is a non-monotonic logic designed for efficient defeasible reasoning by Nute (see Chapter 2). Those kind of applications are useful in laws area especially if they offer an implementation of an argumentation framework that provides a formal modelling of game. Roughly speaking, let the theory is the set of laws, a keyclaim is the conclusion that one of the party wants to prove (and the other one wants to defeat) and adding dynamic assertion of rules, namely, facts putted forward by the parties, then, we can play an argumentative challenge between two players and decide if the conclusion is provable or not depending on the different strategies performed by the players. Implementing a game model requires one more meta-interpreter able to evaluate the defeasible logic framework; indeed, according to Göedel theorem (see on page 127), we cannot evaluate the meaning of a language using the tools provided by the language itself, but we need a meta-language able to manipulate the object language8. Thus, rather than a simple meta-interpreter, we propose a Meta-level containing different Meta-evaluators. The former has been explained above, the second one is needed to perform the game model, and the last one will be used to change game execution and tree derivation strategies.

Hybrid foundations for offshore wind turbines

Nowadays offshore wind turbines represents a valid answer for energy production but with an increasing in costs mainly due to foundation technology required. Hybrid foundations composed by suction caissons over which is welded a tower supporting the nacelle and the blades allows a strong costs reduction. Here a monopod configuration is studied in a sandy soil in a 10 m water depth. Bearing capacity, sliding resistance and pull-out resistance are evaluated. In a second part the installation process occurring in four steps is analysed. considering also the effect of stress enhancement due to frictional forces opposing to penetration growing at skirt sides both inside and outside. In a three dimensional finite element model using Straus7 the soil non-linearity is considered in an approximate way through an iterative procedure using the Yokota empirical decay curves.

"Influence of lower-limb joint models on subject-specific musculoskeletal model predictions during gait" ( "modelli muscoloscheletrici personalizzati dell'arto inferiore: Analisi dell'effetto della modellazione dei giunti sulla predizione dei carichi agenti sul sistema scheletrico durante il cammino").

The aim of the present thesis was to investigate the influence of lower-limb joint models on musculoskeletal model predictions during gait. We started our analysis by using a baseline model, i.e., the state-of-the-art lower-limb model (spherical joint at the hip and hinge joints at the knee and ankle) created from MRI of a healthy subject in the Medical Technology Laboratory of the Rizzoli Orthopaedic Institute. We varied the models of knee and ankle joints, including: knee- and ankle joints with mean instantaneous axis of rotation, universal joint at the ankle, scaled-generic-derived planar knee, subject-specific planar knee model, subject-specific planar ankle model, spherical knee, spherical ankle. The joint model combinations corresponding to 10 musculoskeletal models were implemented into a typical inverse dynamics problem, including inverse kinematics, inverse dynamics, static optimization and joint reaction analysis algorithms solved using the OpenSim software to calculate joint angles, joint moments, muscle forces and activations, joint reaction forces during 5 walking trials. The predicted muscle activations were qualitatively compared to experimental EMG, to evaluate the accuracy of model predictions. Planar joint at the knee, universal joint at the ankle and spherical joints at the knee and at the ankle produced appreciable variations in model predictions during gait trials. The planar knee joint model reduced the discrepancy between the predicted activation of the Rectus Femoris and the EMG (with respect to the baseline model), and the reduced peak knee reaction force was considered more accurate. The use of the universal joint, with the introduction of the subtalar joint, worsened the muscle activation agreement with the EMG, and increased ankle and knee reaction forces were predicted. The spherical joints, in particular at the knee, worsened the muscle activation agreement with the EMG. A substantial increase of joint reaction forces at all joints was predicted despite of the good agreement in joint kinematics with those of the baseline model. The introduction of the universal joint had a negative effect on the model predictions. The cause of this discrepancy is likely to be found in the definition of the subtalar joint and thus, in the particular subject’s anthropometry, used to create the model and define the joint pose. We concluded that the implementation of complex joint models do not have marked effects on the joint reaction forces during gait. Computed results were similar in magnitude and in pattern to those reported in literature. Nonetheless, the introduction of planar joint model at the knee had positive effect upon the predictions, while the use of spherical joint at the knee and/or at the ankle is absolutely unadvisable, because it predicted unrealistic joint reaction forces.

Organic matter deposition/resuspension in a one-dimensional physical-biogeochemical model. A modelling study

The shallow water configuration of the gulf of Trieste allows the propagation of the stress due to wind and waves along the whole water column down to the bottom. When the stress overcomes a particular threshold it produces resuspension processes of the benthic detritus. The benthic sediments in the North Adriatic are rich of organic matter, transported here by many rivers. This biological active particulate, when remaining in the water, can be transported in all the Adriatic basin by the basin-wide circulation. In this work is presented a first implementation of a resuspension/deposition submodel in the oceanographic coupled physical-biogeochemical 1-dimensional numerical model POM-BFM. At first has been considered the only climatological wind stress forcing, next has been introduced, on the surface, an annual cycle of wave motion and finally have been imposed some exceptional wave event in different periods of the year. The results show a strong relationship between the efficiency of the resuspension process and the stratification of the water column. During summer the strong stratification can contained a great quantity of suspended matter near to the bottom, while during winter even a low concentration of particulate can reach the surface and remains into the water for several months without settling and influencing the biogeochemical system. Looking at the biologic effects, the organic particulate, injected in the water column, allow a sudden growth of the pelagic bacteria which competes with the phytoplankton for nutrients strongly inhibiting its growth. This happen especially during summer when the suspended benthic detritus concentration is greater.

Development of an innovative non rule-based energy management strategy for a Hybrid Electric Vehicle, structured for predictive driving controls based on external information knowledge

Recently, the interest of the automotive market for hybrid vehicles has increased due to the more restrictive pollutants emissions legislation and to the necessity of decreasing the fossil fuel consumption, since such solution allows a consistent improvement of the vehicle global efficiency. The term hybridization regards the energy flow in the powertrain of a vehicle: a standard vehicle has, usually, only one energy source and one energy tank; instead, a hybrid vehicle has at least two energy sources. In most cases, the prime mover is an internal combustion engine (ICE) while the auxiliary energy source can be mechanical, electrical, pneumatic or hydraulic. It is expected from the control unit of a hybrid vehicle the use of the ICE in high efficiency working zones and to shut it down when it is more convenient, while using the EMG at partial loads and as a fast torque response during transients. However, the battery state of charge may represent a limitation for such a strategy. That’s the reason why, in most cases, energy management strategies are based on the State Of Charge, or SOC, control. Several studies have been conducted on this topic and many different approaches have been illustrated. The purpose of this dissertation is to develop an online (usable on-board) control strategy in which the operating modes are defined using an instantaneous optimization method that minimizes the equivalent fuel consumption of a hybrid electric vehicle. The equivalent fuel consumption is calculated by taking into account the total energy used by the hybrid powertrain during the propulsion phases. The first section presents the hybrid vehicles characteristics. The second chapter describes the global model, with a particular focus on the energy management strategies usable for the supervisory control of such a powertrain. The third chapter shows the performance of the implemented controller on a NEDC cycle compared with the one obtained with the original control strategy.

Development of Optimal Energy Management Strategies for a Hybrid Boat

The present work proposes different approaches to extend the mathematical methods of supervisory energy management used in terrestrial environments to the maritime sector, that diverges in constraints, variables and disturbances. The aim is to find the optimal real-time solution that includes the minimization of a defined track time, while maintaining the classical energetic approach. Starting from analyzing and modelling the powertrain and boat dynamics, the energy economy problem formulation is done, following the mathematical principles behind the optimal control theory. Then, an adaptation aimed in finding a winning strategy for the Monaco Energy Boat Challenge endurance trial is performed via ECMS and A-ECMS control strategies, which lead to a more accurate knowledge of energy sources and boat’s behaviour. The simulations show that the algorithm accomplishes fuel economy and time optimization targets, but the latter adds huge tuning and calculation complexity. In order to assess a practical implementation on real hardware, the knowledge of the previous approaches has been translated into a rule-based algorithm, that let it be run on an embedded CPU. Finally, the algorithm has been tuned and tested in a real-world race scenario, showing promising results.

Hardware-in-the-loop implementation of single- and dual-phase shift control for dual active bridge converters in EV applications

Isolated DC-DC converters play a significant role in fast charging and maintaining the variable output voltage for EV applications. This study aims to investigate the different Isolated DC-DC converters for onboard and offboard chargers, then, once the topology is selected, study the control techniques and, finally, achieve a real-time converter model to accomplish Hardware-In-The-Loop (HIL) results. Among the different isolated DC-DC topologies, the Dual Active Bridge (DAB) converter has the advantage of allowing bidirectional power flow, which enables operating in both Grid to Vehicle (G2V) and Vehicle to Grid (V2G) modalities. Recently, DAB has been used in the offboard chargers for high voltage applications due to SiC and GaN MOSFETs; this new technology also allows the utilization of higher switching frequencies. By empowering soft switching techniques to reduce switching losses, higher switching frequency operation is possible in DAB. There are four phase shift control techniques for the DAB converter. They are Single Phase shift, Extended Phase shift, Dual Phase shift, Triple Phase shift controls. This thesis considers two control strategies; Single-Phase, and Dual-Phase shifts, to understand the circulating currents, power losses, and output capacitor size reduction in the DAB. Hardware-In-The-Loop (HIL) experiments are carried out on both controls with high switching frequencies using the PLECS software tool and the RT box supporting the PLECS. Root Mean Square Error is also calculated for steady-state values of output voltage with different sampling frequencies in both the controls to identify the achievable sampling frequency in real-time. DSP implementation is also executed to emulate the optimized DAB converter design, and final real-time simulation results are discussed for both the Single-Phase and Dual-Phase shift controls.

Design and implementation of motorbike lean angle observers

This thesis focuses on the investigation and the implementation of different observers for the estimation of the roll angle of a motorbike. The central core of the activity is applying a Model-Based design in order to outline, simulate and implement the filters with the aim of a final comparison of the performances. This approach is crucially underlined among the chapters that articulate this document: first the design and tuning of an Extended Kalman Filter and a Complementary Filter in a pure simulation environment emphasize the most accurate choice for the particular problem. After this, several steps were performed in order to move from the aforementioned simulation environment to a real hardware application. In conclusion, several sensor configurations were tested and compared in order to highlight which sensor suite gives the best performances.

Investigating perceptual multisensory impairments in Autism through a neural network: a possible neural implementation for the shift from cross-modal competition to facilitation

Resolution of multisensory deficits has been observed in teenagers with Autism Spectrum Disorders (ASD) for complex, social speech stimuli; this resolution extends to more basic multisensory processing, involving low-level stimuli. In particular, a delayed transition of multisensory integration (MSI) from a default state of competition to one of facilitation has been observed in ASD children. In other terms, the complete maturation of MSI is achieved later in ASD. In the present study a neuro-computational model is used to reproduce some patterns of behavior observed experimentally, modeling a bisensory reaction time task, in which auditory and visual stimuli are presented in random sequence alone (A or V) or together (AV). The model explains how the default competitive state can be implemented via mutual inhibition between primary sensory areas, and how the shift toward the classical multisensory facilitation, observed in adults, is the result of inhibitory cross-modal connections becoming excitatory during the development. Model results are consistent with a stronger cross-modal inhibition in ASD children, compared to normotypical (NT) ones, suggesting that the transition toward a cooperative interaction between sensory modalities takes longer to occur. Interestingly, the model also predicts the difference between unisensory switch trials (in which sensory modality switches) and unisensory repeat trials (in which sensory modality repeats). This is due to an inhibitory mechanism, characterized by a slow dynamics, driven by the preceding stimulus and inhibiting the processing of the incoming one, when of the opposite sensory modality. These findings link the cognitive framework delineated by the empirical results to a plausible neural implementation.

Simulation and Implementation of a PMSM Sensorless Control Algorithm for Submarine Applications

In this thesis, the study and the simulation of two advanced sensorless speed control techniques for a surface PMSM are presented. The aim is to implement a sensorless control algorithm for a submarine auxiliary propulsion system. This experimental activity is the result of a project collaboration with L3Harris Calzoni, a leader company in A&D systems for naval handling in military field. A Simulink model of the whole electric drive has been developed. Due to the satisfactory results of the simulations, the sensorless control system has been implemented in C code for STM32 environment. Finally, several tests on a real brushless machine have been carried out while the motor was connected to a mechanical load to simulate the real scenario of the final application. All the experimental results have been recorded through a graphical interface software developed at Calzoni.

Design and Implementation of Single phase 230V to Three Phase Inverter Based on the Embedded System STM-32 Applied to motor control

In the field of Power Electronics, several types of motor control systems have been developed using STM microcontroller and power boards. In both industrial power applications and domestic appliances, power electronic inverters are widely used. Inverters are used to control the torque, speed, and position of the rotor in AC motor drives. An inverter delivers constant-voltage and constant-frequency power in uninterruptible power sources. Because inverter power supplies have a high-power consumption and low transfer efficiency rate, a three-phase sine wave AC power supply was created using the embedded system STM32, which has low power consumption and efficient speed. It has the capacity of output frequency of 50 Hz and the RMS of line voltage. STM32 embedded based Inverter is a power supply that integrates, reduced, and optimized the power electronics application that require hardware system, software, and application solution, including power architecture, techniques, and tools, approaches capable of performance on devices and equipment. Power inverters are currently used and implemented in green energy power system with low energy system such as sensors or microcontroller to perform the operating function of motors and pumps. STM based power inverter is efficient, less cost and reliable. My thesis work was based on STM motor drives and control system which can be implemented in a gas analyser for operating the pumps and motors. It has been widely applied in various engineering sectors due to its ability to respond to adverse structural changes and improved structural reliability. The present research was designed to use STM Inverter board on low power MCU such as NUCLEO with some practical examples such as Blinking LED, and PWM. Then we have implemented a three phase Inverter model with Steval-IPM08B board, which converter single phase 230V AC input to three phase 380 V AC output, the output will be useful for operating the induction motor.