Design and implementation of machine learning techniques for modeling and managing battery energy storage systems

The fast technological evolution and industrialization that have interested the humankind since the fifties has caused a progressive and exponential increase of CO2 emissions and Earth temperature. Therefore, the research community and the political authorities have recognized the need of a deep technological revolution in both the transportation and the energy distribution systems to hinder climate changes. Thus, pure and hybrid electric powertrains, smart grids, and microgrids are key technologies for achieving the expected goals. Nevertheless, the development of the above mentioned technologies require very effective and performing Battery Energy Storage Systems (BESSs), and even more effective Battery Management Systems (BMSs). Considering the above background, this Ph.D. thesis has focused on the development of an innovative and advanced BMS that involves the use of machine learning techniques for improving the BESS effectiveness and efficiency. Great attention has been paid to the State of Charge (SoC) estimation problem, aiming at investigating solutions for achieving more accurate and reliable estimations. To this aim, the main contribution has concerned the development of accurate and flexible models of electrochemical cells. Three main modeling requirements have been pursued for ensuring accurate SoC estimations: insight on the cell physics, nonlinear approximation capability, and flexible system identification procedures. Thus, the research activity has aimed at fulfilling these requirements by developing and investigating three different modeling approaches, namely black, white, and gray box techniques. Extreme Learning Machines, Radial Basis Function Neural Networks, and Wavelet Neural Networks were considered among the black box models, but none of them were able to achieve satisfactory SoC estimation performances. The white box Equivalent Circuit Models (ECMs) have achieved better results, proving the benefit that the insight on the cell physics provides to the SoC estimation task. Nevertheless, it has appeared clear that the linearity of ECMs has reduced their effectiveness in the SoC task. Thus, the gray box Neural Networks Ensemble (NNE) and the white box Equivalent Neural Networks Circuit (ENNC) models have been developed aiming at exploiting the neural networks theory in order to achieve accurate models, ensuring at the same time very flexible system identification procedures together with nonlinear approximation capabilities. The performances of NNE and ENNC have been compelling. In particular, the white box ENNC has reached the most effective performances, achieving accurate SoC estimations, together with a simple architecture and a flexible system identification procedure. The outcome of this thesis makes it possible the development of an interesting scenario in which a suitable cloud framework provides remote assistance to several BMSs in order to adapt the managing algorithms to the aging of BESSs, even considering different and distinct applications

Welfare aspects in rabbit rearing and transport

The review starts with the description of the rabbits' (Oryctolagus cuniculus) main habits and the current situation concerning the rabbit husbandry and management systems, as well as their effects on the welfare of these animals. As far as the intensive rabbit husbandry systems are concerned, the main problems are related to the time since rabbits have been domesticated and their adaptive capacity and coping styles as respects the farming environment and management systems. Both these aspects have implications in the present and future of rabbit rearing for different purposes. Examples are given on the effects of different housing and management systems on rabbit welfare, as well as examples of the ethological, physiological and productive indicators used to evaluate these effects. Transportation and, more generally, preslaughter phases including catching, fasting and lairage at the abattoir are considered major stressors for farmed rabbits and might have deleterious effects on health, well-being, performance, and finally, product quality. A general statement of the recent scientific studies considering the effects of pre-slaughter factors on physiological and productive measurements are reported. Finally, some indications in order to improve rabbit welfare, already present at the European level, are also outlined, together with the European Food Safety Authority opinions

Non-Contact Detection of Breathing Using a Microwave Sensor

In this paper the use of a continuous-wave microwave sensor as a non-contact tool for quantitative measurement of respiratory tidal volume has been evaluated by experimentation in seventeen healthy volunteers. The sensor working principle is reported and several causes that can affect its response are analyzed. A suitable data processing has been devised able to reject the majority of breath measurements taken under non suitable conditions. Furthermore, a relationship between microwave sensor measurements and volume inspired and expired at quiet breathing (tidal volume) has been found

Site response analyses for complex geological and morphological conditions: relevant case-histories from 3rd level seismic microzonation in Central Italy

The paper presents the results of 5 case studies on complex site e ects selected within the project for the level 3 seismic microzonation of several municipalities of Central Italy dam- aged by the 2016 seismic sequence. The case studies are characterized by di erent geo- logical and morphological con gurations: Monte San Martino is located along a hill slope, Montedinove and Arquata del Tronto villages are located at ridge top whereas Capitignano and Norcia lie in correspondence of sediment- lled valleys. Peculiarities of the sites are constituted by the presence of weathered/jointed rock mass, fault zone, shear wave veloc- ity inversion, complex surface and buried morphologies. These factors make the de ni- tion of the subsoil model and the evaluation of the local response particularly complex and di cult to ascertain. For each site, after the discussion of the subsoil model, the results of site response numerical analyses are presented in terms of ampli cation factors and acceleration response spectra in selected points. The physical phenomena governing the site response have also been investigated at each site by comparing 1D and 2D numerical analyses. Implications are deduced for seismic microzonation studies in similar geological and morphological conditions.Published5741–57775T. Sismologia, geofisica e geologia per l'ingegneria sismicaJCR Journa

Site Amplifications in the epicentral area of the 2016, M 6, Amatrice earthquake (Italy)

The first mainshock (Mw 6.0) of the 2016 Central Italy seismic sequence, severely struck the Amatrice village and the surrounding localities. After a few days, some Italian Institutions, coordinated by the “Center for Seismic Microzonation and its applications”, carried out several preparatory activities for seismic microzonation of the area. A temporary seismic network was installed that monitored about 50 sites in epicentral area. The network produced a huge amount of records in a wide range of magnitude up to Mw 6.5. For about half of the recording stations, detailed site characterization was undertaken, encompassing single station noise measurements and S-wave velocity profiles. The geological and geophysical data together with the collected dataset of seismic signals were exploited to investigate the site response of selected stations. Significant amplifications are found in the correspondence of several sites that experienced a high level of damage (Imcs >IX), mainly at short and intermediate periodsPublishedRoma5T. Sismologia, geofisica e geologia per l'ingegneria sismic

Landslide Ground Based Remote Sensing Monitoring: Formigal Case Study (Huesca, Spain)

Galahad is an ongoing Specific Targeted Research Project developed within the EU 6th Framework Programme ¿ Priority 1.1.6.3. The objective is to retrieve, through the use of improved GB-SAR and TLS technologies, field parameters that can be used in prediction algorithms of landslides, avalanches and glaciers related hazards. The landslide study area is located in the ski resort of Formigal, central Pyrenees (province of Huesca, Spain). The excavation of a parking area in the summer of 2004 reactivated a complex paleolandslide creating new sliding surfaces. The movement extends over an area of 0.25 km2 and experienced displacements as large as 0.5 cm/day during the period 2004¿2005. Stabilization engineering solutions were carried out reducing maximum observed displacement to 0.2 cm/day at the end of 2005. Within Galahad performed activities consisted in the collection of data on the landslide useful for its detailed characterization and the execution of a series of site measurement campaigns with GB-SAR, TLS and Differential GPS (D-GPS). The monitoring activities started in May 2006 completing a series of four campaigns with Total Station and D-GPS, a continuous two month data acquisition with GB-SAR and several TLS scans during two different periods from three points of view over the landslide. In this paper data obtained by GB-SAR and TLS are compared with D-GPS data, and a good agreement has been found between data sets. The project is still in progress and new site measurement campaigns with GB-SAR, TLS and D-GPS in 2007 will provide further insight into landslide forecasting models.JRC.H.7-Land management and natural hazard

Low low-density lipoprotein (LDL), cholesterol and triglycerides plasma levels are associated with reduced risk of arterial occlusive events in chronic myeloid leukemia patients treated with ponatinib in the real-life. A Campus CML study

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Determinants of frontline tyrosine kinase inhibitor choice for patients with chronic-phase chronic myeloid leukemia: A study from the Registro Italiano LMC and Campus CML

Background: Imatinib, dasatinib, and nilotinib are tyrosine kinase inhibitors (TKIs) approved in Italy for frontline treatment of chronic-phase chronic myeloid leukemia (CP-CML). The choice of TKI is based on a combined evaluation of the patient's and the disease characteristics. The aim of this study was to analyze the use of frontline TKI therapy in an unselected cohort of Italian patients with CP-CML to correlate the choice with the patient's features. Methods: A total of 1967 patients with CP-CML diagnosed between 2012 and 2019 at 36 centers throughout Italy were retrospectively evaluated; 1089 patients (55.4%) received imatinib and 878 patients (44.6%) received a second-generation (2G) TKI. Results: Second-generation TKIs were chosen for most patients aged <45 years (69.2%), whereas imatinib was used in 76.7% of patients aged >65 years (p < .001). There was a predominant use of imatinib in intermediate/high European long-term survival risk patients (60.0%/66.0% vs. 49.7% in low-risk patients) and a limited use of 2G-TKIs in patients with comorbidities such as hypertension, diabetes, chronic obstructive pulmonary disease, previous neoplasms, ischemic heart disease, or stroke and in those with >3 concomitant drugs. We observed a greater use of imatinib (61.1%) in patients diagnosed in 2018-2019 compared to 2012-2017 (53.2%; p = .002). In multivariable analysis, factors correlated with imatinib use were age > 65 years, spleen size, the presence of comorbidities, and ≥3 concomitant medications. Conclusions: This observational study of almost 2000 cases of CML shows that imatinib is the frontline drug of choice in 55% of Italian patients with CP-CML, with 2G-TKIs prevalently used in younger patients and in those with no concomitant clinical conditions. Introduction of the generic formulation in 2018 seems to have fostered imatinib use

Analysis of Early Events during the First Year of Tyrosine Kinase Inhibitor Therapy in Patients with Chronic Phase - Chronic Myeloid Leukemia: A "Campus CML" Study

Tyrosine kinase inhibitors (TKIs) revolutionized treatment of chronic myeloid leukemia (CML). However, the rst months of therapy are crucial, as optimal response is dened as the achievement of molecular milestones at 3, 6 and 12 months (mo.) and as many toxicities, also causing a TKI switch, are more frequent in the 1st yea