A Full Order Sensorless Control Adaptive Observer for Doubly-Fed Induction Generator

This paper presents a sensorless control for a Doubly Fed Induction Generator (DFIG) in the context of grid-connected turbine-based wind generation systems. The paper proposes a full order adaptive observer able to track with excellent accuracy the DFIG rotor position even in presence of significant parameters deviations. The developed adaptive observer is coupled with a traditional stator flux based Field Oriented Control (FOC). The novel approach has been validated by an extensive numerical analysis

Collaborative improvement as an inspiration for supply chain collaboration

The battlefield of competition is today moving from the level of\ud individual firms to the one of the extended enterprises, that is, networks of customers and their suppliers. This paper discusses how learning and continuous improvement today take place in processes based on daily collaboration at intercompany level, i.e. Extended Manufacturing Enterprises (EMEs). The purpose of the paper is to present a preliminary theory on Collaborative Improvement (CoI), i.e. continuous improvement at the EME level. Based on a literature review on Supply Networks, and Continuous Improvement and on evidence from two explorative case studies, the paper proposes a model for Collaborative Improvement in EMEs and discusses a research approach based on Action Research and Action Learning to further develop preliminary theory and actionable knowledge on how to foster and sustain CoI in EMEs

Doubly-Fed Induction Generator (DFIG) in Connected or Weak Grids for Turbine-Based Wind Energy Conversion System

In the last thirty years the quantity of wind electricity generation has grown significantly due to its high-power density. Advances in wind energy technology have significantly decreased the cost of producing electricity from this renewable source. Nowadays, the generation of energy from wind sources plays a crucial role to increasing the green energy. In this context, wind energy conversion systems (WEC) must guarantee, in connected or weak grid operation, good stability in balanced or unbalanced conditions, high efficiency, high reliability and maximum power tracking in order to achieve the best performance when operating conditions vary

Thermally activated magnetization reversal in bulk BiFe0.5Mn0.5O3

We report on the synthesis and characterization of BiFe0.5Mn0.5O3, a potential type-I multiferroic compound displaying temperature induced magnetization reversal. Bulk samples were obtained by means of solid state reaction carried out under the application of hydrostatic pressure at 6 GPa and 1100{\deg}C. The crystal structure is an highly distorted perovskite with no cation order on the B site, where, besides a complex scheme of tilt and rotations of the TM-O6 octahedra, large off-centering of the bismuth ions is detected. Below T1 = 420 K the compound undergoes a first weak ferromagnetic transition related to the ordering of iron rich clusters. At lower temperatures (just below RT) two distinct thermally activated mechanisms are superimposed, inducing at first an enhancement of the magnetization at T2 = 288 K, then a spontaneous reversal process centered at T3 = 250 K, finally giving rise to a negative response. The application of fields higher than 1500 Oe suppresses the process, yielding a ferromagnetic like behaviour. The complementary use of SQuID magnetometry and M\"ossbauer spectroscopy allowed the interpretation of the overall magnetic behaviour in terms of an uncompensated weak competitive coupling between non-equivalent clusters of interactions characterized by different critical temperatures and resultant magnetizations. PACS numbers: 75.85.+t, 75.60.Jk, 76.80.+y, 75.30.Et, 75.30.KzComment: 30 pages, 13 figure

Integrated BMS-MMC Balancing Technique Highlighted by a Novel Space-Vector Based Approach for BEVs Application

This paper proposes a new mathematical model of modular multilevel converters for battery electric vehicles with space-vectors enabling a critical analysis of cell balancing for the battery management system. In particular, the requirements for power balancing and the actual number of degrees of freedom of the control are investigated. The paper shows that the traditional approach of cell balancing is a special case of the proposed control methodology. Numerical analyses with Matlab/Simulink™ highlight the reasons of the slow response of the standard balancing technique for specific operating conditions of the battery electric vehicle. The paper suggests potential improvements that could be introduced through the proposed generalised approach

From sustainability commitment to performance:The role of intra- and inter- firm collaborative capabilities in the upstream supply chain

International audienceOrganisations increasingly see sustainability as an important element of their business strategies, and the role of purchasing and supply functions is critical in translating sustainability commitment into performance. Yet, the impact of sustainability commitment on purchasing processes and routines, as well as the effect of such capabilities on performance, remains empirically under-explored. From a Resource-Based perspective, we argue that commitment to sustainability leads purchasing and supply functions to develop intra-and inter-firm collaborative capabilities, and that in turn these capabilities deliver improved performance. Based on survey data from 383 procurement executives in ten European and North American countries, we use structural equation modelling to empirically test our hypotheses. Our results provide strong support for the hypothesised links between sustainability commitment and both intra-and inter-firm collaborative capabilities; and between inter-firm collaborative capabilities and environmental and social, and cost performance. Conversely, our data do not support the hypothesised links between intra-firm collaborative capabilities and both aspects of performance. In our discussion, we reflect on both confirmatory and conflicting findings in relation to theory and practice, before examining the study's limitations and opportunities for future research

Alternative uses of temporary work and new forms of work organisation

The purpose of this study is to investigate the relationship between the use of temporary workers and the adoption of new forms of work organisation (NFWO) in production. This study aims to understand to what extent these two forms of human resources flexibility are synergic or mutually exclusive. In order to answer this main goal, we discuss different levels of temporary workers adoption in relation to different levels of use of NFWO, the level of integration of temporary workers within the overall production organisation and the joint and synergistic use of NFWO and temporary work. Evidence drawn from seven case studies in manufacturing plants in northern Italy is provided. Results highlight that, according to the characteristics of the production process, temporary workers and NFWO are not mutually exclusive, that temporary workers can be integrated with other workers in the shop floor, and that NFWO can also be adopted for temporary workers. In addition, NFWO has been proven to be a key enabler to integrate temporary workers within the organisation, thus showing an important synergistic effect between the two human resource flexibility practices

Detection of patients with COVID-19 by the emergency medical services in Lombardy through an operator-based interview and machine learning models

BackgroundThe regional emergency medical service (EMS) in Lombardy (Italy) developed clinical algorithms based on operator-based interviews to detect patients with COVID-19 and refer them to the most appropriate hospitals. Machine learning (ML)-based models using additional clinical and geospatial epidemiological data may improve the identification of infected patients and guide EMS in detecting COVID-19 cases before confirmation with SARS-CoV-2 reverse transcriptase PCR (rtPCR).MethodsThis was an observational, retrospective cohort study using data from October 2020 to July 2021 (training set) and October 2021 to December 2021 (validation set) from patients who underwent a SARS-CoV-2 rtPCR test within 7 days of an EMS call. The performance of an operator-based interview using close contact history and signs/symptoms of COVID-19 was assessed in the training set for its ability to determine which patients had an rtPCR in the 7 days before or after the call. The interview accuracy was compared with four supervised ML models to predict positivity for SARS-CoV-2 within 7 days using readily available prehospital data retrieved from both training and validation sets.ResultsThe training set includes 264 976 patients, median age 74 (IQR 55-84). Test characteristics for the detection of COVID-19-positive patients of the operator-based interview were: sensitivity 85.5%, specificity 58.7%, positive predictive value (PPV) 37.5% and negative predictive value (NPV) 93.3%. Contact history, fever and cough showed the highest association with SARS-CoV-2 infection. In the validation set (103 336 patients, median age 73 (IQR 50-84)), the best-performing ML model had an AUC of 0.85 (95% CI 0.84 to 0.86), sensitivity 91.4% (95 CI% 0.91 to 0.92), specificity 44.2% (95% CI 0.44 to 0.45) and accuracy 85% (95% CI 0.84 to 0.85). PPV and NPV were 13.3% (95% CI 0.13 to 0.14) and 98.2% (95% CI 0.98 to 0.98), respectively. Contact history, fever, call geographical distribution and cough were the most important variables in determining the outcome.ConclusionML-based models might help EMS identify patients with SARS-CoV-2 infection, and in guiding EMS allocation of hospital resources based on prespecified criteria