39 resultados para Isodirectionality Principle

em Universidade do Minho


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This paper presents a comprehensive comparison of a current-source converter and a voltage-source converter for three-phase electric vehicle (EV) fast battery chargers. Taking into account that the current-source converter (CSC) is a natural buck-type converter, the output voltage can assume a wide range of values, which varies between zero and the maximum instantaneous value of the power grid phase-to-phase voltage. On the other hand, taking into account that the voltage-source converter (VSC) is a natural boost-type converter, the output voltage is always greater than the maximum instantaneous value of the power grid phase-to-phase voltage, and consequently, it is necessary to use a dc-dc buck-type converter for applications as EV fast battery chargers. Along the paper is described in detail the principle of operation of both the CSC and the VSC for EV fast chargers, as well as the main equations of the power theory and current control strategies. The comparison between both converters is mainly established in terms of the total harmonic distortion of the grid current and the estimated efficiency for a range of operation between 10 kW and 50 kW.

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This paper presents a novel architecture of a bidirectional bridgeless interleaved converter for battery chargers of electric vehicles (EVs). The proposed converter is composed by two power stages: an ac-dc converter that is used to interface the power grid and the dc-link, and a dc-dc converter that is used to interface the dc-link and the batteries. The ac-dc converter is an interleaved bridgeless bidirectional boost-type converter and the dc-dc converter is a bidirectional buck-boost-type converter. The proposed converter works with sinusoidal grid current and with high power factor for all operating power levels, and in both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operation modes. In the paper is described in detail the proposed converter for EV battery chargers: the circuit topology, the principle of operation, the power control theory, and the current control strategy. Several simulation results for both G2V and V2G operation modes are presented.

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This paper presents a novel concept of unidirectional bridgeless combined boost-buck converter for electric vehicles (EVs) battery chargers. The proposed converter is composed by two power stages: an ac-dc front-end converter used to interface the power grid and the dc-link, and a dc-dc back-end converter used to interface the dc-link and the batteries. The ac-dc converter is a bridgeless boost-type converter and the dc-dc converter is an interleaved buck-type converter. The proposed converter operates with sinusoidal grid current and unitary power factor for all operating power levels. Along the paper is described in detail the proposed converter for EV battery chargers: the circuit topology, the different stages describing the principle of operation, the power control theory, and the current control strategy, for both converters. Along the paper are presented several simulation results for a maximum power of 3.5 kW.

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This work presents a model and a heuristic to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving problems with one vehicle was presented, and this heuristic provides good results in terms of accuracy and computation time.

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This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.

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Relatório de estágio de mestrado em Ensino de Música

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Dissertação de mestrado em Bioinformática

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An increasing number of m-Health applications are being developed benefiting health service delivery. In this paper, a new methodology based on the principle of calm computing applied to diagnostic and therapeutic procedure reporting is proposed. A mobile application was designed for the physicians of one of the Portuguese major hospitals, which takes advantage of a multi-agent interoperability platform, the Agency for the Integration, Diffusion and Archive (AIDA). This application allows the visualization of inpatients and outpatients medical reports in a quicker and safer manner, in addition to offer a remote access to information. This project shows the advantages in the use of mobile software in a medical environment but the first step is always to build or use an interoperability platform, flexible, adaptable and pervasive. The platform offers a comprehensive set of services that restricts the development of mobile software almost exclusively to the mobile user interface design. The technology was tested and assessed in a real context by intensivists.

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The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

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Dissertação de mestrado em Direito dos Contratos e da Empresa

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Tese de Doutoramento em Ciências Jurídicas (área de especialização em Ciências Jurídicas - Públicas)

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Dissertação de mestrado em Direito Tributário e Fiscal

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Tese de Doutoramento em Ciências Jurídicas (área de especialização em Ciências Jurídicas Públicas).