1,721,040 research outputs found
Assistance énergétique à base de supercondensateurs pour les sources hybrides à pile à combustible : applications automobiles
No full textID = 569National audienc
Stratégies Avancées de Gestion d'Énergie pour Véhicules Electriques Hybrides à Pile à Combustible
No full textLes Véhicules Electrique Hybride à Hydrogène (FHCEVs) suscitent l'intérêt en tant que solutions de mobilité durables, mais des défis subsistent quant à leur adoption à l'échelle mondiale. L'un des défis majeur de cette topologie réside dans la complexité du contrôle de sont système de stockage d'énergie hybride.La première contribution de cette thèse est l'introduction d'un nouveau paradigme combinant les trois familles de Stratégie de Gestion d'Energie (EMS) structuant les littérature au sein d'une même architecture : l'iEMS. Le concept de l'EMS intégrée (iEMS) vise à fournir une méthodologie simplifiant le processus complexe de conception d'une EMS avancée.Notre deuxième contribution réside dans la construction d'une EMS prometteuse et avancée développée grâce à notre méthode iEMS, intégrant une stratégie d'optimisation en ligne innovent reposant sur une stratégie d'utilisation de la batterie dynamique et la reconnaissance de schémas de conduite. Cette iEMS de référence affiche une performance de plus de 98 % par rapport à l'algorithme optimal du principe du minimum de Pontryaguin hors ligne.Enfin, nous avons conçu un modèle de prédiction de vitesse en parallèle d'une méthodologie basé sur un réseau de neurones « long-short term memory » pour adapter notre iEMS de référence aux conditions du monde réel.L'iEMS comble les lacunes dans les stratégies de gestion de l'énergie pour les FCHEVs favorisant l'efficacité et prolongeant la durée de vie des sources d'énergie. Notre focalisation sur les FCHEVs peut s'étendre à d'autres modes de propulsion, offrant un vaste potentiel d'innovation.This thesis pioneers advanced Energy Management Strategies (EMS) for Fuel Cell Hybrid Electric Vehicles (FCHEVs) in the context of pressing global environmental challenges. FCHEVs have gained attention as sustainable mobility solutions, but challenges remain to their global adoption.Our work contributes by introducing the innovative iEMS framework, integrating optimal, rule-based, and learning-based strategies. The iEMS concept is proposed to simplify the complex process of designing an advanced EMS, reducing energy consumption in real-time conditions.Our second contribution is a promising and advanced EMS developed within our iEMS framework, incorporating SOC targeting mechanisms, a fuzzy logic controller, a driving pattern recognizer, and an online PMP. This reference EMS showcases a performance of more than 98% compared with the offline and optimal PMP algorithm.Finally, we successfully designed a Long Short-Term Memory neural network velocity prediction model and methodology to adapt our reference iEMS to real-world conditions.The iEMS framework addresses gaps in energy management strategies for fuel cell vehicles, promoting efficiency and prolonging energy source lifespan. Our focus on FCHEVs can extend to other propulsion modes, offering vast innovation potential
Contribution à l'étude d'électro-générateurs à pile à combustible (conceptions d'architectures et de leurs commandes)
No full textORSAY-PARIS 11-BU Sciences (914712101) / SudocSudocFranceF
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Health-conscious energy management strategy based on fault diagnosis/prognosis for a fuel cell/battery hybride electric vehicle
No full textLe concept des systèmes d'énergie hybrides a amélioré considérablement les performances dynamiques, l'efficacité énergétique et la durée de vie des systèmes énergétiques, ce qui est très prometteur pour les chaines de conversion électrifiées. Ces dernières années, l'hybridation pile à combustible à membrane d'échange de protons (PEMFC) avec des batteries lithium (Libs) a été particulièrement mise en évidence par de nombreux projets de recherche. La stratégie de gestion d'énergie (EMS) joue un rôle essentiel au niveau de la supervision de ce type de système. Elle pilote les flux d'énergie entre les différentes sources pour satisfaire la charge tout en améliorant l'efficacité opérationnelle. Une EMS intelligente et performante doit être supportée par des résultats fiables relatifs au diagnostic / pronostic de chaque source, à savoir le diagnostic / pronostic de la PEMFC et les Libs qui est indispensable pour la synthèse d'une stratégie EMS consciente de leur santé. Cependant, les travaux de recherche actuels s'appuient souvent sur une décorrélation entre l'EMS et le diagnostic / pronostic associé. Ainsi, l'objectif principal de ces travaux est le développement d'un module de diagnostic/pronostic de chaque source et son intégration dans la synthèse de l'EMS. Les approches seront fondées sur des techniques d'intelligence artificielle au moyen d'un processus d'auto-apprentissage des données opérationnelles.The concept of hybrid energy systems have considerably improved dynamic performance, energy efficiency and lifespan of energetic systems, which is very promising for the powertrain system in electrified vehicles. Especially the effectiveness of hybrid system based on polymer electrolyte membrane fuel cells (PEMFCs) and lithium-ion batteries (LIBs) has been highlighted by many research projects in recent years. In such system, energy management strategy (EMS) plays a critical role in the supervisory level. It manage the power flow among the different power sources, to meet the power demand and to improve the operation efficiency. A smart EMS should be supported by reliable diagnostic/prognostic results of the single power source. Namely, the topic of diagnostic/prognostic of PEMFCs and LIBs is indispensable when designing a health-conscious EMS. However, the current research work of designing EMS and executing diagnostic/prognostic of ESS is usually independent of each other. Therefore, in this PhD project, integrating the diagnosis/prognosis module of each power source into EMS design is the primary aim. Especially, the proposed health-aware EMS and the module of diagnostic/prognostic will be based on artificial intelligence techniques through operation data self-learning process
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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