45 resultados para Electric motor industry


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Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

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This paper proposes a single-phase reconfigurable battery charger for Electric Vehicle (EV) that operates in three different modes: Grid-to-Vehicle (G2V) mode, in which the traction batteries are charged from the power grid; Vehicle-to-Grid (V2G) mode, in which the traction batteries deliver part of the stored energy back to the power grid; and in Traction-to-Auxiliary (T2A) mode, in which the auxiliary battery is charged from the traction batteries. When connected to the power grid, the battery charger works with sinusoidal current in the AC side, for both G2V and V2G modes, and also regulates the reactive power. When the EV is disconnected from the power grid, the control algorithms are modified and the full-bridge AC-DC bidirectional converter works as a full-bridge isolated DC-DC converter that is used to charge the auxiliary battery of the EV, avoiding the use of an additional charger to accomplish this task. To assess the behavior of the proposed reconfigurable battery charger under different operation scenarios, a 3.6 kW laboratory prototype has been developed and experimental results are presented.

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Dissertação de mestrado em Engenharia Industrial

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Dissertação de mestrado integrado em Engenharia e Gestão Industrial

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Proceedings da AUTEX 2015, Bucareste, Roménia.

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ICEIM – International Conference in Entrepreneurship and Innovation Management, Roma, 17-18 de setembro de 2015.

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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

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Dissertação de mestrado em Engenharia Mecatrónica

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Biofilms in food processing plants represent not only a problem to human health but also cause economic losses by technical failure in several systems. In fact, many foodborne outbreaks have been found to be associated with biofilms. Biofilms may be prevented by regular cleaning and disinfection, but this does not completely prevent biofilm formation. Besides, due to their diversity and to the development of specialized phenotypes, it is well known that biofilms are more resistant to cleaning and disinfection than planktonic microorganisms. In recent years, a considerable effort has been made in the prevention of microbial adhesion and biofilm formation on food processing surfaces and novel technologies have been introduced. In this context, this chapter discusses the main conventional and emergent strategies that have been employed to prevent bacterial adhesion to food processing surfaces and thus to efficiently maintain good hygiene throughout the food industries.

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The prelims comprise: * Half-Title Page * Dedication Page * Title Page * Copyright Page * Table of Contents * Foreword * Acknowledgements * Disclaimer * Introduction

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Dissertação de mestrado em Geociências (área de especialização em Recursos Geológicos)

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Dissertação de mestrado integrado em Engenharia Mecânica

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This paper presents the main operation modes for an electric vehicle (EV) battery charger framed in smart grids and smart homes, i.e., are discussed the present-day and are proposed new operation modes that can represent an asset towards EV adoption. Besides the well-known grid to vehicle (G2V) and vehicle to grid (V2G), this paper proposes two new operation modes: Home-to-vehicle (H2V), where the EV battery charger current is controlled according to the current consumption of the electrical appliances of the home (this operation mode is combined with the G2V and V2G); Vehicle-for-grid (V4G), where the EV battery charger is used for compensating current harmonics or reactive power, simultaneously with the G2V and V2G operation modes. The vehicle-to-home (V2H) operation mode, where the EV can operate as a power source in isolated systems or as an off-line uninterruptible power supply to feed priority appliances of the home during power outages of the electrical grid is presented in this paper framed with the other operation modes. These five operation modes were validated through experimental results using a developed 3.6 kW bidirectional EV battery charger prototype, which was specially designed for these operation modes. The paper describes the developed EV battery charger prototype, detailing the power theory and the voltage and current control strategies used in the control system. The paper presents experimental results for the various operation modes, both in steady-state and during transients.