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Your search keyword '"Maurizio Cirrincione"' showing total 3 results
Start Over Author "Maurizio Cirrincione" Journal 2018 21st international conference on electrical machines and systems (icems)
3 results on '"Maurizio Cirrincione"'

1. FPGA-Based Multi-Parametric Non-Linear Model Predictive Control for a Micro-Grid in Small Islands

Author

Maurizio Cirrincione, Krishnil R. Ram, H. K. Mudaliar, Ali Mohammadi, S. Rokocakau, D. M. Kumar, and Mansour H. Assaf

Subjects
business.industry, Computer science, 020209 energy, Control engineering, 02 engineering and technology, Function (mathematics), Renewable energy, Non linear model predictive control, Model predictive control, Gate array, 0202 electrical engineering, electronic engineering, information engineering, Torque, Microgrid, Field-programmable gate array, business
Abstract

This paper studies the concept of Non-linear Predictive Control (NMPC) to micro-grid in remote small islands in Fiji or the Pacific region. A multi-parametric model with a suitable cost function is considered for a microgrid supplied by renewable energy sources and with a flywheel energy storage system The proposed control strategy has been designed for implementation on an Field-Programmable gate array (FPGA) board, for its the great advantages of reducing the overall system cost, size, and realtime operation, making it suitable for easy and cheap application in small islands or villages.

Published
2018

2. Induction Machine Fault Diagnosis Using Stator Current Subspace Spectral Estimation

Author

Giansalvo Cirrincione, Mauro Andriollo, A. Tortella, Rahul R Kumar, and Maurizio Cirrincione

Subjects
parametric methods, Stator, Computer science, 020209 energy, Feature extraction, 02 engineering and technology, law.invention, law, induction machine, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, signal processing, Artificial neural network, business.industry, feature extraction, Mechanical Engineering, 020208 electrical & electronic engineering, fault diagnosis, neural networks, Spectral density estimation, Pattern recognition, Perceptron, Statistical classification, Harmonics, Artificial intelligence, business, Subspace topology
Abstract

This paper presents a subspace-based approach to identify and extract harmonics of interest for the diagnosis of stator and rotor related faults in induction machines. The maj or goal of this paper is firstly to introduce and highlight the effectiveness of prominence measure upon preparing features for classification of faults. Secondly, a new approach is presented here to retrieve harmonics by using prominence measure of the peaks for each case of the fault. Finally, a hierarchical multi-layer perceptron neural network has been used as the classifier and compared with other existing classification algorithms to deduce the best model. The effectiveness of the developed scheme is verified experimentally.

Published
2018

3. Effect of the Temperature Distribution on the Performance of PEMFC Stacks for Fault Diagnosis

Author

Abdesslem Djerdir, Giansalvo Cirrincione, Djafar Chabane, Maurizio Cirrincione, Ali Mohammadi, University of the South Pacific (USP), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), and Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Materials science, Nuclear engineering, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Proton exchange membrane fuel cell, 02 engineering and technology, 010402 general chemistry, 021001 nanoscience & nanotechnology, Fault (power engineering), 7. Clean energy, 01 natural sciences, Temperature measurement, Fault detection and isolation, [SPI.AUTO]Engineering Sciences [physics]/Automatic, 0104 chemical sciences, Stack (abstract data type), Thermocouple, [PHYS.MECA.THER]Physics [physics]/Mechanics [physics]/Thermics [physics.class-ph], [PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph], 0210 nano-technology, Current density, Voltage
Abstract

International audience; This paper presents the temperature distribution on a PEMFC stack which can be used for fault diagnosis. The effect of the temperature is considered on the performance of one single fuel cell both theoretically and experimentally. In order to validate the effect of temperature distribution, several tests were carried out with different operating conditions in one single cell. Thus, according to the variation of temperature, different parameters vary linked to the voltage losses and current density, recognized in the FC thermocouples installed in three different regions of stack FC. The results show good recognition for the considered faults in a stack PEMFC on the basis of temperature distribution.

Published
2018

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