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Implementación de control predictivo basado en modelo para la minimización de pérdidas en máquinas de inducción

Authors: Romero Martínez, Máximo;

Implementación de control predictivo basado en modelo para la minimización de pérdidas en máquinas de inducción

Abstract

El ahorro en el consumo de energía eléctrica se antoja esencial en el panorama internacional actual, siendo clave para ello la eficiencia energética en las máquinas eléctricas. En particular, el motor de inducción es uno de los mayores consumidores de electricidad a nivel mundial y, por tanto, pieza muy importante en la contribución al ahorro energético que se está promoviendo en los últimos tiempos. Es por ello por lo que se ha optado en este trabajo por aplicar los algoritmos desarrollados a este tipo de máquina eléctrica. Siguiendo esta misma línea, se pretende conseguir una mayor eficiencia de los motores de inducción mediante la minimización de sus pérdidas durante su operación. Para ello, se ha desarrollado un algoritmo mediante el cual se consigue que la máquina opere con un flujo máquina con el cual se consiguen obtener unas pérdidas mínimas en la máquina. Esta forma de aumentar la eficiencia de una máquina eléctrica es de las más eficaces. Para la implementación de todo lo comentado anteriormente, es necesario el empleo de un esquema de control que se integre en el accionamiento eléctrico a través de un convertidor de potencia. Se ha optado por uno de los controles que mayor desarrollo ha tenido en los últimos tiempos y que se presenta como una fuerte competencia a los esquemas de control tradicionales basados en controladores PID, el control predictivo basado en modelo. Para unir todas las piezas comentadas anteriormente, se elabora un simulador que permite realizar todo tipo de simulaciones que necesitemos para corroborar el correcto funcionamiento del sistema que estamos desarrollando y el cumplimiento de los objetivos que se plantearon inicialmente.

The saving in electric consumption has become essential in the current international scene, being the energy efficiency of electric machines a key part of it. Particularly, induction motors are one of the greatest electricity consumers in the world. This is why they are important in energy saving contributions nowadays. For all these reasons, this work is focused on induction machines. In this way, one of the goals of this work is to achieve an energy efficiency improvement by minimizing its losses while it is working. To solve it, an algorithm which finds the optimal flux the machine must work with to minimize power losses has been developed. This is one of the most effective ways to increase electric machines efficiency. So as to implement this, it is necessary to use a control scheme integrated in the electric drive by a power converter. I have decided to use Model Predictive Control (MPC), one of the most developed controls nowadays, which competes with traditional scheme controls based on PID controllers. In order to make all simulations needed, an effective simulator joining every single topic exposed before has been elaborated. These simulations enable us to test the proper operation of the system we are developing and the initial aims.

Universidad de Sevilla. Grado en Ingeniería de Tecnologías Industriales

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Spain
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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