Model-based-design to develop sensorless fan
Halin, Anaïs
Promoteur(s) :
Geuzaine, Christophe
Date de soutenance : 26-jui-2017/27-jui-2017 • URL permanente : http://hdl.handle.net/2268.2/2515
Détails
Titre : | Model-based-design to develop sensorless fan |
Auteur : | Halin, Anaïs ![]() |
Date de soutenance : | 26-jui-2017/27-jui-2017 |
Promoteur(s) : | Geuzaine, Christophe ![]() |
Membre(s) du jury : | Vanderbemden, Philippe ![]() Drion, Guillaume ![]() Lambrechts, Marc |
Langue : | Anglais |
Nombre de pages : | 76 |
Mots-clés : | [en] BLDC motor [en] modelling [en] Matlab |
Discipline(s) : | Ingénierie, informatique & technologie > Ingénierie électrique & électronique |
Institution(s) : | Université de Liège, Liège, Belgique |
Diplôme : | Master en ingénieur civil électricien, à finalité spécialisée en "electrical engineering" |
Faculté : | Mémoires de la Faculté des Sciences appliquées |
Résumé
[en] Melexis specializes in developing robust sensorless actuators integrated circuits for automotive applications like water-oil-fuel pumps, engine cooling fans and hvac (heating, ventilating, and air conditioning) blowers.
This master thesis intends for the iterative development of a realistic electro-mechanical system model for existing hvac blowers, controlled without sensors (sensorless control loop), via electronics that measure motor current and motor voltage (self-sensing solution). It aims to predict the behavior of the fan for various control algorithms. Purpose is to accelerate future designs with efficient and robust control algorithms for self-sensing fans and pumps.
In order to reach these objectives, the first step is to select the modelling tool, then to create a model (first in open-loop, then in closed-loop) with available BLDC (brushless direct current) motor systems knowhow from Melexis application engineers. This is done by performing iterative fitting with real system behaviour and simplifying the model to the essence.
Furthermore, this document presents a way to find the electrical and mechanical motor’s parameters which are necessary to run the model. Finally, the model allowed to perform a parametric analysis for hvac blowers enabling to better understand the key parameters influencing the behavior of such systems.
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