Pagel, Michael (2018):
Model-based diagnosis of electric cooling fan drive systems.
Darmstadt, Technische Universität,
[Ph.D. Thesis]
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20180320_Model_based_diagnosis_Pagel.pdf - Accepted Version Copyright Information: CC-BY-NC 4.0 International - Creative Commons, Attribution NonCommercial. Download (8MB) | Preview |
Item Type: | Ph.D. Thesis | ||||
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Title: | Model-based diagnosis of electric cooling fan drive systems | ||||
Language: | English | ||||
Abstract: | This work is a contribution to the field of fault detection and diagnosis for electrically driven engine cooling fans. Its main focus is on the online gathering and determination of important parameters and internal states. The algorithms are specifically designed in a resource and computing efficient manner to allow for series implementation on microcontrollers usually employed in small electrical drives. Furthermore, the developed methods for fault detection and diagnosis are characterized by a low application effort, drastically reducing the costs for transferring them to other applications. Novel algorithms are presented for determination of the winding resistance, the flux linkage over angle and the equivalent series resistance. Furthermore, a novel approach for determination of the magnet temperature is proposed, utilizing the winding temperature, which is derived from the winding resistance without requiring an additional temperature sensor. A method is presented for detection of a demagnetization event based on the flux linkage over angle. Besides that, detection of an aged DC-link capacitor and of winding faults is demonstrated. Furthermore, a novel approach is presented for detection and diagnosis of unusual load conditions, caused for example, by a blockage or dirt on the fan blade. |
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Place of Publication: | Darmstadt | ||||
Classification DDC: | 000 Allgemeines, Informatik, Informationswissenschaft > 000 Allgemeines, Wissenschaft 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik 500 Naturwissenschaften und Mathematik > 500 Naturwissenschaften 500 Naturwissenschaften und Mathematik > 510 Mathematik 500 Naturwissenschaften und Mathematik > 530 Physik 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften |
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Divisions: | 18 Department of Electrical Engineering and Information Technology 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik |
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Date Deposited: | 21 Nov 2018 14:11 | ||||
Last Modified: | 09 Jul 2020 02:22 | ||||
URN: | urn:nbn:de:tuda-tuprints-80898 | ||||
Referees: | Isermann, Prof. Dr. Rolf ; Binder, Prof. Dr. Andreas | ||||
Date of oral examination: | 5 December 2017 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/8089 | ||||
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