Real time monitoring of capacitor degradation in industrial variable speed drives
Publication Date
July 31, 2022
Creator
Abstract
This thesis investigates a condition monitoring strategy suitable for use with monitoring the impedance of electrolytic capacitors in the DC-link of a motor drive, in contribution to the development of advanced intelligent variable speed drives.
Condition monitoring via signal injection is investigated, where signals of known frequencies are injected into the DC-link and electrical quantities are measured and used to estimate the impedance of the electrolytic capacitors at the specific frequency. Injection is achieved using two different methods: injection of a signal via a controlled AC power supply unit, and also injection of a signal via applying a controlled perturbation to motor speed. The limitations of each injection method are described, with simulation studies and experimental validation being used to verify the use of each method in estimating impedance accurately.
In partnership with the project sponsor, a commercial drive was used for practical testing of developed methods: the Siemens G120C. The practical limitations of applying an estimation scheme to a commercial drive were demonstrated, and both simulation studies and experimental validation were used to verify the accuracy of estimates found via use of signal injection into the commercial drive.
To verify that an impedance estimation method may be used with aged capacitors, an accelerated ageing process was devised for producing batches of aged capacitors, where electrolytic capacitors used in the DC-link had their impedances measured using laboratory impedance measurement units and then had their impedances estimated using in-situ measurements of voltage and currents. Taking a measurement of impedance as well as estimating impedance allowed for estimation accuracy to be compared as test conditions varied.
Item Type
ethesis
Thesis Type
PhD
Supervisors
Subjects (LC)
Associated Schools / Departments
Faculty of Engineering
eprints ID
69277
UoN Repository URI
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RAQIB_ABDURRHAMAN_PHD_THESIS_2022-05-31.pdf
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Format
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