Title
Double Dead-Time Signal Injection Strategy for Stator Resistance Estimation of Induction MachinesAuthor (from another institution)
xmlui.dri2xhtml.METS-1.0.item-contributorOtherinstitution
Cegasa Energia S.L.U.Version
http://purl.org/coar/version/c_970fb48d4fbd8a85
Rights
© 2022 The AuthorsAccess
http://purl.org/coar/access_right/c_abf2Publisher’s version
https://doi.org/10.3390/app12178812Published at
Applied Sciences 12(17). 1 September, 2022Publisher
MDPIKeywords
induction motor
signal injection
stator resistance estimation
temperature estimation ... [+]
signal injection
stator resistance estimation
temperature estimation ... [+]
induction motor
signal injection
stator resistance estimation
temperature estimation
thermal protection [-]
signal injection
stator resistance estimation
temperature estimation
thermal protection [-]
Abstract
A sensorless online temperature estimator is presented in this paper, which estimates the temperature using a novel signal injection strategy. This allows to eliminate the temperature sensors in the m ... [+]
A sensorless online temperature estimator is presented in this paper, which estimates the temperature using a novel signal injection strategy. This allows to eliminate the temperature sensors in the machine, as well as their faults, increasing the system reliability. A double dead-time DC signal is injected in the machine, adding a controlled offset in the control drive through the inverter. The proposed strategy eliminates the effect of the dead-time in the injected signal, which is an important drawback in DC injection strategies for resistance estimation. Furthermore, additional hardware is not needed. The strategy has been implemented in an inverter-fed railway traction induction machine. The proposed algorithm has been validated in a real test-bench. [-]
xmlui.dri2xhtml.METS-1.0.item-sponsorship
Gobierno Vasco-Eusko Jaurlaritzaxmlui.dri2xhtml.METS-1.0.item-projectID
info:eu-repo/grantAgreement/GV/Elkartek 2021/KK-2021-00044/CAPV/Vehículo eléctrico basado en Nitruro de Galio/VEGANCollections
- Articles - Engineering [684]
The following license files are associated with this item: