Abstract
The need for high performance and high control accuracy in electric motors has made modern motor control techniques popular. Modern control techniques require position sensors integrated in the electric motor. An alternative method to sensor feedback systems is the cost-effective prediction methods that offer solutions within acceptable limits. In this study, a new observer model is proposed for induction machines. In the design of the observer, Unscented Kalman Filter is used. In the Unscented Kalman Filter design, the rotor position information is defined as a state variable within the mathematical model. Therefor the observer model has been developed without the need for additional sensor costs. As an observer model output, machine internal parameters such as rotor fluxes which cannot be measured directly and rotor speed can be estimated without requiring a sensor by using this method.
Original language | English |
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Title of host publication | Proceedings - 2020 6th International Conference on Electric Power and Energy Conversion Systems, EPECS 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 146-150 |
Number of pages | 5 |
ISBN (Electronic) | 9781728175461 |
DOIs | |
Publication status | Published - 5 Oct 2020 |
Externally published | Yes |
Event | 6th International Conference on Electric Power and Energy Conversion Systems, EPECS 2020 - Virtual, Istanbul, Turkey Duration: 5 Oct 2020 → 6 Oct 2020 |
Publication series
Name | Proceedings - 2020 6th International Conference on Electric Power and Energy Conversion Systems, EPECS 2020 |
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Conference
Conference | 6th International Conference on Electric Power and Energy Conversion Systems, EPECS 2020 |
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Country/Territory | Turkey |
City | Virtual, Istanbul |
Period | 5/10/20 → 6/10/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Keywords
- Induction machine control
- observer model
- sensor
- unscented kalman filter