Steady-state detection techniques: AC-drive-controlled motor systems
Kaipainen, Joonas (2020)
Kaipainen, Joonas
2020
Tieto- ja sähkötekniikan kandidaattiohjelma - Degree Programme in Computing and Electrical Engineering, BSc (Tech)
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Hyväksymispäivämäärä
2020-05-08
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202004304829
https://urn.fi/URN:NBN:fi:tuni-202004304829
Tiivistelmä
Modern AC-drives contain algorithms to optimize and improve the operation of electric motors. Some of these optimization algorithms are performed at steady-state operation of the AC-drive, and therefore, steady-state detection techniques are required. The steady-state operation can be determined from the measured values of the motor. For the motor to operate under steady-state, the output of the motor should be approximately constant. Due to electric motors behavior and the system conditions, determining the steady-state can be challenging.
This thesis examines the benefits of the steady-state detection. The challenges and difficulties of the steady-state detection will also be analyzed. To understand the methods, this thesis will review the basics of AC-drive-controlled motor systems.
In the beginning of this thesis, induction motor and its operating principles will be reviewed to understand the need for optimization algorithms. Then the thesis will examine AC-drives and the control of an induction motor. After that, the thesis will review and analyze different optimization algorithms which can be used to improve the control of an induction motor. These algorithms are identification run, flux optimization and condition monitoring.
The last part of this thesis will focus on steady-state detection. Definitions and basics will be introduced, and the difficulties of steady-state detection will be reviewed. Basic techniques for steady-state detection will be reviewed. These basic techniques are linear regression, t-test and f-test. The final chapter discusses steady-state detection in AC-drive systems.
In conclusion, steady-state detection is a difficult task due to its demands in computing power and need for user input. In AC-drive systems, same software is used in different application, causing different problems in steady-state detection. The benefits of using optimization algorithms can be found hugely beneficial for economic and technical standpoint.
This thesis examines the benefits of the steady-state detection. The challenges and difficulties of the steady-state detection will also be analyzed. To understand the methods, this thesis will review the basics of AC-drive-controlled motor systems.
In the beginning of this thesis, induction motor and its operating principles will be reviewed to understand the need for optimization algorithms. Then the thesis will examine AC-drives and the control of an induction motor. After that, the thesis will review and analyze different optimization algorithms which can be used to improve the control of an induction motor. These algorithms are identification run, flux optimization and condition monitoring.
The last part of this thesis will focus on steady-state detection. Definitions and basics will be introduced, and the difficulties of steady-state detection will be reviewed. Basic techniques for steady-state detection will be reviewed. These basic techniques are linear regression, t-test and f-test. The final chapter discusses steady-state detection in AC-drive systems.
In conclusion, steady-state detection is a difficult task due to its demands in computing power and need for user input. In AC-drive systems, same software is used in different application, causing different problems in steady-state detection. The benefits of using optimization algorithms can be found hugely beneficial for economic and technical standpoint.
Kokoelmat
- Kandidaatintutkielmat [8344]