|dc.description.abstract||in recent years, the Standstill Frequency Response (SSFR) test has been accepted as a powerful tool for the determination of synchronous machine parameters. However, the existing techniques of the SSFR test still have a number of shortcomings which affect the accuracy of the test. This thesis is devoted to examine some of these shortcomings and to develop ways to
enhance the accuracy of this test. Both simulations and experiments have been employed in carrying out this research.
This thesis has investigated the concept of the SSFR test and proposed to involve three d-axis transfer functions in it instead of the commonly used two functions. This involvement can improve the accuracy of the SSFR test. Since the accuracy of the determined machine parameters depends greatly on the accuracy of the transfer function measurement, this thesis has also investigated intensively the various sources of errors in conducting the SSFR test, and the means to eliminate or reduce such errors. Since the accuracy of the determined parameters depends also on the model fitting process, an effective nonlinear model fitting technique, namely the Marquardt algorithm, has been adapted successfully for the synchronous machine parameter estimation.
To verify the developed techniques, an SSFR test has been carried out on a microalternator to determine its parameters. A VAX 11/780 computer and an LP All-K system have been utilized to implement the A/D conversion for the signals with a wide range of frequencies, and to perform
the data processing. The conducted SSFR test has been designed to suit the conditions of various magnetic flux levels in synchronous machines. This thesis describes in detail the developed techniques and the conducted SSFR testing. Test results are also presented and discussed.||en_US