An analytical approach for determination of optimal stator/rotor saliency number of a swıtched reluctance motor

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2020
Kılınç, Cem Erkan
The purpose of this study is to seek the optimal stator and rotor saliency number of a switched reluctance motor (SRM) for hybrid electrical vehicle (HEV) applications. For this purpose, first a previously developed SRM analysis software is investigated to identify possible errors in implementation of both the theory and the coding. Performance prediction method is based on the use of normalized force and permeance data produced via numerical field solution, and a polynomial based interpolation is introduced in the software. This approach is shown to produce accurate results through the comparison of predicted and measured results for the torque-position-current and flux linkage-current-position characteristics. A detailed user interface has been developed for simulations. Once the study on the software is completed, its performance prediction (such as static torque-position, flux linkage-current, average torque, etc.) accuracy is tested through the comparison of the simulation results and measurements of two different SRMs, which are found to be in good agreement. Finally, this software is embedded in an optimization procedure based on genetic algorithm to seek the optimal stator (Ns) and rotor (Nr) saliency numbers. The objective function of the optimization is defined as the maximum average torque attainable within specified dimensions. Optimization is done for different allowable pole combinations. Obtained results indicate that increasing Ns/Nr ratio above 18/12 does not yield any torque density improvement for the specified problem. It is also found that about 10 percent improvement in torque density is possible over the motor currently used in this HEV application.

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Citation Formats
C. E. Kılınç, “An analytical approach for determination of optimal stator/rotor saliency number of a swıtched reluctance motor,” Thesis (M.S.) -- Graduate School of Natural and Applied Sciences. Electrical and Electronics Engineering., Middle East Technical University, 2020.