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Optimization of the New Structure of the Reluctance Motor to Increase the Efficiency and Power-Density by Experimental Methods

Mohammadi Fesharaki, Alireza | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53965 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Sayyaadi, Hassan
  7. Abstract:
  8. Permanent magnets play an essential role in the structure of the electric motor, but due to limited resources, many efforts have been made to meet the need for them. One of the most important types of non-permanent electric motors is reluctance motors. Despite their antiquity in design, torque ripples have led to the limited use of reluctance motors, but advances in science have made it possible to control these ripples.As a result of the major advantages such as low manufacturing costs, high efficiency, and uncomplicated structure, these motors have been the subject of many researches. One way to eliminate the problem of torque ripples is to increase the number of teeth, but in the common structures of these motors, it is not possible, due to interference with the winding space. The new structure used in this study has made it possible to increase the number of teeth. In the previous study, due to the new structure, the engine power formula was recalculated.The new structure has been simulated in 3D finite element software and has been validated by making a sample to further ensure the results. In this project, an attempt has been made to optimize the existing structure by changing the geometric parameters to reduce torque ripples and increase the power density of the motor. To do this, due to the variety of parameters, experiments were first conducted to find their importance and their degree of impact. Then the main experiments were performed on the identified parameters and with the help of the results, the optimal value of the parameters was provided
  9. Keywords:
  10. Geometry Optimization ; Torque Ripple ; Reluctance Motors ; Design of Experiments Method(DOE) ; Genetic Algorithm ; Permanent Magnet

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