Abstract

In parallel with the increased production of electric vehicles, the research on electric motors has become very popular. Switched Reluctance Machines (SRMs) have been widely preferred in these investigations. Mutually Coupled Switched Reluctance Machine (MCSRM) has higher torque performances than conventional SRMs have. In this study, it is aimed to reduce the weight of MCSRM by geometric arrangement. For this purpose, the MCSRM’s stator yoke is minimized without deteriorating the flux distribution. Various geometrical changes are performed on the stator yoke of the MCSRM. Each of the obtained motor models is magnetostatic analyzed in different currents by finite-element analysis. From comparison of the results of the analysis, it is seen that the proposed MCSRM models show reduction in the stator volumes between 11.31% and 14.17%. This reduction leads to a reduction in the overall weight of the MCSRM.

Highlights

  • THE STUDIES OF advanced traction motors generally focus on efficiency, high power density, higher torque, lower noise, and cost [1]

  • An approach is proposed for reducing the weight of Mutually Coupled Switched Reluctance Machine (MCSRM) without loss of performance

  • Some modifications have been made to the geometry of the basic model of designed MCSRM

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Summary

INTRODUCTION

Many studies have been devoted to different rotor or stator configurations with specific properties to improve the performance of SRMs [19,20]. In conventional SRMs, the windings are located on opposite poles of the stator. They are connected as series to form a phase of the machine. In SRMs, as the air gap between the stator and rotor pole heads increases, the reluctance of the magnetic circuit grows. MCSRMs could have 25% more output torque than conventional SRM could have [25] These machines can be used in a variety of applications, using conventional 6 switch inverter or the asymmetric half-bridge converter [26].

STRUCTURE OF MCSRM
DESIGN OF MCSRM
SUBMISSION RESULTS AND DISCUSSIONS
PROPOSED MCSRM STATOR YOKE MODELS
CONCLUSION
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