Abstract
The design of switched reluctance motor (SRM) is considered a complex problem to be solved using conventional design techniques. This is due to the large number of design parameters that should be considered during the design process. Therefore, optimization techniques are necessary to obtain an optimal design of SRM. This paper presents an optimal design methodology for SRM using the non-dominated sorting genetic algorithm (NSGA-II) optimization technique. Several dimensions of SRM are considered in the proposed design procedure including stator diameter, bore diameter, axial length, pole arcs and pole lengths, back iron length, shaft diameter as well as the air gap length. The multi-objective design scheme includes three objective functions to be achieved, that is, maximum average torque, maximum efficiency and minimum iron weight of the machine. Meanwhile, finite element analysis (FEA) is used during the optimization process to calculate the values of the objective functions. In this paper, two designs for SRMs with 8/6 and 6/4 configurations are presented. Simulation results show that the obtained SRM design parameters allow better average torque and efficiency with lower iron weight. Eventually, the integration of NSGA-II and FEA provides an effective approach to obtain the optimal design of SRM.
Highlights
The switched reluctance motor (SRM) is the type of motor that has saliency in both stator and rotor without permanent magnets or windings on rotor [1]
As we intended to maximize both average torque and efficiency and minimize iron weight, it is obvious that the crowded area in Figure 4a, for example, exists in the upper right quarter
This paper introduces a method of SRM design optimization by genetic algorithm
Summary
The switched reluctance motor (SRM) is the type of motor that has saliency in both stator and rotor without permanent magnets or windings on rotor [1]. SRM develops electromagnetic torque based on variation of reluctance values for rotor position change with respect to phases when they are switched on. SRM provides several merits compared to other types of electric machines [2]. The previous merits have increased the research efforts recently and made SRM preferred for high speed applications [1,6]. The torque ripple of SRM is the major problem that results in a high noise and variation. The latter can be improved by both control and design [7]. The control of this machine plays an essential role in the operation and it is required to overcome its challenges, which differ depending on the application [8,9,10]
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