The fundamental operation of the switched reluctance motor (SRM) is arguably the simplest and most eloquent of all the universe of rotary electromagnetic machines. Contrast the elementary operation and construction, with the highly non-linear effects that the material properties and geometrical construction of the core add to the design process.
A consequence of these complexities, the efficient performance of an SRM requires an insight intensive, multivariable and highly iterative design process. For completeness, a literature survey is offered which presents a detailed review of three key papers that were instrumental in furthering the understanding of concepts, as related to; the fundamental operation, modeling and prediction methods and objective based design for the switched reluctance motor. In addition, two complete sections are reserved to review the fundamental concepts of the magnetic theory and the principles of SRM operation and design. From this review of theory and the available literature, it is clear that in order to reduce the complexity of the multivariable optimization problems associated with the complex SRM design, a method is required that can identify the significant variables in order
to remove the non-significant variables from the objective functioni this is commonly referred to parameter screening. This screening process can be facilitated by using factorial design, which is a powerful tool that can be used to test several variables simultaneously in order to determine their significance. The factorial design methodology was applied to a switched reluctance motor, whereby the design parameters were individually screened for their contribution towards the starting torque, aligned/unaligned flux-linkage and the RMS stroke torque. Due to the complexity, sheer number and likely interaction of the critical variables associated with SRM design, a method is described wherein the interaction and criticality of the interactions are sorted through an iterative process; whereby, the least important variables and interactions are weeded out so that the more critical variables and interactions can be studied and rated as to their importance to the outcome of the design
process. important variables and interactions are weeded out so that the more critical variables and interactions can be studied and rated as to their importance to the outcome of the design process.