Optimizing the performance of switched reluctance machines by including non-linear multi-phase excitation

Switched reluctance motors (SRMs) offer various attractive features such as, simple and robust construction, simple stator windings, and reliable operation. This makes it low cost and rugged for industrial applications. SRMs are operated in saturation, for effective conversion of electrical energy to mechanical energy. In this research work a SRM having good saturation characteristics has been designed. The designed SRM has been characterized by finite element analysis (FEA) and by experimental method.; SRMs have large torque ripple because of their doubly salient structure and principle of operation. A torque ripple optimization scheme based on non-linear search methods and two-phase excitation model of SRM has been presented. The two-phase excitation model of SRM, takes into account the nonlinear effects because of saturation and mutual flux linkages caused by multi-phase excitation. In the proposed scheme the incoming and outgoing phase currents are modulated to minimize the torque ripple. Because of the highly nonlinear nature of torque, fibonacci and exhaustive search methods are used for optimizing the torque ripple. Modulation of phase current is done by addition, subtraction and multiplication of constants and variables. This can be very easily achieved in DSP micro-controllers and FPGAs. The proposed optimization scheme has been experimentally validated.; Self characterization scheme for SRMs are less time consuming than the experimental and FEA characterization. A single-phase self characterization scheme, which characterizes the motor as it is rotating, is presented. The results from self characterization are comparable to that of experimental characterization.; Today's motor drives generally have self commissioning scheme, which auto tunes the control system parameters with that of drive parameters. A self commissioning scheme for SRM drive, based on average model has been presented. Speed controller parameters determination using both single-phase and two-phase average model has been presented. It has been shown that the results obtained from average model are compatible with the hardware results and actual SRM model. The controller parameters obtained using average model can be used for online parameter tuning in SRM drive; this will reduce the self commissioning time considerably.