LAUSR

Relatively high torque ripple limits the further development of the switched reluctance machine, and the application of the ripple suppression method will reduce the efficiency of the system. To simultaneously improve the efficiency and torque ripple of the switched reluctance machine, a new commutation and online optimization strategy is proposed. According to the torque per ampere characteristics of the machine, two rotor position angles are defined, which are the boundaries for the high and low torque per ampere operation modes of the two adjacent phases, respectively, and for different operating modes, specific torque hysteresis control schemes are performed. Furthermore, an objective function is constructed with the efficiency and torque ripple coefficient, and during the operation of the machine, the defined boundary angles are online optimized by the genetic algorithm to maximize the value of the objective function. The effectiveness of the method is verified by detailed simulation and experiment under different operating conditions.