An Improved Torque Sharing Function for Torque Ripple Reduction in Switched Reluctance Machines

An offline torque sharing function (TSF) is introduced in this paper for torque ripple reduction in switched reluctance machines (SRM). This TSF uses static flux linkage characteristics of the machine obtained from finite element analysis or experiments that describe the machine dynamics to determine optimal current profiles such that the torque ripple reduction is achieved with minimal copper losses. Due to this feature, the proposed TSF performs well across a wide speed range. Additionally, the objective function of the proposed TSF uses only one weight parameter, which facilitates the use of this TSF. In this paper, an intuitive justification for the selection of this weight parameter is given, and the performance of this TSF is validated in simulation and experimentally on a 5.2 kW, four phase SRM. To baseline its performance, the proposed TSF has been compared to the offline TSF in the literature, which shows that it has better current tracking performance at higher speeds due to the inclusion of flux linkage characteristics. Finally, it has been compared to conduction angle control at speeds above the base speed to show that it can be a viable alternative for the control of SRM even in an operation region normally not considered for TSF.