Control of Torque Ripple and Rotor Position for SRM (8/6- 4 Phases) Using an Optimization Based Model Predictive Torque Control (MPTC)

Abstract

Switched Reluctance Motor (SRM) is used in most of Electric vehicles and wind energy system. But it has some disadvantages are high torque ripple because of its power supply mode and multiphase communication. In this paper Model Predictive Torque Control (MPTC) with Sailfish Optimization (SFO) is reduce the torque ripple of SRM using Torque Sharing Function (TSF).  First, based on flux-linkage characteristic curves acquired from the locked rotor test, an accurate SRM model is created, it predict future operation of SRM drive system. Second, the SFO algorithm is used to optimize TSF parameters for minimize the torque value of SRM. Also developed TSF based MPTC method, which avoids the problem of frequency conversion caused by torque controller. Then Atom Search Optimization (ASO) is used to optimize the position sensor for correct rotor position of the SRM. To verify the MPTC-SFO method is compared with Direct Instantaneous Torque Control (DITC). Both simulation on a four phase 8/6 pole SRM for reduce the torque ripple and select the rotor position. The proposed MPTC-SFO method is higher efficiency than DITC. The obtain result is achieved 19.5 % of torque ripple for the proposed method.