Model Predictive Torque Control for Enhanced SRM With Improving Drive Hardware Performance

Switched Reluctance Motor (SRM) is the choice of next-generation electric vehicle (EVs) traction motor applications, due to their simple rotor structure, power and torque characteristics. However, this SRM drive suffers from high torque ripples, which may cause severe vibration and acoustics. Therefore, torque ripple is effectively reduced by control techniques. This paper proposes an enhanced model predictive torque control (MPTC) that minimizes torque ripple and improves system efficiency. The active voltage vector (VVs) selection is obtained by removing flux linkage, eight sectors in the SRM electric cycle, and minimum VVs at each control period. As a result, a single cost function designed with the weighting factor reduces torque ripple by selecting optimal VVs. The enhanced SRM dynamic motor model and proposed MPTC control are verified through simulation studies and experiments based on a four-phase 8/6 pole SRM drive system.