Performance Comparison of Enhanced Model Predictive Control and Model Predictive Direct Torque Control in SRM Drives

The magnet-less Switched Reluctance Motor (SRM) speed-torque characteristics are ideally suited for traction motor drive characteristics and its advantage to minimize the overall cost of on-road EVs. The main drawbacks are torque and flux ripple, which have produced high in low-speed operation. However, the existing Direct Torque Control (DTC) flux and torque estimation selected large voltage vectors (VVs) give high torque ripples due to sector partition. On the other hand, the Model Predictive Direct Torque Control (MPDTC) including current estimation with weighting factors produces high torque ripples due to the system dynamics and constraints. Therefore, existing DTC and MPDTC can result in high torque ripples. This paper proposed a Model Predictive Control (MPC) with a single cost function objective with a weighting factor: the predicted torque and current considered to evaluate VVs to converter signals. This selects optimal VVs to minimise the SRM drive torque and flux ripples in steady-state behaviour. The classical DTC, MPDTC and proposed model were developed, and simulation results were verified using MATLAB/Simulink. The proposed model operated in 8/6 SRM drives experimental set-up and results to prove the effective minimisation of torque and flux ripples.