Model Prediction Based Instantaneous Torque Control of Switched Reluctance Motor

Switched reluctance (SR) motors have many advantages such as simple and solid construction, low-cost on manufacturing, excellent reliability at high temperatures, and large torque density. However, the higher torque ripple from magnetic saliency is a serious problem preventing its applications from being expanded. Several torque control methods have been already proposed. In practical use, a controller must decide gate signals considering some limitations such as inductance, control period, and so on. However SR motor is often operated in magnetic saturation region. So, it is too difficult to consider the limitations. Then, we notice at flux can be easily estimated by integrating the phase voltage. In the paper, a new torque control method based on model prediction to reduce torque ripple is proposed. The proposed method is confirmed through simulations. Then our new method can reduce torque ripple in wide speed range and provides high efficiency drive.