Virtual auto-tuning position and torque sensors for switched reluctance motor drives

High performance electric motor drives are inherently dependent to the measurement devices, or sensors, operating properly. In particular, switched reluctance motor drives need position and torque sensors to demonstrate full torque control capability. This requirement yields to more expensive and complex drive system. On the other hand, when these sensors fail, the control system should compensate for the failure to function properly. This necessitates back up systems to support the operational drive in case of sensor failure especially for life dependent applications like automotive systems. In this paper, novel virtual position and torque sensors are designed based on modeling of magnetic double saliency characteristics in the switched reluctance motor drives. A practical auto-tuning method is designed to calibrate the virtual sensors. The proposed virtual auto-calibrating sensors are fully implemented on our experimental SRM drive based on TMS320LF2407 fixed-point digital signal processor. The experimental results verify the capability and high performance of the proposed approach.