Abstract
A problem of the switched reluctance drive is its natural torque pulsations, which are partially solved with finite control set model predictive control strategies. However, the continuous control set model predictive control, required for precise torque stabilization and predictable power converter behavior, needs sufficient computation resources, thus limiting its practical implementation. The proposed model predictive control strategy utilizes offline processing of the magnetization surface of the switched reluctance motor. This helps to obtain precalculated current references for each torque command and rotor angular position in the offline mode. In online mode, the model predictive control strategy implements the current commands using the magnetization surface for fast evaluation of the required voltage command for the power converter. The proposed strategy needs only two lookup table operations requiring very small computation time, making instant execution of the whole control system possible and thereby minimizing the control delay. The proposed solution was examined using a simulation model, which showed precise and rapid torque stabilization below rated speed.
Highlights
Switched reluctance drives (SRDs) have attracted a significant amount of attention in recent decades as the most promising type of electric drive
It can only produce a positive current in any phase, which should be taken into account in the model when zero or negative voltage is applied to the winding
The problem of precise torque control in switched reluctance motor drives was partially solved by means of finite control set model predictive control, the drive still suffers from an unpredictable switching rate and acoustic noise
Summary
Switched reluctance drives (SRDs) have attracted a significant amount of attention in recent decades as the most promising type of electric drive. Suggested improved in [10] by decreasing the losses in the motor and in [11] by achieving equal distribution of in [9] to help decrease torque ripple and make the control strategy applicable for any motor It was the temperatures of the power converter’s IGBT-modules. These approaches utilize the improved in [10] by decreasing the losses in the motor and in [11] by achieving equal distribution of magnetization surface of the switched reluctance motor for torque estimation while selecting the best the temperatures of the power converter’s IGBT-modules These approaches utilize the magnetization control command. These systems stabilize the output torque by profiling the phase current shape, with respect of the finite control set model predictive control is the random switching rate and the error in the to the commanded torque, and minimizing ohmic losses.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
