Flux linkage optimization for direct torque control of switched reluctance motor based on model predictive control

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Abstract

In this paper, to solve the problem of large torque ripple in a switched reluctance motor (SRM), a new control strategy based on model predictive flux control is proposed in the direct torque control (DTC) algorithm. First, the flux linkage value in the next period is calculated from the discrete time model of the SRM. Second, to reduce the computation burden and increase the dynamic response, a torque hysteresis controller is embedded in the system to select three candidate voltage vectors for the cost function. Finally, based on flux linkage minimization, the best voltage vector is selected and applied to the system. The proposed direct torque and predictive flux control (DTPFC) method perfectly suits the nonlinear magnetic characteristics of SRM, and shows better steady‐state and dynamic‐state performances compared to DTC. Furthermore, since DTPFC has only one variable in the cost function, the huge task of obtaining the best weighting factor is eliminated. Simulation and experiments are carried out on a three‐phase 12/8 SRM with the proposed control algorithm and DTC. The results demonstrate the validity of the new control approach. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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