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Enhanced Finite-Control-Set Model Predictive Flux Control of Permanent Magnet Synchronous Machines With Minimum Torque Ripples

Finite-control-set model predictive control is a promising candidate in torque control of permanent magnet synchronous machines due to its straightforward control structure and multiobjective optimization. In order to suppress torque ripples, the zero- or the nonzero-voltage vector is inserted within one sampling period. However, the total control period of two voltage vectors is restricted to the constant sampling period, which restricts the further improvement of reference tracking performance. To solve this problem, an enhanced two-vector-based model predictive flux control of permanent magnet synchronous machines is developed. In this method, the total control period of the active voltage vector and the zero-voltage vector is no more restricted. The control periods of both voltage vectors are flexibly modulated on the basis of the cost function minimization. Minimum torque ripples can be obtained without increasing switching losses. The simulation and experimental results verify that the proposed control strategy achieves enhanced steady-state performances while maintaining fast dynamic responses.