Model predictive current control of surface-mounted permanent magnet synchronous motor with low torque and current ripple

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Electromagnetic torque and stator flux of a permanent magnet synchronous motor (PMSM) can be controlled indirectly with model predictive current control (MPCC). In MPCC, a predefined cost function is minimised by selecting and applying appropriate voltage vectors to stator terminals. Since MPCC employs machine model to predict stator currents, it requires accurate knowledge of its parameters. Furthermore, MPCC results in high torque and current ripples at normal sampling rates. In this study, torque and current ripples of a surface-mounted PMSM are effectively reduced by incorporating the concept of duty cycle and applying two voltage vectors, instead of one voltage vector as in conventional MPCC, during a control period. A fuzzy logic modulator is designed and utilised to determine the duty cycles of voltage vectors. Furthermore, sensitivity of the proposed control strategy against parameter variations is alleviated by employing a full-order Luenberger observer. Various case studies are carried out on a hardware-in-the-loop setup and performance of the proposed method is compared with conventional and a recently introduced duty cycle-based predictive control. The obtained results verify the superiority of the proposed MPCC and its effectiveness in reducing the PMSM torque and current ripples with accurate and erroneous knowledge of motor parameters.

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IET Power Electronics

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