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To achieve high efficiency and dynamics in electric drive applications, it is necessary to have accurate torque control. This is typically accomplished through a current regulator that is fed by references generated by various open-loop control strategies, in order to obtain the desired torque. As an alternative, this work presents a model predictive torque control. Starting from the torque reference, the algorithm generates optimal voltage references to the inverter-fed synchronous motor drive while working at maximum efficiency and considering the motor current limit. This feature is achieved by combining two different norms in the cost function. The electromagnetic torque is estimated from the measured currents and an accurate magnetic model of the motor. According to the paradigm of the more autonomous drives, an important feature is that the algorithm requires only knowledge of the motor model. This means that a tuning procedure for control weight is no longer required as analytically discussed in this work. Experimental validation of the proposed technique is performed on a test rig featuring an anisotropic permanent magnet motor in different dynamic operation, including flipping from the motor nominal working point to the generator one.

Continuous Control Set Model Predictive Torque Control With Minimum Current Magnitude Criterion for Synchronous Motor Drives