Low complexity model predictive current control for dual three-phase permanent magnet synchronous motor with extended control set and duty cycle modulation

The model predictive current control (MPCC) method is considered to be one of the most effective methods to solve the dual three-phase permanent magnet synchronous motor driving problem. However, the existing traditional MPCC method is limited. In some cases, inaccuracies in the selected optimal voltage vector (V_opt) can lead to additional current ripple and unsatisfactory steady-state performance, and the MPCC method needs to carry out the traversal optimization process, which increases the computational burden. To solve the above problem, this paper proposes an MPCC method based on an extended finite control set and duty cycle modulation. Firstly, 12 virtual voltage vectors (V³s) with new directions are synthesized, and an extended control set containing 24 V³s is constructed to effectively reduce harmonic current and torque ripple. Then, the dead-beat current control is used to calculate the sector of the reference voltage vector (V_ref), and the V_opt is selected by judging the position of the sector, which reduces the calculation burden. More importantly, the technique of duty cycle modulation is put forward to calculate the residence time of the V_opt, aiming to amend the V_opt magnitude, which can improve the control accuracy. For ease of understanding and software implementation on Digital Signal Processors, triangular carriers are used to generate asymmetric switching sequences. Finally, the experimental results show that the proposed method has better current quality and lower torque ripple than the two existing methods, and the calculation burden is reduced.