Model Predictive Control Based on Dynamic Voltage Vectors for Six-Phase Induction Machines

Abstract

Model predictive control (MPC) has been recently suggested as an interesting alternative for the regulation of multiphase electric drives because it easily exploits the inherent advantages of multiphase machines. However, standard MPC applies a single switching state during the whole sampling period, inevitably leading to an undesired 𝒙-𝒚 voltage production. Consequently, its performance can be highly degraded when the stator leakage inductance is low. This shortcoming has been however mitigated in recent works with the implementation of virtual/synthetic voltage vectors (VVs) in MPC strategies. Their implementation reduces the phase current harmonic distortion since the average 𝒙-𝒚 voltage production becomes null. Nevertheless, VVs have a static nature because they are generally estimated offline, and this implies that the flux/torque regulation is suboptimal. Moreover, these static VVs also present some limitations from the point of view of the DC-link voltage exploitation. Based on these previous limitations, this work proposes the implementation of dynamic virtual voltage vectors (DVVs), where VVs are created online within the MPC strategy. This new concept provides an online optimization of the output voltage production depending on the operating point, resulting in an enhanced flux/torque regulation and a better use of the DC-link voltage. Experimental results have been employed to assess the goodness of the proposed MPC based on DVVs.

Recent Advances in Model Predictive and Sliding Mode Current Control Techniques of Multiphase Induction Machines

“…Fortunately, the implementation of multivector solutions (Gonzalez-Prieto et al, 2018;Xue et al, 2018;Luo and Liu, 2019;Ayala et al, 2020;Gonzalez-Prieto et al, 2020;Aciego et al, 2021;Ayala et al, 2021b;Gonçalves et al, 2021), such as synthesized or virtual voltage vectors (Gonzalez-Prieto et al, 2018;Garcia-Entrambasaguas et al, 2019;, has permitted the minimization of the aforementioned harmonic injection thanks to the use of control actions formed by several switching states per sampling period. To take advantage of MPC features for multiphase electric drives, a significant number of researchers have promoted the development of more competitive multi-vector alternatives (Gonzalez-Prieto et al, 2018;Xue et al, 2018;Garcia-Entrambasaguas et al, 2019;Luo and Liu, 2019;Gonzalez-Prieto et al, 2020;Aciego et al, 2021;Ayala et al, 2021b;Gonçalves et al, 2021), providing phase current with low harmonic content. As a consequence of the evolution of the multi-vector approach, MPC has been able to be reformulated in electric drive regulation techniques (Tenconi et al, 2018).…”

“…On the other hand, as previously exposed, the asymmetrical six-phase IM is one of the most studied electric drives for multiphase electric drives from this perspective. Considering the asymmetrical sixphase IM as a case study, the multi-vector approaches can be classified attending to their building procedure: offline virtual voltage vectors (Gonzalez-Prieto et al, 2018;Gonçalves et al, 2019c,b) and online multiple vector output (Gonzalez-Prieto et al, 2020;Aciego et al, 2021;Ayala et al, 2021b). Regardless of the assumed technique to generate these high-performance control actions, particular attention must be paid to the voltage vector location in the secondary plane due to the crucial effect of this plane in the harmonic distortion of the phase currents (Gonzalez-Prieto et al, 2018;Abdel-Khalik et al, 2020).…”

“…Fortunately, taking advantage of the flexibility mentioned above of MPC, the control designer can create voltage outputs formed by several switching states. Then the harmonic distortion of standard MPC can be reduced (Gonzalez-Prieto et al, 2018;Xue et al, 2018;Luo and Liu, 2019;Gonzalez-Prieto et al, 2020;Aciego et al, 2021;Ayala et al, 2021b;Gonçalves et al, 2021;Romero et al, 2021). The development of multi-vector strategies for MPC in multiphase electric drives is currently an important topic of research to exploit the inherent advantages of MPC for the regulation of these more competitive systems.…”

Algorithm for Implementation of Optimal Vector Combinations in Model Predictive Current Control of Six-Phase Induction Machines

“…The cost function consists of a configurable weighting factor to prioritize current tracking or loss reduction in the x-y plane. This method has the disadvantage of high tracking error and considerable losses in the x-y plane since it uses a single vector [12][13][14]. This fact produces high harmonic content in the stator currents compared to other approaches that integrate modulation strategies in MPC to face this weakness [15].…”

Multivariable generalised predictive control with measurement noise rejection and speed ripple mitigation for PMSM drives

“…In [2, 3], the voltage reference is calculated in a deadbeat manner, and the FCS‐MPC tracks the voltage reference instead of the original target variables (current, torque, or flux), and thus, the weighting factors can be removed. In [4–7], the concept of the virtual vector is used to improve the steady‐state performance, as well as to obtain fixed (or approximately fixed) switching frequencies.…”