Published November 14, 2023
| Version v1
Publication
Model Predictive Control based on Dynamic Voltage Vectors for Six-phase Induction Machines
Description
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, the 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 work 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 article
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.
Abstract
Ministerio de Ciencia, Innovación y Universidades RTI2018-096151-B-100.Additional details
Identifiers
- URL
- https://idus.us.es/handle//11441/150640
- URN
- urn:oai:idus.us.es:11441/150640