A diverse group of so-called multi-vector techniques has recently appeared to enhance the control performance of multiphase drives when a direct control strategy is implemented. With different numbers of switching states and approaches for estimating the application times, each multi-vector solution has its own nature and merits. Previous studies have individually tested each version of the proposed finite-control-set model predictive control (FCS-MPC) strategies using a single experimental setup with specific parameters and, in some cases, using a limited range of operating conditions and focusing exclusively on some control aspects. Although such works provide partial contributions, the control performance is highly affected by the test and rig conditions, being dependent on the machine parameters, the switching frequency and the range of operation. Consequently, it becomes difficult to extract some universal conclusions that guide the control designer on the best alternative for each application. Aiming to enrich the knowledge in this field and provide a broader picture, this work performs a global analysis with different multi-vector techniques, various machine parameters, multiple operating points and a complete set of indices. Experimental results confirm that the selection of the most adequate control strategy is not a trivial task because the degree to which multi-vector techniques are affected by the test conditions is variable and complex. Some tables with a qualitative analysis, based on the extensive empirical tests, contribute with a more complete insight and guide eventual control designers on the decision about the optimal regulation approach to be chosen.

Model predictive control (MPC) is an interesting regulation solution in the field of multiphase electric drives. Its performance has been improved from different perspectives, but most works implement a single-step horizon approach. The complexity of using long-prediction horizons along with the higher complexity of multiphase systems has hindered the real-time implementation of multistep strategies. In fact, the only attempt of designing a multistep solution for multiphase drives uses a smart selection of the voltage vector, reducing the computational burden. Unfortunately, this strategy completely disregards the voltage output selected as the better candidate in the second step (i.e., in $\boldsymbol{k+3}$ ), hence missing valuable information that can be inherited from one sampling period to the next one. This work suggests informing the MPC by creating a so-called hall of fame that stores the switching state determined as a suitable candidate in the previous sampling time. Such vector is promoted in the iterative process by adding a term in the cost function that is activated when the switching state under evaluation is within the hall of fame. Experimental results in a six-phase drive confirm the capability of the proposed scheme to simultaneously improve the current tracking and reduce the switching frequency.

Both industry and academia have recently highlighted the need to provide students with 21st-century abilities that involve soft skills and flexible technical competencies. To this end, active learning (AL) helps scholars to be more autonomous, proactive, self-regulated, sociable and creative. A full AL implementation typically requires costly resources and institutional support. However, it is possible to maintain a traditional teaching structure and include low-cost AL activities that enhance the students’ performance and satisfaction. This proposal suggests a methodology where lectures become more dynamic, the practical teaching is student-centered, the lab teaching is fully open, and the learner’s progress is gamified. A full subject design is presented in a comprehensive manner aiming for satisfying courses with a heterogeneous students’ profile. All activities are carefully selected with a social constructivist approach in order to promote critical thinking, social interaction and students’ engagement. The assessment of the course design implementation is performed considering multiple aspects, such as satisfaction, performance, social relationships and self-regulation. Results confirm the adequacy of the proposal to develop technical skills, excite non-technical competences and motivate scholars with an inclusive approach.

Thanks to the researchand development efforts, multiphase electric drives can be considered a reality for industrial applications, especially when high-performance requirements are mandatory. However, there are still various issues to address in order to fully exploit all the multiphase advantages. For example, the usage of high sampling frequencies can modify the control action effect and, consequently, the selection criterion of direct regulation schemes can become questionable. Focusing on this fact, this work proposes a data analysis to identify undesirable switching patterns of model predictive control (MPC) when the control period is reduced. Based on the conclusions drawn from the mentioned analysis, a new cost function is designed to avoid the application of these suboptimal voltage sequences. This control solution simultaneously enhances signal quality and reduces switching losses. A series of experimental results using different six-phase machines has been obtained to confirm the effectiveness of the proposed control scheme.

Finite Control-Set Model Predictive Control (FCS-MPC) appears as an interesting alternative to regulate multiphase electric drives, thanks to inherent advantages such as its capability to include new restrictions and fast-transient response. Nevertheless, in industrial applications, FCS-MPC is typically discarded to control multiphase motors because the absence of a modulation stage produces a high harmonic content. In this regard, multi-vectorial approaches are an innovative solution to improve the electric drive performance taking advantage of the implicit modulator flexibility of Model Predictive Control (MPC) strategies. This work proposes the definition of a new multi-vectorial set of control actions formed by a couple of adjacent large voltage vectors and a null voltage vector with an adaptative application ratio. The combination of two large voltage vectors provides minimum x-y current injection whereas the application of a null voltage vector reduces the active voltage production. Moreover, the optimum selection of the null voltage vector for each couple of large voltage vectors permits reducing the switching frequency. On the other hand, the active application time for this couple is estimated through an analytic function based on the operating point. This procedure avoids the use of an iterative process to define the duty cycles, hence significatively decreasing the computational burden.

Multiphase electric drives (EDs) offer important advantages for high-demand applications. However, they require appropriate high-performance control strategies. In this context, finite-control-set model predictive control (FCS-MPC) emerges as a promising strategy, offering a notable flexibility to implement multiobjective regulation schemes. When applied to multiphase EDs, standard FCS-MPC exhibits degraded current quality at low and medium control frequencies. Multivector solutions address this issue by properly combining multiple voltage vectors within a single control period to create the so-called virtual voltage vectors (VVVs). In this way, this approach achieves flux and torque regulation while minimizing current injection into the secondary subspace. For this purpose, the VVV synthesis typically prioritizes active vectors with low contribution in secondary subspaces, avoiding the average deception phenomenon. VVV solutions commonly enable an open-loop regulation of secondary currents. Nevertheless, the absence of closed-loop control in the secondary subspace hinders the compensation of nonlinearities, machine asymmetries, and unbalanced conditions in the ED. Considering this scenario, this work implements a multivector FCS-MPC recovering closed-loop control for the secondary subspace. The capability of the proposal to mitigate secondary current injection and compensate for possible dissymmetries is experimentally evaluated in a six-phase ED. Its performance is compared against a benchmark technique in which secondary current regulation is handled in open-loop mode. The proposed control solution significantly improves in current quality, achieving a reduction in harmonic distortion of 54% at medium speed.