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This paper proposes the computation of three-level optimized pulse patterns (OPPs) with reduced common-mode voltage (CMV) over the whole range of modulation indices. Limiting the CMV, however, gives rise to increased current harmonics. To mitigate this, the OPP optimization problem is reformulated to allow for symmetry relaxations and multipolar switch positions. In doing so, the current harmonics not only remain low, but they are occasionally even lower than those of traditional OPPs. The presented numerical results, based on a medium-voltage (MV) drive consisting of a three-level converter and an induction machine, demonstrate the benefits of the proposed approach. acceptedVersion

This paper presents a control method for three-level neutral point clamped (NPC) inverter medium-voltage (MV) drives that addresses the stator current control problem and balancing of the neutral point (NP) potential in a single control loop. To do so, a model predictive control (MPC) algorithm, designed as a multiple-input multiple-output (MIMO) controller, manipulates optimized pulse patterns (OPPs) in real time. As a result, minimal current harmonic distortions are produced, while the NP potential is kept balanced both during steady state and transients. The presented results demonstrate the effectiveness of the proposed control strategy for three-level NPC inverter MV variable speed drive systems. acceptedVersion

As the number of electric automotive vehicles is rapidly growing, the need for higher efficiency and system-friendly operation of the drive train becomes more relevant and urgent. In this paper, the synchronous modulation schemes of selective harmonic elimination (SHE) and optimized pulse patterns (OPPs) are described and their performance benefits for drives used in automotive industry are highlighted. The presented experimental results based on an industrial drive demonstrate that OPPs achieve superior performance in terms of current distortions, system efficiency, and dc-link current ripple compared with conventional asynchronous space vector modulation (SVM). acceptedVersion

This paper presents a model predictive control (MPC) algorithm for interleaved dc-dc boost converters with coupled inductors. The prediction model covers the switching nature of the converter and all possible operating states. The MPC algorithm is realized in MATLAB and designed such to facilitate its real-time implementation on a field programmable gate array (FPGA) using the MATLAB HDL Coder. Open-loop measurement results demonstrate the accuracy of the system model, while the effectiveness of the controller is validated in simulation. acceptedVersion

Long-horizon direct model predictive control (MPC) has pronounced computational complexity and is susceptible to parameter mismatches. To address these issues, this paper proposes a solution that enhances the robustness of long-horizon direct MPC, while keeping its computational complexity at bay. The former is achieved by means of a suitable prediction model of the drive system that enables the effective estimation of the total leakage inductance of the machine. For the latter, the objective function of the MPC problem is formulated such that, even though the drive behavior is computed over a long prediction interval, only a few changes in the candidate switch positions are considered. The effectiveness of the proposed approach is demonstrated with a medium-voltage (MV) drive consisting of a three-level neutral point clamped (NPC) inverter and an induction machine (IM). acceptedVersion

This paper deals with the implementation of a long-horizon finite control set model predictive control (FCS-MPC) algorithm on an embedded system. The targeted application is a medium voltage drive system implying a very low switching frequency. The implementation is facilitated by the use of a high level synthesis (HLS) tool, which synthesizes C++ code into VHDL, enabling a higher level of abstraction and faster prototype development. Experimental results based on a small-scale prototype, consisting of a three-level neutral point clamped (NPC) inverter and an induction machine, confirm that the algorithm can be executed in real time within the targeted control period of 25μs. This allows for high switching granularity, and thus favorable steady-state and transient performance. acceptedVersion

In this paper we present a branch-and-bound algorithm that facilitates the real-time implementation of long-horizon finite control set model predictive control (FCS-MPC) for high-power electronic systems. To achieve this, the optimization process is modified such that the more likely candidates (i.e., the switching sequences with less switching transitions) are explored first. By doing so, computational demanding operations can be efficiently pipelined in a field-programmable gate array (FPGA), rendering the proposed method computationally feasible. The effectiveness of the introduced method is tested both in an FPGA-in-the-loop simulation and with a real-world setup based on a scaled-down low-voltage variable speed drive system consisting of a three-level neutral point clamped inverter and an induction machine. As shown, a real-time implementation with horizon length of twelve is achieved without sacrificing optimality. acceptedVersion

This paper presents a finite control set model predictive control (FCS-MPC) method that improves the performance of a synchronous reluctance machine drive. As shown, when a high sampling-to-switching frequency ratio is used with FCS-MPC, the stator current distortions can be significantly reduced, allowing for less losses in the machine. Moreover, the FCS-MPC steady-state performance is enhanced by introducing an integrating element into the cost function to ensure accurate output reference tracking. Finally, the adopted drive model that relies on an identified accurate magnetic model of the machine further improves the robustness of the discussed control scheme. The presented simulation and preliminary experimental results verify the effectiveness of the discussed method. acceptedVersion

Finite control set model predictive control (FCS-MPC) is a promising method for the control of multi-phase machines, due to its capability to directly account for nonlinearities and multiple controlled variables. To overcome the drawback of high current ripples and excitation of harmonic currents in the so-called xy-subsystem, several methods have been proposed in the literature so far. This paper proposes an MPC-based method that achieves high granularity of switching by not only switching at the discrete time steps, but also within the sampling interval. In doing so, the discussed algorithm, referred to as variable switching point current control (VSP2CC), produces low current distortions, while still keeping the advantages of conventional FCS-MPC, such as fast dynamic behavior during transients. To highlight the above, VSP2CC is applied to a six-phase permanent magnet synchronous machine (PMSM) and compared with conventional FCS-MPC and MPC that employs virtual voltage vectors (VV-MPC). acceptedVersion

In this paper we present a direct model predictive control (MPC) scheme with time-varying sampling intervals. These sampling intervals are computed based on modulation (half-)cycles, which are obtained offline and stored in a look-up table. By utilizing the optimized modulation (half-)cycles and combining control and modulation in one computational stage, the proposed direct MPC scheme achieves lower current total harmonic distortion (THD) than conventional linear controllers with a dedicated modulator, and fast transient responses that characterize direct control methods. The effectiveness of the proposed control scheme is verified on a variable speed drive system consisting of a two-level voltage source inverter and an induction machine. acceptedVersion

This paper presents a control scheme that combines the optimal steady-state performance of optimized pulse patterns (OPPs) with the fast dynamics of direct model predictive control (MPC). Due to inherent challenges that relate to the utilization of OPPs in a closed-loop setting, OPPs are traditionally used in slow control loops. As a result, the associated dynamic performance of the drive system is considerably poor. To overcome this, in this work, a direct MPC algorithm is employed to manipulate the OPPs in a fast, yet optimal, manner. Specifically, the MPC algorithm takes advantage of the knowledge of the stator current evolution—as described by its gradient—within the prediction horizon. Subsequently, a constrained optimization problem with a receding horizon is solved to compute the optimal modification of the offline-computed OPP such that superior steady-state and dynamic performance is achieved. The effectiveness of the proposed method is verified based on a variable speed drive system, which consists of a two-level inverter and a low-voltage induction machine. acceptedVersion

Model predictive control (MPC) requires an accurate system model to achieve favorable performance. Thus, in presence of disturbances, model uncertainties and mismatches, MPC needs tools that provide high degree of robustness to them. Since MPC is, essentially, a proportional control technique, an effective method to deal with the aforementioned issues is the addition of an integrating element to the control scheme. This paper presents a prediction model that introduces an integrator tothe control strategy without increasing the size of the optimization problem. To examine its effectiveness, the sensitivity of the classical and the proposed MPC to parameter deviations are discussed and analyzed, considering a wide range of switching frequencies as well as prediction horizon lengths. The robustness examination is performed based on an industrial case study, namely a medium voltage induction motor drive. acceptedVersion

Model predictive control (MPC) lacks an integrating element. Thus, parameter mismatches can deteriorate its steady-state performance. To address this issue and enhance the robustness of MPC, analternative formulation of the prediction model is discussed in this paper. This model introduces an integrator to the optimization problem without increasing its size and consequently its computational complexity. An in-depth analysis of the effect of parameter mismatches on the control performance is performed when both the conventional and the proposed prediction model are used. Specifically, the aforementioned analysis is carried out for a range of switching frequencies as well as prediction horizon lengths, while a permanent magnet synchronous motor (PMSM) drive is used as a case study. acceptedVersion

In this paper, a flux linkage-based direct model predictive current control approach is presented for small permanent magnet synchronous motor (PMSM) drives. The method aims to minimize the current ripples at steady state by deciding on the optimal switching instant, while exhibiting fast dynamic behavior during transients. To this end, the future trajectory of the stator current is not computed based on the machine inductances or inductance look-up tables, but on the changes of the magnetic flux linkage by utilizing flux linkage maps. As shown, the proposed method can be particularly advantageous for electric drives with a noticeable nonlinearity in terms of saturation and/or cross-coupling effects since it allows for a significantly increased prediction accuracy, which leads to an improved steady-state performance as indicated by the reduced current distortions. acceptedVersion

The Siwakoti-H flying-capacitor inverter (sFCI) is a recent member of the family of transformerless inverters. Due to its minimal design, it presents a favorable alternative to conventional transformerless topologies. One of the major challenges in the control of the sFCI is to maintain the flying capacitor voltage within prescribed limits. To address this issue, a direct model predictive control (MPC) scheme is proposed for a single phase grid-connected sFCI. A discrete-time switched nonlinear model of the converter is derived, which captures the dynamics of the flying capacitor and the LCL filter. The nonlinear model enables the accurate prediction of the system behavior over the whole operating range. The proposed MPC strategy is tasked to work in two different modes, i.e., grid-disconnected mode and grid-connected mode, with specific control objectives. The presented results demonstrate the flying capacitor voltage control in grid-disconnected mode, and also illustrate the steady-state and dynamic performance of the controller in grid-connected mode. acceptedVersion

In this paper we present a modified sphere decoder that can adjust the switching frequency in real time. To achieve this, the underlying integer least-squares (ILS) problem is reformulated and the lattice generator matrix is modified. By doing so, computational demanding operations required to be performed in real time are avoided altogether, rendering the proposed method computationally feasible. Moreover, the optimization process is kept computationally modest by appropriately manipulating the geometry of the ILS problem. The effectiveness of the introduced method is tested with a medium voltage variable speed drive system consisting of a three-level neutral point clamped (NPC) inverter and an induction machine. acceptedVersion