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This article proposes a fixed switching frequency (FSF)-based improved model predictive control (MPC) for a five-level active neutral-point clamped (5L-ANPC) converter. Compared to the conventional MPC for 5L-ANPC converter, the proposed MPC significantly reduces the computational burden while ensuring the balance of dc-link and flying capacitor voltages. The proposed MPC optimally selects the control voltage vectors to reduce common mode voltage (CMV), leading to a small CMV of the converter. Using three voltage vectors action per control cycle in MPC, FSF is achieved. Steady-state and dynamic performances of the proposed MPC have been evaluated by experiments. The results verify the feasibility and effectiveness of the proposed MPC method. [ABSTRACT FROM AUTHOR]

In this article, an efficient model predictive control (MPC) using virtual voltage vectors for three-phase three-level converters is proposed. The proposed MPC achieves constant switching frequency by applying four voltage vectors, including one virtual voltage vectors and three other voltage vectors, in each control cycle. In addition, to reduce the computational burden, two-stage MPC approach is adopted. The first stage chooses one of six medium voltage vectors that minimizes the cost function. Then, in the second stage, these voltage vectors including virtual voltage vectors, which locate the same sector with the optimal medium voltage vector, are involved in the MPC optimization. The advantages of the proposed MPC over the classical MPC have been validated through experimental results. [ABSTRACT FROM AUTHOR]

In this article, a low complexity finite-control-set model predictive control (FCS-MPC) based on the discrete space vector modulation (DSVM) is proposed for T-type three-phase three-level (3P-3L) converters. Different from the conventional FCS-MPC, 48 virtual voltage vectors (VVs) of the converter are constructed by real VVs based on the DSVM. Thus, the performance of 3P-3L converters is significantly improved and the peak amplitude of high-order harmonics concentrates at the sampling frequency. Furthermore, two-stage FCS-MPC based on virtual VVs is proposed to reduce the computation burden. Its first stage selects one of six virtual VVs that minimizes the current tracking error. Then, these candidate VVs located in the same sector as the optimal virtual VV selected in the first stage are evaluated in the second-stage optimization. Thus, the computational efficiency has been greatly improved. To verify the validity of the proposed control method and show its superiority over the conventional FCS-MPC, experimental results are presented. [ABSTRACT FROM AUTHOR]

With the increase of the component number, the power stress distribution among differential power processing (DPP) converters, control implementation, system cost, and reliability become the most challenging issues for a practical photovoltaic (PV) DPP system. This article introduces an improved power-rating balance (IPRB) control for the PV-to-bus based DPP architecture that ensures each PV submodule operate at its true maximum power point (MPP) while achieving more balanced power stress distribution and higher reliability. Specifically, a submodule-level finite-state-machine-based MPP tracking is implemented to guarantee always maximum power yield, whereas a string-level power-rating balancing (PRB) control is adopted to balance the unit-maximum proceeded power by DPP converters based on the built power flow model with respect to the string current. A comprehensive comparison of advanced control strategies for PV-to-bus DPP architectures, including least power point tracking, voltage equalization (VE) based PRB control, and the proposed IPRB, has been carried out with the mission-profile-based reliability assessment under different partial shading scenarios. Component-failure-rate-based reliability analysis shows that the PV-to-bus DPP architecture with the proposed IPRB control can significantly improve the system reliability. Main simulation and experimental evaluations are carried out to verify the effectiveness of the proposed control. [ABSTRACT FROM AUTHOR]

Compared with the conventional multilevel converters, the hybrid-clamped converter (HCC) reduces the number of power devices, which brings down the converter cost while enhancing its reliability for medium-voltage high-power applications. As one of typical medium-voltage HCCs, the single-phase, six-level HCC (6L-HCC) faces the main technical challenge of the voltage balance among five inner capacitors. Most of the existing pulsewidth modulation techniques cannot solve this problem. Advanced control methods that directly apply a selected voltage vector, such as the classical model predictive control (MPC), may fail to balance the inner capacitor voltages during low output frequencies. In view of this situation, this article proposes an improved MPC approach with autotuning weighting factors. It contributes to ensure excellent performance of 6L-HCC under all operating conditions with well-balanced inner capacitor voltages. Simulation and experimental results are proposed to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Differential power processing (DPP) is regarded as a promising architecture in solving mismatching issues among photovoltaic (PV) submodules. Although conventional total-minimum-power-point (TMPP)-based real-time optimization algorithm by using the distributed submodule-level maximum power point tracking and simultaneously the centralized total-minimum-power tracking shows effectiveness in maximizing the power yield. However, uneven power stress among DPP converters, large oscillations, high additional cost for communication among DPP converters, and complicated implementation hinder the practical application. This article proposed a low-complexity power balancing point-based optimization algorithm to reduce the system cost and size, improve the system efficiency, and realize the standardized modular design for DPP converters. Furthermore, simple submodule-level voltage equalization control is implemented to eliminate expensive communication and relieve the control complexity while guaranteeing high maximum-power-point efficiency. The proposed algorithm can reduce the power rating of DPP converters compared with conventional TMPP-based control, which is beneficial to the improvement of system cost, reliability, and lifetime. Both simulation and experimental results under various scenarios are provided to validate the advantages of the proposed algorithm. [ABSTRACT FROM AUTHOR]

An optimized model predictive control (MPC) method is proposed based on the selected switching states to control the four-level hybrid-clamped converter. The proposed method utilizes 64, instead of 512, switching states, compared with a conventional MPC, which greatly eases the calculation burden while achieving the high-quality regulation of output currents and the balance of capacitor voltages. The steady-state performance at both high and low frequencies is investigated, and results are compared with those by the traditional carrier phase-shifted pulsewidth modulation method. The dynamic response to the current or frequency step change is also evaluated. Both simulation and experimental results validate the feasibility and effectiveness of the optimized MPC method. [ABSTRACT FROM AUTHOR]

As the “brain” of the modern photovoltaic power systems, dc solid-state transformers (SSTs) are playing an increasing important role in integrating different photovoltaic modules, batteries, and supercapacitors. This paper aims at improving the conversion efficiency of dc SST for a wide operating range by minimizing the backflow power of the dc SST system. First, the mathematical model of the backflow power from both input and output sides of dc SST is obtained. Then, the penalty function is derived and an enhanced triple phase shift control (ETPS) strategy is proposed to minimize the backflow power for various transmission power and voltage conversion conditions. A comprehensive comparison of the proposed ETPS with other advanced control strategies was carried out through theoretical analysis and experimental tests. Main experimental results are illustrated to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

When an emergency happens to electric vehicles, the voltage of the dc-bus capacitor, which is an important part of the permanent magnet synchronous machine (PMSM) drive system, requires to be reduced as quickly as possible. Recently, a new idea of directly using the windings to discharge the capacitor has come forth. This paper proposes a physical energy flow model (EFM) to explain explicitly the winding-based discharge mechanism first. In the EFM, the performance characteristics of the classical winding-based discharge scheme are evaluated, but it is found that the discharge time will not be qualified when the machine rotor inertia is large and the system safe current is small. In order to reject intense voltage surge, a current control algorithm is proposed to bleed the capacitor voltage. Moreover, the proposed current control method shortens the discharge period to below 3 s for the system studied. The proposed discharge algorithm is verified by the experiment that is conducted on a three-phase PMSM drive system. [ABSTRACT FROM AUTHOR]

This paper presents a novel model predictive control (MPC) for the T-type single-phase three-level inverters. The cumbersome procedure in tuning of weighting factors is eliminated so that the implementation of the proposed MPC becomes easy. The constant switching frequency is achieved during the control implementation in order to facilitate the filter design. In order to optimize the distribution of the output current harmonics, multiple voltage vectors are employed in each control cycle with their application times setting inversely proportion to the respective cost function. The redundant small voltage vectors are utilized to balance the neutral point voltage of the inverter by directly regulating the upper and lower dc-link capacitors voltages. Finally, the proposed MPC algorithm is experimentally evaluated and compared with other two unfixed switching frequency MPC algorithms in terms of the steady state, transient performance, and parameter sensitivity. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) suffers from high computational burden and cumbersome tuning of weighting factors especially for three-level three-phase inverters. Here, a fast finite-switching-state MPC (FSS-MPC) algorithm without weighting factors is proposed. First, the deadbeat control is used to construct the voltage vector reference. Then, the T-type three-level three-phase inverter topology is selected and voltage vectors are carefully tuned in order to minimize the neutral-point (NP) voltage fluctuation. The voltage vectors that are far from the desired voltage vector reference and go against balancing the NP voltage will not participate in the cost function optimization. Thus, only 3 effective voltage vectors instead of totally 27 vectors are required in the implementation of the proposed FSS-MPC algorithm, which saves computation time up to 53.3%. Furthermore, the proposed algorithm makes the tuning of the weighting factor unnecessary, which simplifies the practical implementation and improves the portability of the algorithm. Finally, an experimental prototype was established and main results including the steady-state and dynamic performance were presented to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

As key component for the flexible dc distributed power system, the dual active bridge (DAB)-converter-based solid-state transformer (SST) with high efficiency for a wide operating range is essential. However, with the traditional phase-shift control, high backflow power and current stress will significantly affect the conversion efficiency. In this paper, the backflow power characteristics in both sides of DAB-based SST converters are comprehensively analyzed. On this basis, complete transmission power, backflow power, and peak current mathematical models are established. Then, a minimum-backflow-power-based extended-phase-shift control strategy is proposed with the determination of optimal phase-shift pairs by using the Karush–Kuhn–Tucker function for various scenarios. The backflow power and current stress curves with different algorithms are compared. It shows the proposed control can improve the output power regulation flexibility, minimize the backflow power, and improve the efficiency in wide operating range. Finally, a DAB-based SST prototype was developed and the experimental results verified the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]