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This paper proposes a model predictive control with space vector modulation (MPC-SVM) method that is based on using a voltage angle to reduce ripple components in open-end winding interior permanent magnet synchronous motor (OEW-IPMSM). Conventional model predictive control (CMPC) provides fast transient states by applying an actual voltage vector each switching period. However, due to the limited magnitude of voltage vectors, the CMPC causes large torque ripple and low current quality. The MPC-SVM method proposed herein generates virtual voltage vectors based on the voltage angle and surrounding area. Virtual voltage vectors provide various magnitudes and positions except for areas that are not in use. The optimal reference voltage vector is derived as the result of the cost function operation applied through the space vector modulation (SVM) method, and it improves the steady-state compared to the CMPC. Therefore, torque ripple is reduced and current quality is improved by using fewer virtual voltage vectors, and this results in superior steady-state characteristics. The validity of the proposed MPC-SVM method based on the voltage angle for driving OEW-IPMSM is affirmed through simulation and experimental results in comparison to the CMPC.

This paper proposes an advanced discontinuous pulse-width modulation (DPWM) scheme for a dual inverter to reduce switching loss. A dual inverter is used to drive an open-end winding interior permanent magnet synchronous motor (OEW-IPMSM). It is composed of double two-level inverters with large switching loss owing to the use of 12 switching devices. When a current phase changes, the switching loss cannot be minimized by using a conventional DPWM scheme. As the conventional DPWM scheme uses reference voltage for switching, the switching loss cannot be minimized due to the difference between the phases of the stator current and phases of reference voltages. However, the proposed DPWM scheme with additional calculations of the current phase can minimize switching loss. When the current phase changes, the proposed DPWM is switched to ±30° of the maximum point of the current. Furthermore, the effectiveness of the proposed switching loss reduction ability is verified through simulations and experimental results.

Multilayer neural network-based model predictive control (MLNN-MPC) has received a lot of attention in different power electronic applications. However, the computational burden often imposes limitations in low-order DSPs especially if a large number of voltage vectors (VVs) are used. The execution time of MLNN-MPC in low-order DSPs is affected heavily by the number of input, output, neurons in the hidden layer, and the type of activation function. Furthermore, MLNN contains many parameters that needed to be optimized, such as initial weights, number of iterations, and number of neurons. Therefore, in this study, a creative single-layer neural network-based model predictive control with discrete space vector PWM (SLNN-MPC-DSVPWM) is proposed to overcome these limitations. The main advantages of the proposed method include easy implementation on low-order DSPs, better performance compared with MLNN-MPC, allowing the use of a large number of VVs, and no initialization of lookup tables for all VVs. The proposed SLNN is trained using the Levenberg-Marquardt algorithm and results in an execution time of only $8~\mu \text{s}$ compared with the complexity of the conventional MPC-DSVPWM and recent MLNN-MPC methods. The SLNN-MPC-DSVPWM is validated by both simulation and experimental results for permanent magnet synchronous motors.

This paper proposed a GRU/LSTM-based deep regression model for thermal estimation of modular multilevel converter submodule. The MMC is composed of many submodules with the power semiconductors such as IGBTs and MOSFETs. The switches are the main components determining the reliability of the MMCs, and the swing of junction temperature causes most switch failures in the power semiconductors. So, thermal estimation is essential to improve the reliability of the MMC systems. Thermal modeling is a regression problem of time-series data, considering various environmental conditions. The conventional models cannot reflect the complex environmental conditions due to their fixed mathematic formulas. Therefore, this paper proposes the deep regression model that can estimate the junction temperature by using the arm current of the MMC submodule. The proposed model improved the accuracy of thermal estimation by more than 7.2 times compared to the existing method. Moreover, it does not require pre-processing and takes about 4.5ms on average to process 100ms data.

This paper proposes a reduction method for DC-link ripple current and common-mode voltage (CMV) in a hybrid active neutral-point-clamped (ANPC) inverter. A Si and SiC hybrid ANPC inverter has been developed recently to overcome the extremely high cost of a full-SiC ANPC inverter. A hybrid ANPC requires much fewer SiC MOSFETs than a full-SiC ANPC inverter while providing a comparable power density. Voltage source inverters such as hybrid ANPC inverters utilize electrolytic capacitors, which have a large capacitance per volume, as a DC link. However, an electrolytic capacitor is one of the most vulnerable components in a power electronic converter due to its small allowable ripple current. A large ripple current flowing into the electrolytic capacitor generates a heat loss, which shortens the lifetime of the capacitor. Furthermore, the common-mode voltage (CMV) causes an undesirable leakage current and electromagnetic interference. The CMV depends on the pulse-width modulation of the voltage source inverters. The proposed method enhances the reliability of the hybrid ANPC inverter by reducing the DC-link ripple current and CMV simultaneously. The effectiveness and validity of the proposed method are verified through simulations and experimental results.

In this paper, a new method for reducing the ripples of torque and flux is proposed for the predictive torque control (PTC) of permanent magnet synchronous motors. The conventional PTC uses equations to analyze the relationship between the electrical torque and voltage with a fixed magnitude of reference voltage. Consequently, flux and torque ripples increase significantly at low-speed operation. This paper proposes an improved PTC algorithm using a simple duty-ratio regulator. The proposed method will minimize the torque error by calculating an appropriate torque minimization function to mitigate the induced torque and flux ripple at low speed operation. This torque minimization function is synthesized into the space vector pulse-width modulation block to reduce the torque ripple induced owing to the fixed time duration. The proposed scheme considerably reduces the torque and flux ripples and establishes a fast-dynamic response of the torque in the transient state. Simulation and experimental results show that the proposed method achieves a more efficient steady-state performance and a faster step response compared with the conventional PTC.

The cascaded H-bridge multilevel inverter (CHMI) is a modular structure that consists of many power semiconductor switches. With this increase in the number of power semiconductor switches, it is hard to predict and handle the failure of the devices, and hence reliability of CHMI decreases. The major cause of power semiconductor switch failure is junction temperature that is produced by power losses. The study proposes a multi-carrier pulse-width modulation (PWM) scheme for reduction in switching losses of CHMI. In the proposed modulation scheme, the two legs conduct switching operation at different frequencies for switching reduction. One leg conducts switching operation with high frequency, while the other leg conducts switching operation with fundamental frequency. The switching operations with different frequencies cause unbalanced switching loss to each leg. Therefore, the junction temperature that is based on power losses leads to different life-times for the power semiconductor switch. Additionally, the switching frequency of the two legs is alternated to evenly distribute switching losses and junction temperature. Simulation and experimental results verify the performance of the proposed PWM scheme.

In this paper, an optimized space-vector modulation (SVM) to reduce DC-link ripple current in three-level inverters is presented. Various types of capacitors can be utilized to balance the voltage in the DC-link of voltage source inverters. Electrolytic capacitors are widely used owing to their large capacitance per volume. However, electrolytic capacitors have a short lifespan because the allowable ripple current is low. A conventional SVM that is focused on improving harmonic characteristics. Therefore, it cannot balance the DC-link ripple current properly because using some voltage vectors increases the DC-link ripple current. To overcome this limitation and extend the lifespan of the capacitors, an optimized SVM is proposed to reduce the DC-link ripple current. The proposed modulation scheme synthesizes the reference voltage by choosing voltage vectors that cause smaller increases in the DC-link ripple current, avoiding those that cause larger increases. The effectiveness of the proposed optimized SVM is verified by simulations and experimental results.

In recent decades, renewable energy has become an important part of the power generation field. In any renewable energy system, power converters form the dominant part, owing to their important role. However, such converters are exposed to the danger of single and/or multiple open- and short-circuit faults. This paper proposes a creative control strategy for tolerating the faults by generating a new switching sequence and reference signals in hybrid active natural point clamped (ANPC) converters. The hybrid ANPC convertors are exposed to consequent short- or open-circuit faults simultaneously for each kind of faults. In these regards, the operation under multi-short-circuit and multi-open-circuit faults are analyzed and described. Correspondingly, the control strategy with the selection of new vectors under the faulty conditions is explained and clarified in detail. Furthermore, the proposed strategy does not require installing any additional devices or changing the original topology, and it can be applied to hybrid ANPC converters without any special requirements to withstand high voltage levels. The effectiveness of the proposed control strategy is verified and confirmed by simulation results and experimentally tested using a 15-kW hybrid ANPC prototype converter.

This paper proposes open fault diagnosis and tolerance control methods for grid-connected hybrid active neutral-point-clamped (ANPC) inverters with optimized carrier-based pulse width modulation. The hybrid ANPC inverter is composed of silicon carbide metal-oxide-semiconductor field effect transistors and Si-insulated gate bipolar transistors. Open faults of switch devices lead to the distortion of output currents, inverter performance degradation, and low reliability. Therefore, the open-circuit fault diagnosis and the tolerance control methods should be handled to improve the reliability of the inverter. The fault tolerance control methods for grid-connected inverters should also consider the fixed voltage modulation index as the modulation index is fixed. In this study, the proposed fault tolerance control method handles the open fault without reducing the modulation index. The implementation of the proposed method is easy and can be conducted through a simple change in the reference waveform. The effectiveness of the proposed fault detection and fault tolerance control methods was verified through the simulation and experimental results.

This article presents an open-switch fault detection method for a hybrid active neutral-point clamped (HANPC) inverter based on deep learning technology. The HANPC inverter generates a three-level output voltage with four silicon switches and two silicon carbide switches per phase. The probability of open fault in switching devices increases because of the large number of switches of the entire power converter. The open-switch fault causes distortion of output currents. A convolution neural network (CNN) comprising several convolution layers and fully connected layers is used to extract features of distorted currents. A CNN network was trained using three-phase current information to determine the location of the open-switch fault. Our proposed CNN model can accurately detect approximately 99.6% of open-switch faults without requiring additional circuitry and regardless of the current level within an average time of 1.027ms. The feasibility and effectiveness of the proposed method are verified by experimental results.

This paper proposes an improved discontinuous pulse-width modulation (DPWM) method based on phase-shifted PWM (PS-PWM) for three-phase cascaded H-bridge (CHB) multilevel inverters. Due to the CHB multilevel inverters employ a large number of power semiconductor switches, they suffer from device failures because the switches are one of the major failure factors in a power electronic system. Therefore, the reliability and life-time of CHB multilevel inverters are mainly determined by the reliability of switches. The most failure of switches is occurred by its accumulated thermal stress which is generated by power losses including the conduction and switching loss. By applying the conventional DPWM, the life-time of switches can be extended because it reduces the switching loss. The conventional DPWM, however, still operates with high speed carrier frequency and it is not enough to reduce the switching loss of the CHB multilevel inverter with a large number of inverter cells. The proposed novel DPWM method provides the improved switching loss reduction through the different switching behaviors for each leg. Additionally, the rotation scheme promises even power distribution and life-time management among inverter cells in a CHB multilevel inverter. The simulation results and experimental results confirm the switching loss reduction and even power distribution abilities of the proposed modulation method.

This paper deals with a new torque ripple minimization method for a Switched Reluctance Generator (SRG). Although, the SRG has many advantages including simple and robust construction, and high power density as a generator, it has not been widely employed in the industry. One of the major drawbacks of the SRG is its high torque ripple that results in high noise operation of the generator. In this paper, a non-unity Torque Sharing Function (TSF) is proposed to minimize the torque ripple over a wide speed range of operation. Simulations as well as experimental results are presented to verify the effectiveness of the proposed torque ripple minimization technique.

This paper presents an indirect matrix converter (IMC) topology for hybrid electric vehicle (HEV) application with three-phase and single-phase outputs. The HEV includes mechanical, electrical, control, and electrochemical systems among others. In the mechanical system, a traction motor and a compressor motor are used to drive the HEV. The traction motor and the compressor motor are usually operated as three-phase and single-phase motors, respectively. In this respect, a dual AC-drive system can operate the traction and the compressor motor simultaneously. Furthermore, compared to a conventional dual matrix converter system, the proposed topology can reduce the number of switches that the dual outputs share with a DC-link. The application of this system for HEV has advantages, like long lifetime and reduced volume due to the lack of a DC-link. The proposed control strategy and modulation schemes ensure the sinusoidal input and output waveforms and bidirectional power transmission. The proposed system for the HEV application is verified by simulation and experiments.

The utilization of three-level T-type (3L T-type) inverters in finite set-model predictive control (FS-MPC) of grid-connected systems yielded good performance in terms of current ripples and total harmonic distortions. To further improve the system’s performance, discrete space vector modulation (DSVM) was utilized to synthesize a higher number of virtual voltage vectors. A deadbeat control (DBC) method was used to alleviate the computational burden and provide the optimum voltage vector selection. However, 3L inverters are known to suffer from voltage deviation, owing to the imbalance of the neutral-point voltage. We have proposed a simplified control strategy for balancing the neutral point in the FS-MPC with DSVM and DBC of grid-connected systems, not requiring a weighting factor or additional cost function calculation. The effectiveness of the proposed method was validated using simulation and experiment results. Our experimental results show that the execution time of the proposed algorithm was significantly reduced, while its current quality performance was not affected.

This paper proposes an output current ripple reduction algorithm using a proportional-integral (PI) controller for an energy storage system (ESS). In single-phase systems, the DC/AC inverter has a second-order harmonic at twice the grid frequency of a DC-link voltage caused by pulsation of the DC-link voltage. The output current of a DC/DC converter has a ripple component because of the ripple of the DC-link voltage. The second-order harmonic adversely affects the battery lifetime. The proposed algorithm has an advantage of reducing the second-order harmonic of the output current in the variable frequency system. The proposed algorithm is verified from the PSIM simulation and experiment with the 3 kW ESS model.

This paper proposes a new method to reduce the ripple current of the DC-link capacitor in a two-level voltage source inverter (VSI), with a discontinuous pulse-width modulation (DPWM). In real applications, a capacitor block is very bulky, due to the parallel connection of several capacitors that share the value of the ripple current. Hence, it contributes significantly to the volume and weight of the whole system. Conventional DPWM is used to minimize the amount of switching for the power transistors, therefore, reducing stress and power loss. This leads to increased efficiency and reliability of the system. Nevertheless, the reduction of the DC link ripple current is still not optimal. Therefore, the proposed method introduces a PWM phase-shift technique to provide further reduction of the DC-link ripple current in a DPWM-based VSI. The efficacy of the proposed method is confirmed by simulation and experimental results.

This paper proposes a second-order harmonic reduction technique using a proportional-resonant (PR) controller for a photovoltaic (PV) power conditioning system (PCS). In a grid-connected single-phase system, inverters create a second-order harmonic at twice the fundamental frequency. A ripple component unsettles the operating points of the PV array and deteriorates the operation of the maximum power point tracking (MPPT) technique. The second-order harmonic component in PV PCS is analyzed using an equivalent circuit of the DC/DC converter and the DC/AC inverter. A new feed-forward compensation technique using a PR controller for ripple reduction is proposed. The proposed algorithm is advantageous in that additional devices are not required and complex calculations are unnecessary. Therefore, this method is cost-effective and simple to implement. The proposed feed-forward compensation technique is verified by simulation and experimental results.

This paper presents a method to improve the quality of input-output currents in a three-level neutral-point clamped (NPC) inverter with small direct current-link (DC-link) capacitor systems. The inverter systems with the small DC-link capacitors have several advantages in terms of cost, volume, life-time, and reliability when compared to inverters that use large DC-link capacitors. However, there are problems with respect to the deterioration of the input current quality and a severe ripple of neutral-point voltage (NPV), which can cause an aggravated output current. To mitigate these issues, an additional circuit is applied for the input current shaping and a compensation algorithm is applied to reduce the ripple voltage of NPV. The effectiveness of the proposed design and control method is verified with various simulation and experimental results.

This paper proposes a balanced current control strategy for the current source rectifier (CSR) stage of an indirect matrix converter (IMC) under unbalanced grid voltage conditions. If the three-phase grid connected to the voltage source inverter (VSI) of the IMC has unbalanced voltage conditions, it affects the currents of the CSR stage and VSI stage, and the currents are distorted. Above all, the distorted currents of the CSR stage cause instability in the overall system, which can affect the life span of the system. Therefore, in this paper, a control strategy for balanced currents in the CSR stage is proposed. To achieve balanced currents in the CSR stage, the VSI stage should receive DC power without ripple components from the CSR stage. This is implemented by controlling the currents in the VSI stage. Therefore, the proposed control strategy decouples the positive and negative phase-sequence components existing in the unbalanced voltages and currents of the VSI stage. Using the proposed control strategy under unbalanced grid voltage conditions, the stability and life span of the overall system can be improved. The effectiveness of the proposed control strategy is verified by simulation and experimental results.

This paper proposes a fault detection and the improved fault-tolerant control for an open fault in the five-phase inverter driving system. The five-phase induction machine has a merit of fault-tolerant control due to its increased number of phases. This paper analyzes an open fault pattern of one switch and proposes an effective fault detection method based upon this analysis. The proposed fault detection method using the analyzed patterns is applied in the power inverter. In addition, when the open fault occurs in the one switch of the induction machine driving system, the proposed fault-tolerant control method is used to operate the induction machine using the remaining healthy phases, after performing the fault detection method. Simulation and experiment results are provided to validate the proposed technique.