Optimal Switching Sequence Research Articles

Discovering the incorporation limits for wurtzite AlPyN1−y grown on GaN by metalorganic vapor phase epitaxy

We report on the growth of AlPN on GaN/sapphire templates by metalorganic vapor phase epitaxy using tertiarybutylphosphine (tBP) and NH3 as group-V precursors. P is easy to incorporate into the group-III lattice site, forming PAl anti-site defects and shrinking lattice constants that are even beyond AlN since Al is larger than P. We found that higher temperatures favor P incorporation on the N-sublattice, forming AlPyN1−y, while growth temperatures below 1000 °C result in dominant P incorporation on the Al-sublattice, forming PAl anisites. Similarly, larger NH3 flows stabilize GaN, leading to flat interfaces, but favor the formation of PAl. Furthermore, the P incorporation into AlPyN1−y is non-linear. At very low tBP flows, it initially increases to reach a maximum. Further increasing the tBP flow increases mostly the incorporation of P on the Al-sublattice, and the c-lattice constant decreases again. This leaves a small window of low V/III ratios below 5 and low P/N ratios of 1% or smaller, leading up to ∼4% P incorporation at typical growth temperatures of GaN. However, at such low V/III ratios, GaN is not stable even with N2 carrier gas and requires optimized switching sequences to minimize its decomposition and preserve flat interfaces. Eventually, a 10 nm coherent layer of AlP0.01N0.99 could be reproducibly grown on top of GaN channels with a smooth surface, an abrupt AlPN/GaN interface, and a two-dimensional electron gas with an electron mobility of ∼675 cm2/V s and a sheet carrier density of 1.5 × 1013 cm−2 at room temperature.

Optimal Switching Sequence MPC for Four-Leg Two-Level Grid-Connected Converters

This paper presents a versatile and effective model predictive current control strategy based on optimal switching sequences for four–leg two–level grid–connected converters. The proposed control methodology, presents an excellent dynamic performance, good tracking of high-frequency reference signals, fixed switching frequency, and well-formed harmonic spectrum, enabling the proposed controller to govern shunt active filters and distributed generation applications based on four-leg converters. Experimental results demonstrate the effectiveness and high-quality performance obtained with the proposed strategy.

An Optimal Switching Sequence Model Predictive Control Scheme for the 3L-NPC Converter with Output LC Filter

In some applications of microgrids and distributed generation, it is necessary to feed islanded or stand-alone loads with high-quality voltage to provide low total harmonic distortion (THD). To fulfil these demands, an LC filter is usuallyconnected to the output terminals of power electronics converters. A cascaded voltage and current control loop with pulse-width modulation schemes are used to regulate the voltages and currents in these systems. However, these strategies have some drawbacks, particularly when multiple-input–multiple-output plants (MIMO) are controlled using single-input–single-output (SISO) design methods. This methodology usually produces a sluggish transient response and cross–coupling between different control loops and state variables. In this paper, a model predictive control (MPC) strategy based on the concept of optimal switching sequences (OSS) is designed to control voltage and current in an LC filter connected to a three-level neutral-point clamped converter. The strategy solves an optimisation problem to achieve control of the LC filter variables, i.e., currents and output voltages. Hardware-in-the-loop (HIL) results are obtained to validate the feasibility of the proposed strategy, using a PLECS–RT HIL platform and a dSPACE Microlab Box controller. In addition to the good dynamic performance of the proposed OSS–MPC, it is demonstrated using HIL results that the control algorithm is capable of obtaining low total harmonic distortion (THD) in the output voltage for different operating conditions.

Model Predictive Control With Reduced Common-Mode Voltage Based on Optimal Switching Sequences for Nested Neutral Point Clamped Inverter

This paper proposes a new model predictive control strategy with reduced common-mode voltage (CMV) based on optimal switching sequences (OSS-MPC) for a three-phase (3PH) four-level nested neutral point clamped (4L-NNPC) inverter. The proposed method controls load current, mitigates the voltage fluctuations of flying capacitors (FCs) in the entire operating frequency range, and provides a constant inverter switching frequency. In this work, the switching sequences (SSs) are configured so that the peak CMV is limited to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$V_{dc}/6$</tex-math></inline-formula> . By involving time in the optimization process, the balance of FCs voltages is realized in the entire operating frequency, especially in low-frequency operating mode. Also, the voltage fluctuations of FCs are further mitigated through a mathematical-logic technique. To implement the proposed method on the digital signal processor, the deadbeat control technique is also used to reduce the search space and thus, computation burden. The performance of the proposed method is verified in MATLAB/SIMULINK. The experimental results are carried out based on a scaled-down hardware prototype validating the theoretical claims.

Low Complexity Model Predictive Flux Control Based on Discrete Space Vector Modulation and Optimal Switching Sequence for Induction Motors

In this paper, a low-computational burden model predictive flux control (MPFC) based on discrete space vector modulation (DSVM) and the optimal switching sequence (OSS) is proposed for achieving switching frequency (SF) and computational burden efficiencies in motor drives fed by two-level voltage source inverter. The DSVM is used to extend the prediction candidates of MPFC and greatly improve the performance of the controller. A generalized minimum flux error method independent of the number of virtual vectors is derived to cancel the exhaustive optimization method and lower the execution time of the proposed algorithm. In addition, new over-modulation and OSS schemes are designed to optimize the use of DC-link voltage and mitigate the inverter SF when implementing the optimal control action into switching states. The comparative experimental results show that without significant performance degradation, the proposed strategy provided about 50% SF and 25% execution time reductions compared to the classic MPFC methods.

Discrete space vector modulation and optimized switching sequence model predictive control for three-level voltage source inverters

This paper proposes a discrete space vector modulation and optimized switching sequence model predictive controller for three-level neutral-point-clamped inverters in grid-connected applications. The proposed strategy is based on cascaded model predictive control (MPC) for controlling the grid current while maintaining the capacitor voltage balanced without weighting factor. To enhance the closed-loop performance, the external MPC evaluates 19 basic and 138 virtual vectors (VV) of the proposed space vector method. The optimal control voltage is then selected using an extended deadbeat method to reduce the execution time of the proposed control algorithm. By using the discrete space vector modulation principle, the VV are synthesized based on switching sequence (SS) and are divided into negative and positive SSs considering their impact on the neutral point (NP) potential. The inner MPC evaluates both types of SSs and selects the one that keeps the capacitor voltage balanced. Various controllers are evaluated and compared against the proposed control strategy. The results show that the proposed strategy improves performance without weighting factor, while maintaining a total harmonic distortion of current to be less than 2%. Compared to the modulated MPC which provides the same fixed switching frequency, the proposed controller reduces the computational burden by over 50% while also providing better NP voltage balance accuracy.

Total Harmonic Distortion Reduction in Multilevel Inverters through the Utilization of the Moth–Flame Optimization Algorithm

This paper shows the implementation of the Moth–Flame Optimization algorithm in a Cascade-H multilevel inverter with five and seven levels to determine the optimal switching sequence of the inverter’s semiconductor devices. The algorithm was coded in Matlab software, and the obtained switching sequences were implemented in a Cascade-H multilevel inverter laboratory prototype, where the output voltage waveform was obtained using a digital oscilloscope. The experimental Total Harmonic Distortion was obtained using a power quality analyzer. The experimental results show the improvement of the Total Harmonic Distortion in the voltage output. These results were compared with other papers in the literature with different metaheuristic methods concerning the same modulation. These findings demonstrate the feasibility of employing the Moth–Flame Optimization Algorithm to significantly reduce the Total Harmonic Distortion, obtaining a lower value than most analyzed papers.

Optimal Modulation Strategy for Current-Source Converter to Reduce DC-Link Current Ripple

As one of the most important performance index of a current source converter (CSC), DC-link current ripple is closely related to the modulation strategy. Excessive DC-link current ripple not only reduces the system efficiency, but also increases the total harmonic distortion (THD) of grid current and leads to more electromagnetic interference. To get around this problem, optimizing modulation strategy is more attractive compared with increasing the inductor or switching frequency. To this end, based on detailed analysis of the mechanism to reduce the DC-link current ripple and the inherent deficiency of current ripple continuous increase phenomenon between two adjacent sequences, a novel modulation strategy by employing optimized switching sequence according to the modulation index is proposed. By applying the proposed modulation strategy, the current ripple is effectively reduced in the full range of modulation index. Furthermore, the proposed scheme is easy to implement in practice without increasing the switching frequency or inductor. Finally, selected experimental results confirm the validity of theoretical analysis.

Influence of switching sequences on the neutral point voltage balance in a three-level voltage source invertor

BACKGROUND:Ensuring the voltage balance of the neutral point of the DC link within acceptable limits is one of the mandatory requirements during the operation of a three-level autonomous neutral point clamped voltage source inverter. It is known that neutral point voltage imbalance can adversely affect the operation of the inverter and the load at all, lead to the failure of both power switches and capacitors in the DC link. Neutral point voltage imbalance mostly often occurs due to the asymmetry of the nominal values of DC capacitors, inconsistent properties of switching devices, asymmetric three-phase load, and also due to the imperfection of the converter control algorithm.&#x0D; AIMS:Selection of the optimal switching sequence that ensures the smallest deviation of the neutral point voltage and the number of switching of power switches in a three-level voltage source inverter.&#x0D; METHODS:For an objective comparison of the considered switching sequences and their influence on the neutral point voltage balance, a simulation model of a three-level neutral point clamped voltage source inverter was developed in theMATLAB/Simulinksoftware. To control this inverter, a space vector modulation method was used with three different switching sequences: five-segment, seven-segment and standard.&#x0D; RESULTS:The topology of a three-level neutral point clamped voltage source inverter is presented. The experimental dependencies of the neutral point voltage deviation error was taken with a change in the modulation coefficient, the frequency of the fundamental harmonic at the inverter output, and load characteristics for three different switching sequences.&#x0D; CONCLUSIONS:In this paper, the influence of the basic vectors and the influence of switching sequences on the neutral point voltage balance are studied. Combinations of states of large and zero basic vectors do not affect the neutral point voltage. For the medium basic vectors, the neutral point voltage can increase or decrease depending on the operating conditions of the inverter. The small basic vectors significantly affect the neutral point voltage. Considering the abovementioned, the seven-segment sequence that ensures both the optimal balance of the neutral point voltage and the level of switching losses should be considered as the best switching sequence for a three-level inverter.

Three-Stage Duty Cycle-Based Deadbeat Predictive Torque Control for Three-Phase SPMSMs With CMV Reduction

Model Predictive Torque Control (MPTC) is highly regarded for its simple structure, rapid dynamic response, and optimized control performance when applied to actual motor driving systems. However, conventional MPTC techniques often lead to undesirable effects in three-phase inverter-based surface-mounted permanent magnet synchronous motors (SPMSMs), such as high electromagnetic torque, stator flux ripples, and significant current harmonic distortion. Notably, the generalized MPTC approach generates a substantial common mode voltage (CMV) that can cause damage to the motor bearing and winding insulation in SPMSMs. To address these issues, this paper proposes a three-stage duty cycle-based deadbeat predictive torque control (DCDPTC) technique for SPMSMs. The proposed technique leverages the volt-second equilibrium theorem by aligning the duty cycles with the predicted electromagnetic torque, stator flux, and their respective target values while accounting for extreme cases, accordingly electromagnetic torque and stator flux ripples as well as the total harmonic distortion (THD) of the stator current are minimized. In order to improve the system robustness, the duty cycle is limited to avoid the overmodulation. Furthermore, optimized switching sequences are meticulously arranged to ensure the CMV is lowered and the minimum number of switching transitions is maintained while utilizing a fixed switching frequency. The proposed technique is simplified. Its resultant performance is validated by experimental results.

Stochastic restoration of distribution networks with high penetration of solar PV systems through a generic switching order mechanism

The process of fault isolation and service restoration (FISR) is an essential component of the implementation of distribution automation. By using FISR to determine the switching order, whether manually or remotely, the network's reliability is significantly enhanced in comparison to that of conventional switching. On the other hand, it is impossible to refute the exponential development of distributed energy resources such as photovoltaic (PV) generators. This paper introduces a general FISR for distribution networks with high penetration of solar PV systems. The proposed FISR strategy is an optimum switching sequence with the goal of reaching the best restoration hour before any likely fault occurrence. The proposed framework takes into account the inherent uncertainty in network demand and renewable generation in addition to the innovative mathematical programming model for the switching order. In addition, this stochastic programming handles the radiality constraint in the restoration process by creating a fictional layer as a means of reducing the complexity of the modeling. Moreover, the impact of PV penetration level on the optimal switching order for heavy-loaded distribution feeders is addressed and investigated.

Optimal Switching Sequence Model Predictive Control for Modular Multilevel Converter

This paper proposes a new optimal switching sequence model predictive control method for modular multilevel converter (MMC). In this method, the common mode voltage (CMV) is cosidered, which makes the model more accurate. The proposed method realizes the optimization of multiple control objectives of output current tracking, circulating current suppression (CCS), and submodule voltage balancing. The sequence that allows the output current to track its reference value is calculated in the <inline-formula><tex-math notation="LaTeX">$\alpha -\beta$</tex-math></inline-formula> coordinate system. And the virtual vectors aim to suppress the circulating current without influencing the output current are inserted. Capacitor voltage balancing is achieved by redundant vectors selection and tranditional selection algorithm. These control objectives are calculated independently, thus weighting factor is not required. At the same time, the computation burden is reduced by restricting the voltage mutation. This method has a satisfactory dynamic response and steady-state performance, the simulation and experimental results are given to verify the effectiveness of the method.

Performance evaluation of isolated three-phase voltage source inverter with LC filter adopting different MPC methods under various types of load

As the variety of loads in microgrids continues to grow rapidly, the drawbacks of using conventional voltage and current double closed-loop PI control are becoming increasingly intolerable. These disadvantages include poor static tracking of the output and the need for complicated tuning of optimal PI control parameters. Model predictive control (MPC) is widely studied in recent years and gradually applied to the inverter as a modern control strategy. Currently, the research on MPC mainly focuses on reducing the computational burden of algorithms and improving computing skills. In this paper, the control theory of continuous-control-set model predictive control (CCS-MPC), optimal switching vector model predictive control (OSV-MPC), quasi-sliding mode model predictive control (QS-MPC) and optimal switching sequence model predictive control (OSS-MPC) are elaborated. Also, the disadvantages of adopting conventional voltage and current double closed-loop PI control on microgrids are clarified. Moreover, aiming at evaluating the influence of connecting and/or removing the common loads, such as electric vehicles to the microgrid on the output performance of microgrids in practical engineering applications, single three-phase voltage source inverter with LC filter system with two-phase pure resistance load, three-phase diode rectifier bridge nonlinear load, constant power load and constant current source load applying four different MPC methods, are simulated. The simulation results show that under different types of load, system with nonlinear load applying OSV-MPC method has the biggest value of total harmonic distortion (THD) of the output voltage and the biggest steady state root mean square (RMS) tracking error of the output voltage, which are 1.33% and 2.1 V, respectively. The performances of the output voltage of the system adopting MPC are generally improved compared to the system using conventional voltage and current double close-loop PI control. Regarding the output voltage performance of a system under load step change, a system using the OSS-MPC method with a nonlinear load exhibits the smallest overshoot of the output voltage and the smallest root mean square value of the tracking error (RMSE) between the output voltage and the reference value within 20ms after the load step change. Specifically, the overshoot and RMSE are 2.804 V and 0.810 V, respectively. The simulation results provide valuable guidance for selecting the appropriate model predictive control strategy for microgrid integrating complex loads, such as electric vehicles in practical applications.

Degradation-Conscious Multiobjective Optimal Control of Reconfigurable Li-Ion Battery Energy Storage Systems

Lithium-ion battery energy storage systems are made from sets of battery packs that are connected in series and parallel combinations depending on the application’s needs for power. To achieve optimal control, advanced battery management systems (ABMSs) with health-conscious optimal control are required for highly dynamic applications where safe operation, extended battery life, and maximum performance are critical requirements. The majority of earlier research assumed that the battery cells in these energy storage systems were identical and would vary uniformly over time in terms of cell characteristics. However, in real-world situations, the battery cells might behave differently for a number of reasons. Overcharging and over-discharging are caused by an electrical imbalance that results from the cells’ differences in properties and capacity. Therefore in this study, a stratified real-time control scheme was developed for the dual purposes of minimizing the capacity fade and the energy losses of a battery pack. Each of the cells in the pack is represented by a degradation-conscious physics-based reduced-order equivalent circuit model. In view of the inconsistencies between cells, the proposed control scheme uses a state estimator such that the parametric values of the circuit elements in the cell model are determined and updated in a decentralized manner. The minimization of the capacity fade and energy losses is then formulated as a multiobjective optimization problem, from which the resulting optimal control strategy is realized through the switching actions of a modular multilevel series-parallel converter which interconnects the battery pack to an external AC system. A centralized controller ensures optimal switching sequence of the converter leading to the maximum utilization of the capacity of the battery pack. Both simulation and experimental results are used to verify the proposed methodologies which aim at minimizing the battery degradation by reconfiguring the battery cells dynamically in accordance with the state of health (SOH) of the pack.

Model predictive control of modular multilevel converter based on fixed switch state set for offshore wind power

AbstractThis paper aims at the problems of the traditional modular model predictive control (MPC) of modular multilevel converter (MMC) with huge computational complexity and high equivalent switching frequency. In this paper, a model predictive control method based on fixed switch state set (FSS‐MPC) is proposed. In this method, two cost functions are used to control phase current and circulating current. Meanwhile, the number of the upper and lower on‐state sub‐modules (SM) is obtained by cost functions. In order to obtain the optimal switching sequence of SM, FSS‐MPC adopts a SM capacitive voltage balancing strategy which has low sorting frequency. Under the control of the FSS‐MPC, the amount of switch combination and sorting computation are greatly reduced. In addition, the switching frequency is extremely low. Finally, to verify the effectiveness and feasibility of the proposed control strategy, a simulation system of 11‐level MMC for offshore wind power has built on the MATLAB/Simulink platform.

Theoretical and Experimental Comparative Analysis of Finite Control Set Model Predictive Control Strategies

This research paper studies and highlights the features of the most popular finite control set model predictive control (FCS-MPC) strategies available in the state of the art, which are the optimal switching vector (OSV-MPC), modulated model predictive control (M2PC), and optimal switching sequence (OSS-MPC) methods. Thus, these strategies are studied experimentally by analyzing the transient and steady state performance using a grid tie conventional three-phase two-level voltage source inverter (VSI) with inductive output filter in a Typhoon HIL real-time simulator (RTS) with a Texas Instruments F28379D digital signal processor (DSP). Hence, quantitative indicators, such as the maximum tracking error, the mean absolute error, the settling time, the total harmonic distortion, the switching frequency spectrum, the switching pattern, and the computational burden are compared with the aim to deduce the best strategy for each criteria.

Optimal switching sequence control for current stress reduction of DC-link capacitors in dual-three phase PMSM drives

The safety and installation space of DC-link capacitor is crucial for dual-three phase permanent magnet synchronous machines (DTPMSM) drives in industrial applications. Reducing the capacitor current stress can contribute to decrease the designed capacitor value and install size, thus enhance safety of drives fed by two parallel inverters. Therefore, an optimal switching sequence control scheme for DTPMSM drives is proposed to reduce the DC-link capacitor current stress in this paper. For DTPMSM drives, the maximum four adjacent voltage vectors control (MFAVC) method is usually adopted due to its control flexible and stability characteristic. Based on MFAVC, the capacitor current can be derived though the current reconstruction theory to reorder the current amplitude over one switching period. Through the rearrangement of voltage vector and duration, the theoretical analysis of capacitor current reduction is presented. On this basis, the optimal switching sequence control method can be implemented based on the minimized current sum of the two inverters. The performance of proposed method has been evaluated via. comparatively experimental tests on a prototype 3 kW DTPMSM drive, which shows superior features on reducing capacitor current stress. Furthermore, it is also found that the proposed method is helpful to redesign a small capacitor value for DTPMSM drives.

A Novel Modulation Method Based on Model Prediction Control With Significantly Reduced Switching Loss and Current Zero-Crossing Distortion for Vienna Rectifier

Finite control set model predictive control (FCS-MPC) is widely used in rectifiers due to its fast response. When there are multiple control objectives, the optimal switching sequence is selected by minimizing the cost function with weighting factors. However, the reduction of current ripple caused by output error and switching loss is in conflict to a certain extent for FCS-MPC. In addition, when multiple objectives are controlled, the selection of weighting factor is a serious challenge. Therefore, a modulation method based on continuous control set model predictive control is proposed in this article. Two phases are clamped and one phase is modulated, which not only can significantly reduce the switching loss without increasing the computational burden, but also can control the neutral point voltage without using weighting factors. In addition, when the proposed method is adopted, current zero-crossing distortion can be suppressed over the full range of modulation index. The effectiveness of the proposed method is verified by simulation and experimental results.

A predictive control method for switching sequence selection based on SVPWM for five‐level converter

AbstractAiming at the problems of complex realization, single control target and difficulty in selecting the optimal zero sequence voltage when the traditional space vector PWM (SVPWM) algorithm is adopted in five‐level active neutral‐point‐clamp (5L‐ANPC) converter, a predictive control optimal switching sequence selection (PC‐OSSS) method is proposed. The method adopts the SVPWM control strategy base on the line voltage coordinate and then realizes the selection of optimal switching sequence through the multi‐objective predictive control method. Firstly, the principle of SVPWM based on line voltage coordinate is introduced, and all switching sequences that can be output are obtained. Secondly, the mathematical models of the floating capacitor (FC) voltage, the neutral point (NP) voltage and the common mode (CM) voltage corresponding to each switch sequence are established. Finally, the optimal switch sequence is selected by using the predictive control method based on priority ranking. Compared with traditional SVPWM, the outstanding advantage of this method is that the traditional qualitative comparison method is replaced by quantitative calculation. The multi‐objective control performance of the converter is improved while retaining the advantages of the traditional SVPWM fixed frequency. Finally, the practicability and effectiveness of the proposed control strategy are verified by simulation and experiment.

Polyphase Permanent Magnet Synchronous Motors Direct Current Model Predictive Control with Long Prediction Horizons

This manuscript presents a novel direct current model predictive control with long prediction horizon for medium-voltage polyphase permanent magnet synchronous motor drives. By utilizing the proposed technique, we can reduce the armature current harmonics and torque ripples, minimize the electrical and mechanical losses, improve the torque and speed rendering quality, and achieve a highly reliable permanent magnet motor drive. The state-space model of a representative polyphase permanent magnet synchronous motor is derived with the armature current and flux linkage jointly chosen as the state-space variables. Leveraging completing the squares, the mixed-integer-quadratic-programming (MIQP) problem can be formulated and efficiently solved, which provides the optimal switching sequence for the IGBT inverter. The proposed control algorithm is also implemented and examined with computer simulation to show the robustness and effectiveness.