The gallium nitride/silicon carbide (GaN/SiC) Cascode device is a composite structure, which employs a low-voltage GaN device as an assistant switch to change the high-voltage depletion-mode SiC device into an enhancement-mode device. A normally-off GaN/SiC Cascode device was constructed by low-voltage enhancement-mode gallium nitride high electron mobility transistor (GaN HEMT) and high-voltage depletion-mode silicon carbide junction field-effect transistor (SiC JFET). The Cascode device combined the advantages of GaN HEMT such as high switching speed and simple gate-driving circuit and the high blocking voltage of SiC JFET. Both the operating principle and the switching process of GaN/SiC Cascode device were analyzed in detail, and its static characteristics were also tested. A double-pulse test platform was constructed, and the switching loss of the GaN/SiC Cascode device was compared with those of the Si/SiC Cascode device and SiC JFET at varying load current. Results show that the turn-off loss of GaN/SiC Cascode device was the lowest. In addition, the three devices were applied in an LLC resonant converter respectively, and the conversion efficiency of the converter was tested, indicating that the LLC resonant converter based on GaN/SiC Cascode device exhibited the highest conversion efficiency.

The loss and volume of magnetic components in resonant DC-DC converters account for nearly 50%, which seriously restricts the improvement of power density in high-frequency converters. The magnetic integration technology can reduce the loss and volume of magnetic components, so it has been widely studied and applied. However, the traditional magnetic loss measurement methods cannot accurately and conveniently measure and evaluate the magnetic core loss of magnetic components in integrated resonant inductors and transformers, causing difficulties in the optimization of magnetic core loss. In this paper, the magnetic flux distribution in integrated magnetic components is analyzed, and a method is proposed to obtain the magnetic core loss of integrated magnetic components by testing the difference in losses before and after adding auxiliary integrated magnetic components in parallel in a resonant topology. At the same time, a parameter design method for auxiliary magnetic components is also put forward. This method can accurately and conveniently measure the magnetic core loss of integrated magnetic components under actual circuit conditions. Simulation and experimental results verified the effectiveness of the proposed magnetic loss measurement method for integrated magnetic components.

Due to the lower and significantly fluctuating voltage of micro-source modules (e.g., photovoltaic and fuel cells) in DC microgrids, there is a need for a DC-DC converter with a high gain and a high efficiency to serve as an interface circuit. Therefore, a novel active switched capacitor DC-DC converter based on an isolated Sepic topology is proposed. This converter reduces voltage spikes on the switch tube caused by leakage inductance through a clamp circuit and employs multiple boost units to achieve a high voltage gain. In addition, it also has advantages such as electrical isolation, low stress on the main switch tube and passive clamping. The operation modes and boosting mechanism of the proposed converter are studied, the component stresses are analyzed, and the efficiency of this converter is derived. Finally, a 200 W prototype was constructed in the laboratory to verify its performance.

In the wide conversion range applications of traditional DC-DC converters, there is an urgent need for higher voltage gain, efficiency and reliability. A DC-DC converter based on a switching voltage doubling clamping unit is proposed and analyzed. In this topology, the switch voltage stress is low and the inherent duty cycle is small, which helps reduce switch losses and improve the converter efficiency. All the switch devices achieve voltage clamping, thus reducing the voltage spikes generated during switch transitions. Compared with coupled windings, the single-input inductor reduces the size of the converter and the input current ripple. The shared grounding of input and output terminals ensures the output reliability. Through a comparison with other typical converters and performance analysis with a combination of a 200 W experimental prototype, the feasibility and effectiveness of the DC-DC converter based on the switching voltage doubling clamping unit were validated.

Aimed at the problems in traditional quasi-Y-source inverters such as high busbar voltage peaks and high device voltage stress, the circuit topology of an active clamp-type Y-source three-phase inverter is proposed. By adding power switch tube, capacitor and diode to form a clamping circuit, the voltage gain is improved, the voltage stress of the power device is reduced, and the continuous characteristic of input current is maintained. A third-order harmonic injection boost modulation strategy is adopted to improve the utilization rate of DC-link voltage. The working principle for this inverter is analyzed in detail, and the formulas for its voltage gain and the device voltage stress are deduced. In addition, its performance is compared with those of other inverters, and its advantage is theoretically demonstrated. Finally, a simulation model and an experimental prototype were built for verification, and both the simulation and experimental results verified the feasibility of the proposed inverter.

To address the issue of sub-module number errorscaused by harmonics based on nearest level modulation (NLM) when the voltage level is increasing in a modular multilevel matrix converter (M3C), a mathematical model for M3C was established. The operating principle for M3C based on NLM was analyzed, and an optimized sampling NLM strategy was proposed. Asimulation model of M3C consisting of 20 sub-modules was constructed based on MATLAB/Simulink, and a low-power experimental prototype of M3C was also built. Results verified the feasibility and effectiveness of the proposed method for harmonic suppression.

The hybrid cascaded nine-level inverter can output more levels using fewer H-bridge units. Under the mixed carrier cascaded modulation strategy, the quality of output voltage waveform is higher, but the output power is not balanced, which will lead to uneven heating and shorten the service life of the equipment. Under the mixed carrier phase-shift modulation strategy, the power self-balancing can be completed, but the power balancing time is too long. Aimed at these problems, a novel hybrid modulation strategy is proposed, where the high-voltage unit is modulated by a stepped wave and voltage constraints are added, and the carrier wave of the low-voltage unit is reconstructed. Compared with the traditional modulation strategy, this strategy can achieve the power balance of three units in the full modulation regime after adding voltage constraints, and reduce the time required for the power balance of the low-voltage unit. Simulation and experimental results verified the feasibility of the proposed modulation strategy.

As an excellent front-end rectifier for power supply, the VIENNA rectifier is widely used in medium-to-high voltage and high-power scenarios such as electric vehicle charging piles and wind power generation systems. However, due to the unidirectional flow of its topological energy, there may be current zero-crossing distortion under traditional control methods, resulting in weak reactive power compensation capability. Therefore, based on the analysis of current zero-crossing distortion, a control scheme integrating zero-crossing distortion suppression and reactive power compensation was adopted, with a focus on analyzing the constraints faced by the VIENNA rectifier when providing maximum reactive power compensation capability, as well as the capability of the VIENNA rectifier to provide additional reactive power compensation when delivering different active power to load. Simulation results verify that the adopted control scheme can effectively suppress the zero-crossing distortion of input current of the VIENNA rectifier and thus enhance its reactive power compensation capability.

Cascaded H-bridge photovoltaic (PV) inverters are susceptible to problems such as shading of PV modules and aging of devices. As a result, an imbalance in the output power between H-bridge units will appear, and over-modulation may occur in some units due to excessive power, resulting in a poor performance of grid-connected current and triggering the instability of the inverter system as a whole. Aimed at this problem, a segmented improved control strategy for enhancing the operating range of the PV inverter is proposed. This method compensates the third-order harmonic and multiple harmonics for some of the overmodulated units. For the severely overmodulated units, their output power are reduced at first, and then the multiple harmonics are compensated. This strategy expands the operating range of the inverter, and it ensures that no overmodulation occurs in all the units under severe power imbalance. In addition, the waveform of grid-connected current is good. The theoretical analysis and simulation results prove the feasibility and effectiveness of the novel control strategy.

Aimed at the problem that the charging and discharging state switching frequency is too high and the life is reduced during the process of wind power fluctuation suppression by energy storage, a fluctuation suppression control strategy based on the hybrid energy storage of dual battery packs is proposed. First, the adaptive moving average filter method is used to decompose the wind power to obtain the grid-connected power. Second, the wavelet packet decomposition of the energy storage target power is carried out to obtain the hybrid energy storage reference power, and the fuzzy control is used to optimize the energy storage target power, so as to prevent the energy storage from overcharge or overdischarge and make the energy storage run at the optimal depth of discharge (DOD). To make the battery run at the optimal DOD while reducing the switching times of working states, a circuit structure of dual battery packs running separately for charging and discharging tasks is adopted, and an adaptive power complementary control strategy is designed to realize power scheduling between battery packs. In addition, a power allocation strategy is also introduced to ensure the state-of-charge balance among each unit in the same battery pack. Finally, the control strategy is simulated and analyzed, and the rainflow counting method is used to evaluate the life of energy storage. Results show that the proposed control strategy can reduce the charging and discharging times of energy storage and prolong its life.

To reduce the carbon emissions of a microgrid system under operation and with the consideration of influences of uncertainties in renewable energy output on the system’s scheduling results, a two-layer optimal low-carbon economic scheduling model for microgrids containing liquid carbon dioxide (CO₂) energy storage is proposed. This model introduces a tiered carbon trading mechanism into the operation and scheduling stage of the system, so as to reduce carbon emissions of the microgrid system. Under a carbon trading scenario, the carbon emissions and scheduling cost data generated by two models of liquid CO₂ energy storage and conventional energy storage during the operation of microgrids are compared and analyzed, and results verify that the proposed model can effectively reduce carbon emissions and improve the economic efficiency after the introduction of liquid CO₂ energy storage.

The energy storage system is an important part of photovoltaic microgrid. However, the traditional battery energy storage system has many problems such as a low power density and a short service life. A supercapacitor hybrid energy storage system based on photovoltaic power generation is established, and its control strategy is proposed, under which the DC-DC converter connected to the energy storage element is controlled through the coordinated operation of model predictive control (MPC) and low-pass filter, and the DC-AC converter connected to the AC side is controlled through a virtual synchronous generator. MPC is a real-time control method, and it can determine the constraints in certain time domain in the future according to the system state at present and optimize the control objectives in the predicted time domain, which has good stability and robustness compared with other control methods. Under changes in the parameters including the intensity of solar radiation, the DC bus voltage can be kept stable, and the dynamic response capability of DC bus voltage can be improved. Finally, the system is simulated in MATLAB/Simulink, and the effectiveness of the proposed method is verified.

With a focus on the research of energy storage configuration and aimed at the problems such as incomplete data and poor data quality of distributed photovoltaic output, a configuration method for the basic responsiveness capability of energy storage based on the extreme value theory is proposed. First, a probabilistic analysis method for distributed photovoltaic output based on generalized extreme value distribution is put forward, and the power data under different granularities of extreme value is fitted and analyzed. Second, with two goals of reducing the photovoltaic abandonment rate and smoothing the output fluctuation normally, the configuration method for the basic responsiveness capability of energy storage is proposed based on the return period and return level of distributed photovoltaic output. Finally, the feasibility and extensibility of the proposed method are verified by simulations of an example based on the output data of a distributed photovoltaic power station in a certain area. Results show that the generalized extreme value distribution can achieve a good fitting of distributed photovoltaic output distribution, and the dependence on data accuracy is minor. Meanwhile, the configuration results of the basic responsiveness capability of energy storage given by the proposed method agree with the minimum storage capacity requirements for photovoltaic projects in some provinces of China.

The overall development statuses and trends of hydrogen-related industries are briefly introduced at first, and different types of electrolytic water hydrogen production technologies are compared in detail. Then, the development statuses of photovoltaic (PV) power hydrogen production, wind power hydrogen generation and wind-PV complementary hydrogen generation technologies are summarized, and the development trends in the future are investigated. Finally, the research framework system of “Green Hydrogen Plant” for a large-scale new energy hydrogen production system is constructed. The research and development ideas for key technologies involved in new energy hydrogen production are provided, the demand analysis for products and solutions required by relevant projects is conducted, and suggestions for the research direction of “wind-PV-hydrogen-storage” energy comprehensive utilization in the future are put forward.

Lithium-ion batteries are the most commonly used batteries in an energy storage system, and their state-of-health (SOH) is an important battery parameter monitored in a battery management system. In addition to the accuracy of prediction, the simulation of a user’s random charging behavior for realizingreal-time evaluation at any time is also very important. Based on the user’s random charging behavior and from the perspective of obtaining the data integrity, the SOH prediction methods are divided into three types, which are based on complete charging cycle data, segment of charging data and segment of charging data restored complete data, respectively. The mean and variance of battery capacity changes during the charging process of NASA battery aging experimental data are used as feature inputs of different prediction models, and the prediction results obtained using three methods are compared and analyzed. Results show that the complete charging data features have high prediction accuracy, and the quality of features extracted from segment data is related to the segment collection time. The complete data features can be obtained in a short time through the restoration network, but the prediction accuracy is affected by the restoration network. In addition, the actual prediction needs to take into account the randomness of charging behavior and the real-time performance of prediction results.

The estimation performance of state-of-charge (SOC) of lithium battery plays a vital role in abattery management system. The recursive least squares method with forgetting factor was used to identify the parameters of a battery model. Aimed at the problem that the sampling of a filter in the existing SOC estimation algorithm cannot well simulate the probability distribution of the system state, a rank sampling method was introduced, and an adaptive square root rank filter algorithm was proposed. The covariance matrix of the system state was updated iteratively in the form of square root, and the observation noise was adjusted adaptively according to the innovation in each iteration, so as to improve the SOC estimation accuracy and its adaptive capability with respect to noise. The performance of the proposed algorithm was verified by simulation experiments under FUDS and DST conditions. Results show that the proposed algorithm can improve the convergence speed and estimation accuracy compared with extended Kalman filter, unscented Kalman filter and rank filter.

The use of traditional constant balance coefficient for the state-of-charge (SOC) of batteries cannot reach a compromise between the balancing speed and circulating current. To overcome this limitation, an adaptive balance optimization control strategy for battery SOC is proposed, which is based on modular multilevel converter-battery energy storage system (MMC-BESS). A detailed analysis of the power components within the MMC-BESS bridge arm is given, and the design of an SOC equalization controller based on direct control of battery power on the DC-DC side is optimized. A standard deviation factor based on a constant proportional balance coefficient is introduced, and the interphase-interarm-intraarm cascaded SOC balance algorithm is improved, which can adaptively determine the proportional balance coefficient according to the SOC difference in each module. In addition, a feedforward control quantity is added to the outer power loop of the DC-DC controller, so as to improve the response speed of battery power charging and discharging. The simulation results based on MATLAB/Simulink show that the proposed SOC balance control strategy can reduce the circulating current at the initial stage of balance and shorten the total balance time.

The analysis method based on incremental capacity (IC) achieves effective analysis of the aging mechanism of lithium-ion batteries by converting voltage plateaus into characteristic peaks. However, the immune capability of IC curves with respect to noise is poor, and the extracted health features are susceptible to interference from the noise peaks. To solve this problem, a state-of-health (SOH) estimation method based on noise immunity probability density function (PDF) feature extraction combined with an ensemble learning model is proposed. First, the PDF curve is obtained by calculating the PDF of the voltage curve, and different peak features extracted from the PDF and IC curves are analyzed and compared by setting different values of signal-to-noise ratio. Second, the learning speed and randomness of extreme learning machine are used to construct an ensemble learning model framework, so as to reduce the prediction error of a single model. Finally, SOH estimation experiments under different noise conditions were conducted on the CALCE dataset, and results demonstrated the high accuracy and reliability of the proposed method.

In a new power system characterized by a “dual-high” structure, the virtual synchronous generator (VSG) technology has been widely applied in the grid-forming control of inverters owing to its inherent response capability to inertia and frequency variations. When the grid voltage is unbalanced, the power injected by grid-connected inverters based on the conventional VSG will include second-harmonic fluctuations. To address this issue, a virtual voltage and current regulation strategy under three-phase unbalanced conditions based on VSG is proposed. Through the analysis of the mechanism of inverter power fluctuations and the virtual phase-current regulation (VPCR) method used in grid-following control, it is pointed out that the existing VPCR method cannot solve the power fluctuation problem under grid-forming control. With the combination of grid-forming control characteristics of VSG, a power fluctuation suppression strategy is proposed, which integrates virtual voltage and current regulation on the basis of the existing VPCR method. This approach only requires adjusting the voltage and current gain coefficients, without the need for additional control loops or positive-negative sequence separation, thereby fully preserving the control characteristics and grid-forming attributes of VSG. The proposed method can effectively suppress power fluctuations under voltage imbalance. Experimental results verified the feasibility of the proposed power fluctuation suppression strategy.

The wind-thermal bundled outgoing system may cause sub-synchronous oscillation, while the inherent low-frequency oscillation of the thermal power unit and the interaction between its controller and sub-synchronous oscillation increase the difficulty in stability control. To solve this problem, a small-signal model of the system is established using the modular modeling idea at first, and the leading factors and participation modules of low-frequency and sub-synchronous oscillations are obtained by analyzing the eigenvalues and participation factors of the system oscillation modes, so as to determine the input signal and installation position of the controller. Then, the robust active disturbance rejection control (ADRC) technology is used to perform linearization, and a multi-channel and multi-frequency band doubly-fed wind farm linear ADRC (L-ADRC) additional damping controller is designed. Finally, considering the influence of the low-frequency oscillation additional damping controller on the damping of sub-synchronous frequency band, a coordinated suppression strategy for the multi-channel and multi-frequency band doubly-fed wind-thermal outgoing system based on an improved particle swarm optimization algorithm is put forward, which is verified by time-domain simulations. Results show that the designed control strategy has good suppression effect on low-frequency and sub-synchronous oscillation, and it also has good immunity and robustness.

The short-circuit and phase failure of a DC flexible offshore wind power transmission system at the receiving end will generate excess power, leading to an incremental voltage of DC bus. One of the effective methods to solve this issue is adding DC energy-consuming devices. To reduce the volume and cost of DC energy-consuming devices, a DC energy-consuming device based on a novel submodule and the corresponding hybrid switching control strategy are proposed. The proposed control strategy combines the advantages of step switching control and cyclic switching control schemes, which can effectively reduce the power impact on the system caused by the step change in excess power and simplify the topology of the new submodule. Meanwhile, the problems of operation imbalance and unequal heat dissipation among submodules can be solved. A design method for the parameters of electrical components in the DC energy-consuming device is also given, and a simulation model of the proposed DC energy-consuming device is built. Simulation results verify the effectiveness and feasibility of the topology of the proposed novel DC energy-consuming device and its hybrid switching control strategy.

The series impedance measurement device (SIMD) measures the impedance of a new energy grid-connected inverter by injecting voltage disturbances. However, the rated fundamental current of the inverter under test will flow through the SIMD and thus limit the switching frequency. To address this issue, an SIMD based on resonance shunt is proposed. The proposed topology and control strategy ensure the impedance measurement accuracy in the range of 5 Hz–1 kHz, and achieve a goal that the fundamental current hardly flows through the SIMD and thus the SIMD only bears a small disturbance current. At the same time, an impedance measurement method based on single-phase voltage disturbance injection is adopted to realize the impedance measurement of a three-phase inverter, which improves the device’s energy density and measurement efficiency. Finally, the validity of the proposed topology and control strategy was verified by hardware-in-the-loop experiments.

With the rapid construction of urban rail transit, the problems such as the low utilization rate of regenerative braking energy have become increasingly prominent. The energy storage system is one of the effective ways to solve the utilization problem of regenerative energy in urban rail, and its reasonable control can accelerate its response speed and improve the stability of urban transit systems. First, aimed at the hybrid energy storage systems of urban rail transit, the characteristics of vehicle-mounted and ground-mounted energy storage systems including their safety, flexibility, transmission loss and energy saving efficiency are analyzed. Second, with the combination of the characteristics of energy storage media, four main energy storage approaches (i.e., battery, flywheel, supercapacitor and hybrid energy storage) for the vehicle-mounted and ground-mounted energy storage systems are summarized separately. On this basis, five control strategies for hybrid energy storage systems are elaborated and analyzed from multiple perspectives, such as their control modes and application statuses. Finally, the key technologies of control strategies for urban rail hybrid energy storage systems are summed up, and the development direction in the future is also projected.

The accurate prediction of the futural capacity of lithium batteries is crucial for their health management systems. Aimed at the impact of capacity regeneration on the capacity sequences of lithium-ion batteries, a long short-term memory (LSTM) neural network-based remaining useful life prediction model is proposed, which is based on capacity sequence decomposition and reconstruction. First, the CEEMDAN technology is used to decompose the original sequence into various intrinsic mode components, so as to eliminate the phenomenon of capacity rebound. Second, the Hurst technique is utilized to reassemble each component into multiple systematically strong sub-sequences, which can reduce the time consumption during the testing phase. Third, the whale optimization algorithm is applied to multiple sub-sequences to optimize the parameters of LSTM, and the outcomes from various sets of predictions are further aggregated to derive the ultimate prediction results. Finally, the effectiveness of the proposed model is verified on two sets of lithium-ion battery failure datasets with different degradation characteristics. Experimental results show that the proposed method can maintain both the mean absolute error and root mean square error in certain ranges.

The state-of-charge (SOC) prediction for lithium-ion batteries is an important part of a battery management system, and accurately predicting their SOC is of significance for ensuring their safe operation. On this basis, empirical mode decomposition (EMD), long short-term memory (LSTM) recurrent neural network and Attention mechanism are used to build an SOC prediction model for a lithium-ion battery. The voltage, current, surface temperature and the voltage decomposed by EMD in its charging and discharging processes are taken as the characteristics of the model. The LSTM layer of the model can capture the battery time information from the historical cycle data of the lithium-ion battery, and the long-term dependence relationship is also summarized. The Attention layer of the model can capture the nonlinear and dynamic relationship between feature input and SOC output, so as to optimize the weight relationship between each cycle stage and each feature and further improve the SOC prediction accuracy. Experiments were carried out based on the public battery data set of University of Maryland, and results show that compared with that of a model which only uses LSTM, the average prediction errors of the proposed model under three different working conditions were reduced by 49.36%, 45.61% and 46.93%, respectively.

Capacity and impedance are usually used as direct characteristics to determine the health status of lithium-ion batteries, but they cannot be easily measured in a direct manner. Aimed at the problem of remaining useful life (RUL) prediction for lithium-ion batteries, an indirect prediction method based on expectile regression (ER) is proposed. First, several indirect health indicators which can characterize the performance decline of batteries are extracted from the charging process of batteries, and the correlations with capacity are analyzed using the Pearson and Spearman correlation analysis method. Second, a novel ER-extreme machine learning (ER-ELM) model is developed by combining with ELM. The BFGS quasi-Newton method is introduced to optimize the parameters of the ER-ELM model, and a lithium-ion battery RUL prediction model is established. Finally, the model is verified using the CALCE lithium-ion battery data set. Results show that compared with the standard ELM model, the ER-ELM model has stable output of prediction results, the maximum root mean square error of prediction results is 0.028 9, and all the values of goodness of fit are above 98%, indicating a better performance in terms of tracking capacity decline and regeneration.

To solve the problems in most dual-output wireless power transfer (WPT) systems such as unnecessary cross-coupling, low space utilization and requirement for additional compensation components, the circuit decoupling method was used to establish a constant-current and constant-voltage dual-output WPT system, which can realize load-independent constant-current and constant-voltage output and zero voltage switching with near zero phase angle characteristics. On this basis, a theoretical model of T-shaped decoupling circuit and dual-output WPT system was established, and mathematical theoretical derivation was also conducted to verify the correctness of the proposed system. In addition, the system was simulated and verified, and the simulation results were consistent with the theoretical derivation. Finally, a system magnetic coupler was designed, and an experimental prototype was built, with operating frequency of 85 kHz, constant-current output of 5 A and constant-voltage output of 60 V. Experimental results verified the correctness of the theoretical analysis, and the maximum efficiency of the system can reach 93.4%.

The hybrid power supply technology can effectively integrate the advantages of different power supply units, which is one of the key technologies to realize high power density pulse load power supply systems. Aimed at the problems in the existing aerospace servo pulse load power supply system such as a large capacity and a low power density, a battery-active capacitor pulse load hybrid power supply system and the corresponding optimal capacity configuration technology are proposed. First, the system architecture and operation state are analyzed, and the optimization target and key constraints are established. Second, the capacity of the battery and active capacitor are optimized using an analytical method, and the distribution manner of pulse load power between the battery and active capacitor is established, so as to realize the volume minimization of the power supply system. Finally, an experimental prototype of the pulse load power supply system with a constant power of 2.7 kW and a peak power of 35.0 kW was constructed in the laboratory, and experimental results verified the theoretical analysis.

To solve the problem of common-mode voltage spikes caused by dead-time in the traditional model predictive pulse pattern control algorithms, an improved model predictive pulse pattern control algorithm was proposed. First, the pulse pattern design approach of the traditional model predictive pulse pattern control algorithm was introduced. Then, the influence of dead-time on this algorithm was analyzed, and the pulse pattern was optimized considering the dead-time effect to eliminate the common-mode voltage spikes generated during the dead-time. Finally, the traditional model predictive control based on common-mode voltage suppression, the traditional model predictive pulse pattern control algorithm and the proposed algorithm were experimentally compared. Experimental results show that compared with the traditional model predictive pulse pattern control algorithm, the proposed algorithm effectively suppressed the common-mode voltage amplitude to one-sixth of DC-side voltage without significantly increasing the total harmonic distortion of current ortorque ripple, thereby eliminating the common-mode voltage spikes during the dead-time.

To address the computational burden associated with traditional model predictive control strategies when a permanent magnet synchronous motor (PMSM) is driven by three-level converters, an optimization strategy is proposed. First, a discretized model of the PMSM is developed. Second, the Nelder-Mead algorithm is applied to the selection of optimal voltage vectors for the three-level converter, iteratively seeking the voltage vector that minimizes the current control errors. Finally, the output voltage vector is determined in conjunction with the DC-side capacitor voltage. The proposed optimization strategy involves a maximum of seven current predictions within a control cycle. Experimental validation demonstrates that compared with the traditional model predictive control strategy, the proposed optimization strategy reduced the computation time by approximately 45%, without compromising the steady-state control performance. Moreover, this strategy exhibited excellent DC-side capacitor voltage balancing capability.

Under the indirect vector control, the output torque from an induction motor is easily affected by changes in the rotor time constant. To improve the torque control accuracy of the motor, an online correction algorithm for the rotor time constant is necessary. However, the existing parameter correction algorithms mostly rely on accurate mathematical models of the motor, which are susceptible to model parameter errors and other non-ideal factors, making it difficult to ensure the accuracy of output torque. To address these issues, based on the traditional reactive power-based rotor time constant correction algorithm, the calculation errors of reactive power in actual systems is considered, and a method for calibrating and compensating for reactive power calculation errors is proposed. This method can reduce the output torque error of induction motors from 4% to less than 1%, and its effectiveness was verified by experimental results.

The back electromotive force harmonics of a five-phase permanent magnet synchronous motor (FPPMSM) will significantly reduce the decoupling performance of a-dual-FPPMSM series drive system powered by a single inverter. Meanwhile, the traditional control strategy for the dual-FPPMSM series drive system based on an accurate motor model is too sensitive to changes in motor parameters. To solve these problems, the deadbeat control of decoupling between torque and flux is constructed at first, with flux amplitude and torque angle as the intermediate variables. Then, the speed ring active disturbance rejection control is established to generate the preset motor fundamental wave torque, based on which the torque ring active disturbance rejection control is constructed to generate the torque angle increment. Experimental results show that the proposed control strategy is insensitive to changes in motor parameters, and the decoupling performance between two motors is better.

The discontinuous pulse width modulation (DPWM) method can effectively reduce the switching loss and improve the system efficiency. However, it will also bring in high-order common-mode voltage, which results in an decline in the quality of grid current and an increase in the common-mode current (CMC). To solve this problem, a novel DPWM method is proposed, which can reduce the content of common-mode voltage in the modulation wave by injecting third-order sinusoidal signals into the wave under the traditional DPWM1 modulation at the clamping stage. A common-mode loop model of a photovoltaic inverter system is established, and the reason of the increasing CMC under the DPWM modulation is theoretically explained. The theoretical analysis and experimental results show that the proposed novel DPWM method can improve the efficiency of the photovoltaic inverter system while ensuring that the THDi and CMC are similar to those under the SVPWM modulation. As a result, good current quality and high efficiency are maintained simultaneously.

The sorting voltage equalization algorithm is often used as a submodule capacitor voltage control strategy for a modular multilevel converter (MMC), which poses a challenge in locating the open-circuit fault of an upper switch in a half-bridge submodule. To solve this problem, a method for locating the insulated gate bipolar transistor (IGBT) open-circuit fault in the submodule of MMC based on reconstructed subunit voltage is proposed. The voltage circuit equation of a three-phase MMC is established, and the influence of current flow path on the capacitor voltage and the reasons for abnormal output current and bridge arm circulating current are analyzed when an open-circuit fault for a single-switch occurs in the half-bridge submodule. An adaptive state observer based on extended Kalman filter (EKF) is used to achieve the optimal estimation of output current and bridge arm circulating current, and fault diagnosis is performed using the residuals between the optimal estimation value and the actual sampling value. Subsequently, the submodules with the same position as the faulty bridge arm in the three-phase system are grouped and reconstructed, so as to obtain the reconstructed subunits. The adaptive state observer based on EKF is utilized to estimate the reconstructed subunit voltage, and the difference between the estimated value and the actual average voltage of the corresponding reconstructed subunit is compared with a preset threshold, thus achieving the fault localization. Four typical IGBT open-circuit fault conditions of submodules were selected for experimental verification, and experimental results show that the proposed fault diagnosis and localization method is correct and feasible.

To improve the reliability of a grid-connected converter under operation, an open-circuit fault diagnosis and fault-tolerant control strategy is proposed for a T-type three-level grid-connected converter. After an open-circuit fault occurs in a power device, through the analysis of the operating state of the converter, the changing relationship between the converter output current and the currents flowing from the midpoint of the DC-side capacitor to each phase is elucidated. The average value of the converter output current and that of the currents flowing from the midpoint of the DC-side capacitor to each phase are calculated, and these values are compared with the preset diagnostic thresholds to locate the faulty power device. According to their locations, the faults are categorized into Class-I (vertical bridge arm fault) and Class-II (horizontal bridge arm fault). The corresponding fault-tolerant structures are designed for the two types of faults, and a fault diagnosis and model predictive fault-tolerant control strategy is proposed for the T-type three-level grid-connected converter. Experimental results verify that the proposed method can quickly locate the position of the faulty power device of the converter, realize fault-tolerant continuous operation and improve the reliability of the converter.