The traditional nearest level modulation (NLM) has advantages of simple control and low switching frequency. However, when the number of output levels is small, the harmonic distortion rate of output waveform from a modular multilevel converter(MMC) under the NLM modulation will be large. In this paper, a full-bridge auxiliary sub-module is added to each arm of the traditional three-phase six-leg MMC topology, and the capacitance voltage of the auxiliary sub-module is half of that of the half-bridge sub-module. Aimed at this MMC topology, an improved hybrid modulation strategy is proposed, which can realize the balance control of half-bridge and auxiliary sub-module, reduce the harmonic distortion rate of MMC AC-side output current, and reduce the switching frequency and system loss of the full-bridge sub-module. A detailed simulation model is built in MATLAB/Simulink, and simulation results verify the effectiveness of the proposed MMC topology and the improved hybrid modulation strategy.

A modeling data and optimization algorithm driven electrothermal behavior model of gallium nitride high electron mobility transistor (GaN HEMT) is proposed to facilitate the quantitative analysis of problems caused by high speed switching, such as turn-on overvoltage, false turn-on, oscillation and EMI noise. Compared with the traditional behavior models of GaN HEMT, the proposed model can precisely depict the electrothermal characteristics of GaN HEMT in a wide temperature range in both the first and third quadrants by only two compact equations. Meanwhile, the nonlinear parasitic capacitances of GaN HEMT can be accurately modeled by one compact equation. In addition, an optimization algorithm combing the genetic algorithm and Levenberg-Marquardt algorithm is put forward, and a one-step extraction of modeling parameters is realized based on this optimization algorithm and modeling data, which can reduce the modeling time and work load to a certain degree. Results show that the proposed modeling method can precisely model multiple types of GaN HEMT devices manufactured by different companies. Finally, the correctness and effectiveness of the proposed modeling method was verified by the well-matched simulated dynamic waveforms and experimental measurement data.

The HT-6M Tokamak Reconstruction is an international project of cooperation between China and Thailand for responding to the Belt and Road Initiative. The function of pulse power supply for heating field is to breakdown and produce plasma, and the corresponding power supply scheme adopts the form of capacitor energy storage pulse discharge. To calculate the parameters of power supply that meet the requirements, the discharging process of pulse power supply for heating field is analyzed mathematically, and the core devices are designed and developed according to working parameters of power supply equipment. To verify the theoretical analysis of discharging process, a set of small capacitor energy storage pulse power supply was developed. At the same time, a turn-off experiment on a high-power solid-state circuit breaker was carried out.

Silicon carbide (SiC) is a promising wide-bandgap semiconductor material owing to its excellent electrical and thermal characteristics. Power metal-oxide-semiconductor field-effect transistors (MOSFETs) based on SiC are suitable for high-power fields, and their high-temperature gate oxide reliability is one of the most concerned characteristics. In this paper, the high-temperature gate oxide reliability of self-developed SiC MOSFETs is compared with that of the foreign SiC MOSFETs of the same specification by positive and negative high-temperature gate bias (HTGB) tests. The negative HTGB test results show that the deviation of threshold voltage of self-developed SiC MOSFETs is almost equal to that of the foreign SiC MOSFETs, and the maximum discrepancy between them is about 4.52%. However, the positive HTGB test results show that the deviation of threshold voltage of self-developed SiC MOSFETs is smaller than that of the foreign SiC MOSFETs, with a maximum discrepancy of 11%. The reason for the better performance of self-developed devices is that an appropriate amount of nitrogen is added to the SiC/SiO2 interface, which can passivate interface defects and reduce the generation of fast interface states, so that the total interface state density is minimized.

In view of the fact that the existing methods cannot identify all the effective power supply paths for voltage over-limit, which leads to problems of poor real-time performance and unobvious suppression effect in the voltage over-limit identification in distribution network, the voltage over-limit identification in distribution network with photovoltaic (PV) power supply is studied based on a regulation function, so as to improve the corresponding real-time performance and effectiveness. First, an external characteristic model of PV power supply is constructed by using its physical mechanism, based on which a simulation model of PV power supply is built in the Matlab/Simulink software. According to the power relationship in distribution network with PV power supply, the voltage variation at the grid-connected point before and after the integration of PV power supply is calculated, and the mechanism of voltage over-limit is analyzed, so as to design the equivalent circuit of distribution network with PV power supply. All the effective power supply paths for voltage over-limit are specified, a candidate set of voltage over-limit regulation strategies for distribution network with PV power supply is set up in an decreasing order by means of the regulation function, and the candidate strategies are selected from the candidate set of regulation strategies to realize the voltage over-limit identification. The analysis results of an example show that the proposed method can effectively adjust the voltage of distribution network with PV power supply to a normal state with less iteration times and a short execution time, indicating a high practicability.

To accurately obtain the on-orbit health status of a spacecraft electrical power system, a condition quantitative assessment model for a satellite electrical power system with the fuzzy theory is proposed. First, an index system for evaluating the system condition is established by analyzing the operating characteristics of one satellite electrical power system. Combined with the time-varying characteristics of actual telemetry, the corresponding telemetry pre-processing method for electrical power system and a dimensionless deterioration function are put forward. Then, a hierarchical condition quantitative assessment method for the satellite electrical power system is established through introducing the variable weight theory and fuzzy theory. Finally, the correctness and effectiveness of the proposed condition quantitative assessment method are verified by analyzing the actual on-orbit and simulation data of the satellite and comparing with the traditional method. Moreover, the deteriorated system condition can be assessed by the proposed method two days earlier only based on thresholds.

Aimed at the problems of fast loss and high capacity configuration of battery energy storage equipment in microgrid, an optimal configuration model of battery energy storage capacity of microgrid considering life loss is established in this paper. In addition, a cost calculation method for the battery energy storage life loss based on fixed daily cycle times is also proposed. This method combines the piecewise linearization idea and the scenario analysis method, and it can effectively extend the lifetime by optimizing the discharging depth and daily cycle times of battery energy storage. Moreover, considering the uncertainties in wind power output and load power, a two-stage robust optimization model is introduced, which is further solved by the column-and-constraint generation algorithm. Finally, the effectiveness of the novel model under different uncertainties and different unit prices of battery energy storage is verified by numerical examples.

Aimed at the problem that the failure of electronic components or power off in the current control unit of a short-circuit current protection device will lead to a protection failure, a passive electromagnetic current transformer is proposed. The working principle for the trigger device is analyzed, and the maximum magnetic flux of iron core within the effective working range of the transformer is determined according to the magnetization curve of the core material. Considering that the magnetic flux in the iron core is easily saturated at a large current, simulations are performed to analyze the influence of air gap distribution on magnetic flux intensity in the transformer. An electromagnetic current transformer core structure is designed, which can still effectively work at the 15 kA short-circuit current peak. The 3D transient electromagnetic simulations show that when the short-current rising rate is 20 A/µs and the number of turns in the secondary winding is 30, the output voltage from the secondary winding is not less than 14 V. Finally, an engineering prototype of hybrid current-limiting fuse with a passive electromagnetic current transformer as its trigger device was made, and a short-circuit current detection test was carried out. The experimental results basically agreed with simulations, indicating the accuracy and validity of the design of iron core.

As the number of charge and discharge cycles of a lithium-ion battery increases, its state-of-health (SOH) will degrade to some degree accordingly. Aimed at this problem, a method for estimating the SOH of lithium-ion battery based on an improved multi-objective Cuckoo search (IMOCS)-BP neural network is designed, which adaptively changes the update probability and search step size of the Cuckoo search (CS) algorithm while avoiding the algorithm from falling into the local optimum, thereby solving the problems of slow convergence speed and low solution accuracy in the CS algorithm. The IMOCS algorithm is combined with BP neural network to conduct a global search in the node space, reduce the influence of initial values of weight and threshold on BP neural network, and realize the parameter optimization. Through Matlab simulations, it is verified that the SOH estimation algorithm based on IMOCS-BP neural network has a low error and a strong performance, thus realizing an accurate SOH prediction of lithium-ion battery.

A Super-Boost converter can greatly reduce the mass and volume of power supply and improve the corresponding power density by replacing the traditional charging and discharging module, so it has a broad application prospect in space power system. However, due to the existence of multiple power components and the reverse flow characteristics of inductance current, its power supply mode and output ripple voltage are more complex than those of the traditional Boost converter. To provide a theoretical guidance for the analysis and design of the Super-Boost converter, its power supply mode and output ripple voltage are studied. It is found that there exists continuous conduction mode, pseudo continuous conduction mode and pseudo discontinuous conduction mode in both inductor L₁ and L2. The analytical mathematical models of critical inductance and output ripple voltage in each operation mode are established, the relationship between peak current and inductance is discussed, and the minimum capacitance and minimum inductance that meet the design requirements are obtained. On this basis, a design method for the converter parameters is given, and experimental results verify the theoretical analysis.