The islanded microgrid adopts droop control to make inverters share load power according to the capacity proportion of distributed generation (DG), so as to prevent the DG from overload, light load, or generating power circulation. However, the power sharing effect of inverters is related to both the line impedance and the changes in the actual capacity of DG. To solve this problem, an improved droop control strategy considering the randomly changing output from DG is proposed. This strategy adopts two-layer control, in which the outer-layer control eliminates the influence of line impedance in a rated working state. Under changes in the operation condition, the proportion of changed capacity of DG is obtained according to the changes in the voltage of DC bus in a two-stage inverter, and the reference values of power and voltage in a non-rated working state are formulated. In the inner-layer, an improved droop control is adopted to adjust the coefficient of droop control to make the inverters work under the reference value of voltage. Finally, the output from inverters is adjusted to ensure power balance. Simulation results verify the correctness and feasibility of the proposed strategy.

The three-level T-type shunt active power filter (3LT²SAPF) has been widely used to improve the power quality of power grid under nonlinear load, and its harmonic suppression and reactive power compensation performance and the corresponding reliability have attracted wide attention. Meanwhile, model predictive control (MPC) can achieve multi-objective optimization. However, once the parameter mismatch occurs due to reasons such as changes in temperature, the output performance of an MPC system will be seriously deteriorated. This may even may endanger the system stability. Additionally, when the circuit relation is unknown, the establishment of a predictive model is not available, and the MPC controller will not be applicable. To solve these problems and enhance the robustness of the 3LT²SAPF system, a linear fitting sequential model-free predictive control method was proposed. First, the principle of linear fitting method for current prediction was analyzed. Second, a current error matrix for each switching vector was established, which can be used for harmonic current tracking. Finally, the cost functions for neutral-point (NP) voltage and DC-bus voltage were designed. The results of numerous experiments under different scenarios verified the correctness and effectiveness of the proposed method.

By combing the multi-level technology with the cascade modular technology, the T-cascade modular multilevel converter (TMMC) has characteristics such as 9-level port voltage, redundant switching mode, multiple power ports and hardware multiplexing, and it has become one of the ideal topologies for realizing uninterruptible power supply (UPS) with high power density and high efficiency. However, the large number of DC-link capacitors which are susceptible to failures poses a threat to the reliable operation of TMMC-UPS. Therefore, it is necessary to monitor DC-link capacitors under the scenario of TMMC-UPS to intelligently perceive the changes in the capacitance value and prevent the degradation failure of capacitors, so as to ensure the reliability of UPS. Therefore, a double-scale convolutional neural network model is proposed. By extracting the low- and medium-frequency features of capacitor voltage ripple, both the capacitance value and the equivalent series resistance can be identified, thus improving the monitoring accuracy of capacitor status. The proposed data-driven method does not rely on any mathematical model, and it does not need to add additional measurement hardware either, so it can be easily extended to the parameter identification field of other types of converters.

In a magnetic coupling wireless charging system, the transmission coil is an important part for improving the efficient transmission of electric energy, and its figure of merit directly affects the efficiency of the whole system. To meet the demand of high-efficiency transmission, first, an equivalent circuit model for an S-S compensation topological system was established, and the relationship between the coil’s transmission efficiency and figure of merit was obtained through theoretical derivation, i.e., maximizing the ratio of the coil’s mutual inductance to its internal resistance can achieve high-efficiency transmission. Then, aimed the mutual inductance and internal resistance which were also the main optimization objectives for coil design, the relationship among the coil’s mutual inductance, internal resistance and geometric parameters was deduced theoretically, and it was further refined into a multi-parameter optimal function problem with constraints between the coil’s efficiency and its parameters. Finally, an iterative solution based on the particle swarm optimization algorithm was proposed, and the winding coils with different specifications were made according to the obtained geometric parameters, so as to test the optimization results.

In response to the challenges posed by fluctuating load power and reduced efficiency due to variations in the angle and position of a receiving coil, a parity time (PT) symmetric spatial wireless power transfer system based on coil switching is proposed. First, the mathematical model of a cubic structure is established, which is endowed with double-layer space spiral coils on all of its six sides. Simulation results verify that under the condition of equivalent turns and radius, the double-layer coil exhibits a larger inductance and a better coupling performance than the single-layer space spiral coil, and the corresponding design is more compact. Second, the operating frequency and transmission characteristics of SS compensation throughout the whole coupling region are derived. Given the frequency splitting phenomenon existing in the PT symmetric region, a primary-side frequency detection coil switching strategy is put forward to enable adaptive switching in different power supply regions. Finally, experimental validation was carried out, and results show that under specific frequency conditions in a three-dimensional space, the receiving coil can consistently maintain a stable power output of 18 W and an efficiency exceeding 80%, with power fluctuations remaining within 6.7%, thereby validating the effectiveness of the proposed strategy.

Due to the magnetic saturation effect, there is a difference between the apparent inductance and incremental inductance of a permanent magnet synchronous motor (PMSM), resulting in a deviation in the description of the motor model. With the consideration of the influence of magnetic saturation effect, a new PMSM model is established in this paper by introducing apparent inductance and incremental inductance, and the model parameters are further identified by the particle swarm optimization (PSO) algorithm. To solve the problem that the PSO algorithm is easy to fall into local optimum and its convergence speed is slow, an adaptive particle swarm optimization (APSO) algorithm combined with reverse learning is proposed. To overcome the influence of inverter nonlinearity on the identification results, the error voltage caused by inverter nonlinearity is taken as a new parameter to be identified, and it is identified online. Experimental results verified the accuracy of the APSO algorithm when it was used in identifying the d- and q-axis apparent inductance, d- and q-axis incremental inductance, permanent magnet flux linkage and inverter nonlinearity error voltage of PMSM.

Permanent magnet synchronous motors (PMSMs) have been widely applied in the field of industrial electric vehicles owing to their advantages of high power density, high reliability and easy maintenance. Compared with the PMSM equipped with a high-precision encoder and a speed sensorless algorithm, the PMSM equipped with Hall sensors can guarantee the system’s low cost, as well as its control performance. However, the output information about the position and velocity from low-resolution Hall sensors is of low accuracy when using the vector control method, resulting in motor current ripple and electromagnetic torque pulsation. Therefore, a fusion speed estimation method is proposed, in which the least squares method independent of motor parameters is used to output a continuous smooth angle, and a sliding mode observer based on the motor’s mechanical motion equation is designed to estimate the speed in real time. The motor is started by square wave to solve the problem of missing discrete position, and the designed observer is also proved by the Lyapunov stability method. Finally, experimental results verify the correctness and feasibility of the proposed speed estimation method.

To address the issue of uneven thermal stress distribution in power devices under in-phase disposition PWM (IPD-PWM), an improved carrier disposition PWM strategy is proposed. Aimed at enhancing the reliability of converter systems, this strategy leverages the concept of carrier reconstruction by optimizing the dynamic distribution ranges of modulation waves and carriers. With a focus on balancing the switching losses among submodules, the mechanism by which the modulation wave range influences switching losses at varying modulation ratios is analyzed in depth. The results of Matlab-PLECS co-simulation thermal modeling and experiments on a seven-level converter platform verify that the improved strategy achieves balanced thermal stress distribution in power devices while maintaining output harmonic characteristics identical to those under the traditional IPD-PWM. Consequently, the overall lifetime of the converter is significantly extended.

As a category of power electronic transformers, DC transformers have demonstrated excellent application prospects. However, the weight and cost of traditional magnetic-core isolation transformers directly constrain the development and applications of DC transformers. Consequently, coreless DC transformers employing lightweight and low-cost coreless isolation transformers have emerged as a new research direction. First, the characteristics of coreless transformers and their functions within DC transformers are systematically reviewed. Second, the technical configurations of coreless DC transformers are analyzed, categorizing them into linear and sinusoidal types. Final, the technical characteristics of three sinusoidal coreless DC transformer variants (i.e., self-inductance resonant, leakage inductance resonant and PT-symmetrical) are examined, and a comparative study of their performance is also conducted.

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.