With the remarkable growth of renewables, distributed power generation systems (DPGSs) are starting to take over the dominant role of synchronous machines. As an essential interface between renewables and power grids, the grid-connected inverter plays an important role in the safe and stable operation of DPGSs. Among two types of grid-connected inverters, i.e., grid-following (GFL) and grid-forming (GFM) ones, attention has gradually turned to the GFM inverter in recent decades, owing to its synchronous-machine-like characteristics and capability of operating in weak grid or even forming a stand-alone grid. However, similar to the GFL inverter, the GFM inverter may exhibit non-passive characteristics in the mid/high-frequency bands, leading to mid/high-frequency resonance risk.

The existing research mainly focuses on sub-synchronous oscillation, but the mid/high-frequency resonance issue still needs to be explored. In order to mitigate the mid/high-frequency resonance and harvest the desired performance, this paper provides the optimal design procedure for controller parameters from the perspective of internal stability and the impedance reshaping method via the grid current feedforward from the perspective of external stability.

Firstly, a mathematical model of the voltage-current double-loop controlled GFM inverter is established. The control block diagram of the inverter’s control system is depicted, and its equivalent transformation is performed. Accordingly, the impedance model of the GFM inverter is obtained as a controlled source in series with the output impedance.

After that, the stability of the GFM inverter is divided into internal stability and external stability, which characterize the stability of the equivalent voltage source and the interaction stability between the equivalent impedance and the grid, respectively. From these two stability dimensions, the stability mechanism and resonance risk of the GFM inverter are analyzed based on the Nyquist stability criterion and the passivity theory, and the main factors affecting the system stability are revealed.

According to the internal stability constraints, stability margin requirements, and steady-state error, an optimal design procedure for the control parameters is provided, which avoids repeated trials and ensures internal stability and low steady-state error. Additionally, based on the external stability constraints, the impedance shaping scheme with the grid current feedforward is proposed, and the corresponding feedforward function is derived. The proposed scheme is simple to implement and can effectively enhance the inverter's robustness against grid impedance variations.

Finally, experiments are carried out on a 10 kW GFM inverter prototype. The results confirm that under different grid conditions, the inverter can with the designed parameters and the proposed scheme continuously operate stably, and the power quality is high, which verifies the theoretical analyses and the proposed scheme.

The magnetic lift control rod drive mechanism (CRDM) is a critical electromagnetic actuator for regulating nuclear reaction rates. Its dynamic process is complex to predict due to the cross-coupling among current response, magnetic circuit saturation, and motion state. The latest equivalent magnetic network (EMN) model exhibits inaccuracies and relies on flux distribution during modeling, lacking generality. In multi-field coupling analysis, researchers often employ multi-software collaborative or semi-simulation methods, which incur significant time and hardware costs. This paper proposes a dynamic equivalent magnetic network (DEMN) model and a multi-physics field coupling calculation method considering transient current changes and saturation.

Firstly, the structure of the magnetic lift CRDM is introduced, and its lift solenoid valve is selected to analyze the electromagnetism-mechanics coupling during dynamic processes. Then, the mechanism is partitioned using orthogonal grid lines, and mesh units of multiple media are consolidated into a single medium to unify the reluctance calculation formula. During dynamic changes, only the grid size or position in the motion region is altered, thereby eliminating redundant modeling and reducing computational errors caused by mesh discrepancies. A connection relationship and calculation method for branch reluctance are established to address the misalignment between fixed and moving mesh units, facilitating continuous armature movement. A multi-physics field coupling calculation method is proposed by combining circuit models and kinematic formulas, which consider transient current changes and saturation. Finally, Compared with 3D finite element analysis (FEA) and experiments, the DEMN model and the proposed multi-field coupling calculation method are verified.

3D FEA results show that the magnetic density distribution, inductance, and electromagnetic force are highly consistent with the DEMN results, where the maximum error of inductance is 5.7%, and the maximum error of electromagnetic force is 3.4%. The experiments show that linear and saturated inductance variations are similar. The calculation accuracy of the release and suction currents under various loads exceeds 91%. Additionally, the dynamic results closely align with experimental results, with motion time calculation errors at 28 A and 40 A currents of 0.99% and 2.99%, respectively.

The conclusion is as follows. (1) By using orthogonal grid lines, the unified calculation of reluctance is achieved, accelerating the modeling speed. (2) By changing the grid size or position of local areas, the dynamic changes of the EMN model are achieved, avoiding the problem of repeated modeling in the multi-field coupling calculation process and reducing the calculation errors caused by differences in mesh partitioning. (3) Compared with FEA, the proposed DEMN model requires less computational resources and shorter computation time while ensuring accuracy. Compared with the experimental results, the effectiveness and accuracy of the DEMN model and multi-field coupling calculation method are verified. It can be extended to EMN modeling, performance analysis, and rapid optimization design of the entire CRDM.

In non-destructive testing (NDT), there is a growing demand for simulation tools that can predict magnetic characteristics, enhance understanding, and avoid harsh and uncertain experimental expectations. Due to the high sensitivity and non-destructive nature, the measurement and simulation of magnetic barkhausen noise (MBN) have become important in NDT.

This paper measured the MBN signals of soft magnetic materials under different stress conditions at a magnetic frequency of 10 Hz. The experimental results revealed the significant impact of tensile and compressive stresses on the MBN signals. Specifically, as tensile stress increases, the spacing between magnetic domain walls decreases, reducing energy loss in the movement of domain walls. The migration rate of the domain walls is accordingly increased, which in turn causes the MBN signals to rise. At the same time, due to the presence of additional domains in oriented silicon steel, the MBN signals exhibit a double-peak structure. As tensile stress increases, these additional domains are suppressed. Hence, peak-to-peak values one and two increase, and the increase in peak value two is significant. When a magnetic field and compressive stress are applied along the rolling direction, the compressive stress increases the energy of the magnetic domain walls, reducing their migration rate and weakening the MBN signals. Ithelpsto better understand the changes in the magnetic properties of soft magnetic materials under different stress conditions.

Existing MBN models can not accurately simulate the MBN signals of different soft magnetic materials under stress. This paper proposes a mathematical model based on the improved S-J-A hysteresis model. This model simulates MBN signals by considering the irreversible motion of magnetic domain walls in soft magnetic materials, thereby increasing the accuracy of the simulation. Specifically, the improved S-J-A hysteresis modelsimulates the irreversible hysteresis loops of soft magnetic materials, considering the relationship between magnetic anisotropy, model parameters, and stress. Then, these irreversible hysteresis loops are linked with the MBN envelope line to establish a mathematical model for the MBN envelope curve. Next, the MBN signals are simulated by modulating white noise in the 1~50 kHz range with this envelope curve. Finally, three different soft magnetic materials are selected: oriented electrical steel sheet (30QG120), non-oriented silicon steel (35WW230), and amorphous alloy (1K101). The proposed MBN model simulates MBN signals under different mechanical stress conditions.

The proposed MBN model accurately simulates the MBN signals of the oriented electrical steel sheet (30QG120), non-oriented silicon steel (35WW230), and amorphous alloy (1K101) under stress. A comparison of MBN signals between oriented silicon steel, non-oriented silicon steel, and amorphous alloy is conducted, revealing that the double-peak structure exhibited by oriented silicon steel under tensile stress is related to its anisotropy. Microscopic analysis gains a deep understanding of the stress effects on the magnetism of soft magnetic materials and the generation mechanism of MBN. The proposed MBN model provides a reliable tool in material characterization and non-destructive testing (NDT) applications, laying the foundation for further engineering applications.

The dynamic transformer rating (DTR) and thermal life loss of oil-immersed transformers under on-site variable load operation conditions are closely related to the transient temperature rise of the equipment. However, as an implicit solution method, the traditional finite element analysis and finite volume method need to be iteratively solved in each sub-step of transient thermal analysis, which has many computational resources and is time consuming. It is challenging to meet the requirements of fast calculation. The rapid and accurate solution of the temperature field (especially the hot spot temperature rise) of the oil-immersed transformer in field operation is the premise to realize the digital operation and maintenance of the transformer and the DTR evaluation. Therefore, this paper proposes a lattice Boltzmann (LBM) physical in the loop simulation model for coupled electrical networks. The real time evaluation of DTR under electrical network constraints is realized through the rapid solution of the transformer temperature field.

Firstly, the D2Q9 model is used to solve the fluid flow and thermal lattice Boltzmann equations (LBEs) to capture the transient oil flow and temperature rise process inside the transformer. In the Simulink environment, the equivalent current source model is used to construct the electrical network constraints of multi-level load scenarios, and the established transformer LBM model is used as a component for numerical encapsulation to complete the construction of the physical-in-the-loop simulation model. Secondly, to verify the effectiveness of the proposed method, the finite volume method (FVM) is used to simulate the same oil-immersed transformer model. The grid independence test determines the optimal number of grids. The number of grids is 1 250×420 for LBM modeling and simulation, and the number of units is 43 654 for FVM meshing. Compared with the constructed LBM-Simulink model with the FVM model, LBM still has the advantages of speed and memory occupation when the number of lattices is higher than the number of FVM units. If commercial software is used, this advantage will be further expanded. Thirdly, the steady state solution results of the hot spot temperature rise of the established LBM model are compared with the FVM solution, and the error is 2.60%. According to the load curve given in the transformer guidelines, it is used as input to solve the transient temperature rise of the established LBM and FVM simulation models. Finally, the results show that the LBM and FVM calculations are better than the transformer guide calculation. The maximum error between the hot spot temperature calculated by LBM and FVM is 6.44%. Moreover, the hot spot temperature rise trend of LBM is consistent with the transformer load guidelines, which verifies the effectiveness of the proposed method.

Based on the constructed LBM model, the load capacity of oil-immersed transformers under constant 25℃ and typical ambient temperature changes in summer and winter are evaluated at 6~18 hours during the day. The results show that under the premise that the relative insulation life loss of oil-immersed transformers is less than 1. The maximum load capacity coefficients are 1.20, 1.10, and 1.60 under the constant ambient temperature of 25℃, typical temperature changes in summer, and typical temperature changes in winter. The simulation model based on the proposed LBM provides an effective method for real-time monitoring of temperature rise, load capacity evaluation, and dynamic capacity increase of oil-immersed transformers.

The rapidly developing field of artificial intelligence (AI) has made significant advancements in areas such as image processing, language, decision-making, and diagnostics, providing new methods for solving complex problems. The increasing intelligence of electrical equipment, combined with the coupling of strong and weak electrical fields, has led to the emergence of multi-scale, multi-physical field coupling and nonlinear problems in electromagnetic fields. High-precision numerical modeling and optimization are increasingly challenging.

Therefore, this paper combines recent research outcomes from the author’s team to introduce deep learning methods for solving typical interdisciplinary problems, such as data-driven modeling, physics-driven PDE solving, and knowledge-embedding modeling. In particular, the paper discusses the current state of intelligent modeling for complex electromagnetic field problems driven by both data and knowledge. It also offers perspectives on the scientific challenges and important future directions in the research and engineering implementation of electromagnetic field intelligent modeling.

In the area of data-driven modeling, the paper explores its application in the performance analysis and optimization of electrical equipment. The discussion is divided into three parts: performance parameter calculation, electromagnetic thermal field prediction, and knowledge discovery modeling. By combining numerical simulation and experimental data, deep learning algorithms can mine potential knowledge from the data, enabling rapid computation of one-dimensional performance and two- and three-dimensional fields. This approach allows for real-time simulation of local performance, global performance, and micro characteristics.

Regarding physics-driven partial differential equation (PDE) solving, the paper discusses two main research directions: knowledge-embedding regularization methods and designing machine learning model structures based on physical meaning. Constructing loss functions or network structures that align with physical laws makesit possible to solve PDEs without relying on sample data. This method is beneficial when physical conditions are incomplete and sample data is scarce. Using AI to solve physical equations helps overcome traditional bottlenecks, improving computational efficiency and expanding application scope.

In the area of knowledge-embedding modeling, the paper discusses how to implicitly integrate domain knowledge, mainly through multi-fidelity models and neural network operator methods, to improve the precision and efficiency of computational models. By embedding the knowledge inherent in high-precision samples into the model, high-precision forward and inverse problem models can be built. As data accumulates, the model's accuracy and generalization ability will improve. This method fully utilizes the advantages of deep learning and integrates basic physical theories. As data grows, knowledge-embedding methods are expected to be crucial in solving more complex electromagnetic field problems and enhancing overall simulation outcomes.

In conclusion, the fusion of AI and knowledge has become a significant trend in the development of numerical simulation. Integrating data-driven, physics-driven, and knowledge-embedding methods has accelerated the advancement of electromagnetic field modeling and optimization. These methods have improved simulation accuracy and expanded the application range of numerical simulations for complex electromagnetic field problems. However, the exploration of AI in numerical simulation is still in its early stages, facing challenges such as insufficient model generalization, computational efficiency improvement, and physical constraint integration. Future research should focus on addressing these issues to promote the broader application and development of AI in the field of electromagnetic field numerical simulation.

As the power source of the robotic manipulators, the motors inside the joint servo systems generally start with a load directly and cannot execute position calibration due to the operating conditions. Therefore, the commonly used position acquisition scheme is the Hall position sensor during motor start-up. However, this scheme cannot start the motor with the maximum starting torque, as the Hall position sensor only provides the present sector of the motor rather than the precise angle. The traditional processing method utilizes a square-wave voltage to start up or take the middle value of the Hall sector as the angle input to the motor drive algorithm, thereby obtaining a large torque across the entire angle range of the Hall sector. These methods are simple but lose some torque in the event of a significant deviation in the position estimation.

This paper proposes a quick-startup method for surface-mounted permanent magnet synchronous motors (SPMSMs) based on a Hall position sensor. Firstly, the start-up process of different curves of random initial angles is analyzed. The deviation between the actual rotor position and the imprecise estimated position decreases the starting torque, as the Hall sector spans an angle range of 60°. Under these conditions, combined with the field-oriented control (FOC) algorithm and the maximum torque per ampere (MTPA) strategy, the quick start-up method is proposed, and the critical start-up curve parameters are numerically calculated. Although the initial and precise angles during the start-up process are not available, the proposed curve can be close to the average locus to a great extent.

The simulation and an experiment are conducted using an actual servo motor under different initial angles. The results show that when the initial rotor position is close to the minimum angle of the Hall sector, the proposed method exhibits a pronounced acceleration effect. Due to the short stroke, although the position tracking of the proposed method is slightly behind the traditional method, the time difference is negligible when the initial position approaches the maximum angle. Combined with the average start-up time of the entire initial angle in the Hall sector, the proposed method can effectively reduce the average start-up time.

A quick start-up method for SPMSM based on a Hall position sensor is proposed. In the conventional control method, the maximum starting torque and the minimum statistical value of the start-up time cannot be achieved over the entire range of initial angles. Therefore, the novel position curve is designed to improve the start-up time for small initial angles in each Hall sector while considering the start-up process at other angles. Statistical analysis has demonstrated a significant reduction in the start-up time expectation of the entire initial rotor positions. The method optimizes the torque reduction problem during the start-up process, which is caused by imprecise positioning in the first Hall sector. Moreover, the ease of transplantation allows the method to be applied to various motor drive algorithms.

Due to the advantages of high power level, small torque ripple, and strong reliability, dual three-phase permanent magnet synchronous motors (DTP-PMSM) have been widely used in electric vehicles, ship propulsion, and aerospace power systems. The high fault-tolerant capability for open-phase faults is an important application feature of DTP-PMSM. Developing fault-tolerant control strategies is crucial for improving fault-tolerant performance. While both the minimum loss (ML) and maximum torque (MT) control strategies offer their advantages, stator copper loss and torque output capacity cannot be simultaneously considered. The full range minimum loss (FRML) control strategy comprehensively considers both ML and MT optimization objectives. The stator copper loss is effectively reduced without sacrificing the output torque range. Currently, the FRML control strategies usually add the restriction of sinusoidal current mode. However, the restriction of the sinusoidal current mode narrows the solution space of the current reference and prevents further improvement of the fault-tolerant performance. Therefore, a FRML control strategy based on harmonic current injection is proposed.

Firstly, considering the control complexity and optimization effect, third harmonics are injected into the fault-tolerant phase current to expand the solution space. By optimizing the current references, the fault-tolerant performance of ML and MT control strategies is further improved. Secondly, considering the stator copper loss and torque output capacity holistically, an allocation coefficient is introduced to combine the ML and MT strategies nonlinearly. The fault-tolerant trajectory can be smoothly switched online by adjusting the allocation coefficient under various load conditions. The proposed FRML control strategy simplifies the implementation complexity and produces a unified expression of current reference, which effectively reduces stator copper loss over the torque range. Finally, the proposed control strategy is verified on a surface-mounted DTP-PMSM platform. The quasi-proportional resonance controllers ensure accuracy in tracking the AC current reference. Both ML and MT control strategies achieve smaller stator copper loss and larger torque output capacity after the third harmonic injection than the sinusoidal current mode. When the FRML control strategy based on harmonic current injection is applied, the allocation coefficient is modified in real-time with the change of load condition. Under the rated load of 65.5%, 67.7%, and 69.7%, the stator copper loss is lowered by 6.2%, 4.91%, and 3.1%, respectively, compared to the MT control strategy. The fault-tolerant control strategy is verified.

The following conclusions can be drawn. (1) The strategies with the injection of third harmonic exhibit the superior performance of copper losses and torque output capability than that with sinusoidal current mode thanks to the more thorough current optimization. Therefore, the fault-tolerant control strategy based on third harmonic injection is more favorable for the stator copper loss optimization in the full torque range. (2) The proposed FRML control strategy based on harmonic current injection can further expand the range of torque optimization and enhance adaptability to various load conditions. (3) The proposed fault-tolerant control strategy is scalable. Future work will be focused on extending the applicability of the proposed control strategy to other polyphase motors, such as nine-phase motors.

The large-scale development of wind power is a major demand for the development and utilization of new energy sources, and the high-performance service of the wind turbine fleet is an important guarantee for realizing the goal of the national carbon peaking and carbon neutrality goals. With the continuous increase of stand-alone capacity and installed capacity, wind conditions, sea conditions, and other complex environments make the synergistic optimization between service performance of large-scale wind turbine fleet- safe operation capacity-power generation benefits complex, and the unit safety and accurate warning and service quality control face serious challenges.

Firstly, the advantages and disadvantages of condition monitoring and fault diagnosis of key components of WTGs and reliability assessment are sorted out and compared. The current status of their service quality regulation is investigated. Secondly, the impacts of WTG’s healthiness, corrosive environment, and thunderstorms on the service quality of WTGs are elaborated, and the impacts of WTG FM strategy on the service quality are summarized. Then, the factors that affect the service quality of the wind turbine fleet are analyzed. The characteristics of voltage control strategy, operation and maintenance, and tail current control are analyzed.

High-quality power generation, operation and maintenance strategies, and tailing effects are analyzed at the level of the wind turbine fleet based on the service quality control methods of key components, wind turbines, and the wind turbine fleet. An outlook of the possible future direction is made to enhance the service performance of the wind turbine fleet and promote the healthy and sustainable development of the wind power industry.

This paper analyzes the electromagnetic energy flow and coupling characteristics in wireless power transmission (WPT) systems. Addressing the complexities in accurately depicting the electromagnetic energy transformation within WPT systems, the research overcomes challenges associated with the intricate mathematical methods and the absence of models capable of characterizing spatial energy flow distribution.

A model for electromagnetic energy flow in WPT under sinusoidal excitation is established based on Poynting’s theorem. A reduced-order mathematical model is developed by analyzing common electromagnetic energy flow characteristics of basic electrical components. This model qualitatively explores the energy coupling in the transmission space. The coexistence of inductive and capacitive coupling in WPT systems is discussed, emphasizing the significance of enhancing near-field electromagnetic coupling for overall system performance. The working mode of WPT in the electromagnetic near-field region is presented from the perspective of the energy flow mechanism. An experimental platform is constructed to verify the inductive and the capacitive coupling methods.

The electromagnetic energy flow characteristics of conductors, transformers, and capacitors are analyzed, facilitating power transmission through the electromagnetic fields in their vicinity rather than by themselves. The electromagnetic energy flow characteristics of WPT systems are discussed as a combination of multiple RLC circuits. It is found that electromagnetic power is partly stored in the electromagnetic fields of individual circuits (self-energy) and partly in the fields between circuits (mutual energy). The analysis is simplified by considering a system with two RLC series circuits, revealing that WPT relies on mutual coupling between the primary and secondary sides for contactless power transfer.

The paper also discusses typical magnetic resonant WPT systems using the image method to analyze the field strength distribution in the coupling space. The symmetry between inductive and capacitive coupling characteristics is revealed, offering guidance for practical engineering design. Experiments are conducted to verify the coexistence of inductive and capacitive couplings and to analyze their frequency characteristics. Results indicate that as the operating frequency increases, the ratio of capacitive coupling to inductive coupling increases, which is significant for understanding WPT technology.

In conclusion, the paper analyzes the electromagnetic energy flow and coupling characteristics in WPT systems, offering valuable insights for the theoretical research and practical application of WPT technology. It highlights the importance of understanding the coexistence of inductive and capacitive couplings and their frequency characteristics to enhance the performance of WPT systems.

As a non-contact power supply method, wireless power transfer (WPT) technology is widely used in medical, automotive, and cellular devices because of its reliability, safety, and high degree of freedom. However, the parameter drift phenomenon of the coupler inevitably occurs in practical applications, which leads to the fluctuation of self-inductance and makes the WPT system suffer from frequency detuning. Thus, its transmission characteristics and stability are affected. Traditional bilateral frequency tuning methods are non-uniform because of the type of topology, and some require communication equipment and complex optimization of control parameters. This paper proposes a unified decoupling control strategy of frequency tuning for high-order compensated WPT systems.

Four T-type higher-order compensation networks of LCC/LCC, LCC/S, CLC/CLC, and CLC/S are analyzed as examples. Based on the impedance model, the bilateral resonance characteristics of the primary-side LCC-compensated WPT system and the primary-side CLC-compensated WPT system are deduced. If the primary side is in a resonant state, the RMS value of the input current will reach the minimum. If the secondary side is in a resonant state, the RMS value of the current will reach the maximum. Finally, the generalized criterion is obtained for bilateral tuning decoupling control of higher-order compensated WPT systems.

This paper proposes a control strategy to realize the bilateral tuning decoupling control without communication or parameter identification. Instead of the inherent compensation capacitance, the switched capacitor converter (SCC) structure is used, and the equivalent capacitance of the SCC is varied by changing the conduction angle of the control signal. Based on the generalized tuning criterion, the conduction angle of the SCC control signal is changed with the help of the double-step perturbation observation method, and the primary and secondary currents are searched until the minimum value of the primary input current and the maximum value of the secondary coil current. Therefore, the WPT system reaches the resonant state while the conduction angle is optimal. The primary and secondary resonance parameters are realized independently and adaptively, and the bilateral tuning and decoupling control is achieved.

Finally, an experimental prototype of a 180 W LCC/LCC WPT system is built. The experimental results are consistent with the theoretical analysis, verifying the effectiveness of the proposed generalized tuning decoupling control strategy. The results show that the method can effectively suppress the frequency detuning problem caused by the parameter drift of the coupler and the self-inductance fluctuation, improving the transmission efficiency and stability of the WPT system. In addition, the proposed method is applicable to the high-order WPT system with a π-type compensation network.