PV systems are typically equipped with reactive power compensation devices when connected to the grid, and static synchronous compensator (STATCOM) devices are widely employed due to their flexible control capabilities. The increasing utilization of power electronic devices in the power grid has resulted in a shift from physical synchronization to control synchronization as the dominant mode of system operation. Analyzing static synchronization stability problem is more challenging for these systems compared to conventional power systems, as converter output characteristics are influenced by control strategies. Therefore, it is imperative to urgently address the problem of static synchronization stabilization under control strategy dominance.

First, this paper establishes the static synchronous stability analysis model of the grid-connected converter based on the control loop and circuit structure of each converter in a parallel system under the respective dq reference frame. The dq reference frame of the converter is determined by the phase information provided by the control loop in a multiple converter parallel system, thus enabling a unified coordinate system for static synchronization stability analysis. Subsequently, an equivalent small signal model is developed for analyzing multiple grid-connected converters. In comparison with existing coordinate conversion methods, Kirchhoff's current law is incorporated to enhance accuracy and reduce errors.

Then, the stability criterion for impedance analysis is enhance, and the static grid-synchronization performance indices are created. The small perturbation oscillation characteristics are measured using overshooting and regulation time, while the participation factor is employed to analyze the impact of each pole of the system. Finally, the attenuation coefficient is utilized to assess static synchronization stability performance.

The model is developed in Matlab/Simulink for simulation verification. Subsequently, an analysis is conducted on the impact of parameters such as the control loop parameters and STATCOM capacity on static synchronization stability. The main conclusions are summarized as follows:

(1) Optimizing the reactive power output of the grid-connected converter based on known control parameters can significantly enhance static synchronization stability performance, with the dominant influence of small perturbations after oscillation mode being attributed to poles generated by phase-locked loop control.

(2) The attenuation coefficient of the system exhibits a rapid increase in proximity to the critical stability region. Hence, it is imperative for the system to possess a certain margin of attenuation coefficient during operation. Based on the simulation analysis results presented in this study, static synchronous instability phenomena occur when the attenuation coefficient of the PV system exceeds 300. Conversely, when the attenuation coefficient falls below 250, the system remains in a state of static synchronous stability. These findings establish a criterion for analyzing and assessing static synchronization stability within such systems.

(3) The addition of STATCOM to the PV system primarily impacts the conductance matrix transfer function of the q-coupled channel. The phase-locked-loop coupling oscillations between the grid-connected converters do not affect the dd channel. Within the stable operating region, an increase in bandwidth for the DC voltage control loop, active current control loop, and reactive current control loop results in an amplification of both attenuation coefficient and system oscillation amplitude.

(4) When the phase-locked loop parameters of the STATCOM are the same as the PV system, the stability performance of the system is mainly affected by the grid impedance and the equivalent conductance transfer function of each grid-connected converter. And each grid-connected converter can independently connect to the grid and achieve stable operation to ensure that the system achieves static synchronous stability in this case.

(5) In cases where the active output of the PV system is low, STATCOM typically adjusts its capacitive or inductive reactive power provision to improve static synchronization stability performance. Conversely, when compensating for capacitive reactive power, utilizing STATCOM may yield superior results compared to using the PV grid-connected converter alone. Hence, allocating an optimal capacity for STATCOM can significantly enhance static synchronization stability performance.

Electromagnetic drive forming technology is a special forming process that uses pulsed Lorentz force to drive a high-conductivity sheet to move, thereby driving a low-conductivity sheet to cause plastic deformation, which can effectively make up for the shortage of traditional electromagnetic forming in forming low-conductivity materials. However, in the existing electromagnetic drive forming, the driver sheet also undergoes plastic deformation, which tends to lead to a serious problem of wastage of the driver sheet, and it is difficult to regulate the forming shape.

To solve this, instead of the traditional circular drive sheet, a solid copper ring with a specific thickness is employed, utilizing the strong electromagnetic force generated in the copper ring to propel it at high speed into collision with a metal sheet. This impact generates a contact force, causing the sheet to undergo plastic deformation. Additionally, an electromagnetic-structural coupling model for the copper ring electromagnetic drive forming process is developed using LS-DYNA software. A series of electromagnetic drive forming experiments are then conducted, using a TA2 titanium plate as the test material, to validate the feasibility of the proposed method. Numerical simulation and experimental results show that under a single discharge (7 kV), a metallic copper ring with a diameter of 80 mm can drive the titanium plate to deform and the forming height can reach 14 mm. Meanwhile, based on strain analysis of the forming sheet and the driven ring, the solid copper ring does not deform and can be reused. In addition, by changing the size and shape of the copper ring, the forming profile of the plate can be flexibly adjusted. For example, when the diameters of the circular driving rings are 65, 80, and 95 mm, uniformly deformed areas with diameters of 58, 72, and 87 mm are observed on the top of the sheet, which is highly consistent with the shape of the rings. Even if the forming height is increased, the forming shape of the center area of the sheet remains a flat-topped profile when enhancing the discharge voltages. On this basis, the dynamic deformation process of the sheet is further investigated through numerical methods, to reveal the deformation behavior and forming mechanism of the titanium plate driven by the copper ring, which demonstrates that the forming velocity approaching 100 m/s and the strain rate is up to 1 000 s^-1. Hence, this forming process belongs to the category of high-speed forming technology.

The obtained results indicate that, since the copper ring is a solid ring with a specific thickness, it does not experience plastic deformation during the electromagnetic drive forming process and can be reused. This effectively addresses the issue of excessive waste of the driver sheet in conventional electromagnetic drive forming. The copper ring also provides shape adjustment capabilities, allowing for the formation of sheets with circular, quadrilateral, and hexagonal flat tops. The height of the flat-topped profile can be controlled by adjusting the discharge voltage, overcoming the problem of limited shape flexibility in existing electromagnetic drive forming methods. These results are of significant practical value for advancing and expanding the applications of electromagnetic drive forming technology.

With the rapid development of the global economy, offshore wind power generation technology has been advancing towards field group scale and industrialization, becoming a research hotspot in international renewable energy. However, to reduce the economic costs associated with deep-sea wind power technology and enhance the efficient of wind energy capture and utilization, the capacity of wind turbines has been gradually upgraded to 10 MW and above. This trend towards large capacity has consequently led to increased weight and volume of wind turbines, complicating offshore transportation, lifting, operation and maintenance, which limits further development of offshore wind power technology. Moreover, the significant volatility and intermittency of offshore wind power contribute to increased grid penetration issues, difficulties in large-scale grid connections, and a notable phenomenon of wind curtailment. Furthermore, the non-stationary wind power can cause grid voltage fluctuations, flicker, frequency fluctuations, harmonics and other power quality problems, affecting the stable operation of the grid.

To address these problems, Hunan University's wind power generation team proposed an innovative integrated technology for hydrogen production through offshore superconducting wind power generation. This innovative system utilizes water electrolysis to locally consume offshore wind energy, with the produced liquid hydrogen being transported to land via ships or pipelines for comprehensive utilization. Additionally, a liquid hydrogen circulation refrigeration system provides a stable low-temperature environment for superconducting wind turbines, significantly reducing platform volume and weight and ensuring the reliable operation of the integrated system.

The article provides an overview of recent development in HTS wind turbine technology and offshore wind power hydrogen production technology, both domestically and internationally. It analyzes the key structures and feasibility of the proposed innovative integrated system, highlighting how it compares to traditional technologies. Additionally, the article explores recent advancements in offshore wind power generation and transmission technologies. The discussion then shifts to the benefits of the proposed innovative technology in comparison to other existing technologies and schemes. It summarizes the advantages of integrating hydrogen production and offshore superconducting wind power generation, analyzes the variability of superconducting wind turbines output power and the limitations of current converter topology control strategies, and proposes the key technologies of designing superconducting wind turbines converter topology with efficient energy transfer capability and designing a superconducting wind power system friendly control strategy.

For the future development of the integrated system, an energy island system plan that is integrated with renewable energy development is proposed. This plan is based on the operational principles of each sub-structure and aims to harness the efficient synergy of renewable energies. Research will focus on determining the appropriate ratios for various energy production and conversion devices, which will optimize the configuration of multi-energy complementarity. This approach aims to establish an integrated energy system that reduces the standby capacity required by the system’s various equipment. Furthermore, this initiative will promote the coupling of the power with renewable energy systems, facilitating the synergistic development of electric power and green hydrogen. This strategy will improve the optimized configuration of the energy supply system and establish a common technological framework for large-scale superconducting wind power hydrogen production technology.

Current electric shock detection methods are primarily designed to address faults between the live wire and the ground wire, mainly relying on monitoring changes in residual current to identify issues. However, in the case of a neutral-to-live electric shock fault, the fault circuit often does not cause a significant change in the residual current. This presents a considerable challenge for existing detection methods when it comes to identifying neutral-to-live electric shock incidents.

To address the aforementioned issues, a low-voltage neutral-to-live electric shock faults detection method based on dynamic fault characteristics and a light gradient boosting machine has been proposed. Firstly, a 1:1 prototype experimental platform for a low-voltage distribution network was established in a real system. Under various operating scenarios involving multiple household loads, experiments reproducing live neutral shock faults were conducted alongside control experiments using a sliding resistor to replace the electrically shocked body. A substantial amount of experimental samples representing both fault and normal operating states was collected, creating a comprehensive database. Secondly, the complexity of neutral-to-live electric shock faults is assessed based on the interference of load current on fault current. A fault circuit electrical equivalent model is established by considering the dynamic resistance and breakdown arcs at the dual contact points of the neutral-to-live shock, in conjunction with biological dynamic impedance. The impact of fault current on the main circuit current is analyzed. Finally, features of the main circuit current are extracted from the perspective of magnitude and high-frequency components, and the temporal changes of individual features before and after the occurrence of faults are compared. Given the difficulty in clearly distinguishing between fault and non-fault states based on individual features alone, along with the fact that these features exhibit varying sensitivity to both states, a multidimensional representation of the system state is employed. Following an ensemble computational approach, a lightweight gradient boosting machine model is developed, leveraging its uni-directional gradient sampling method and ensemble operation mechanism to accurately classify the two states.

The proposed method was evaluated on a test dataset consisting of 50 666 samples, achieving an overall accuracy of 96.82%. Specifically, the identification accuracy for 35 831 normal samples was 97.50%, while the accuracy for 14 835 neutral-to-live electric shock faults was 95.17%. The test results indicated that the proposed method could accurately distinguish neutral-to-live electric shock faults from normal operating conditions, including those in the control group with the sliding rheostat added, even when the fault information was significantly obscured by high load currents. Compared to existing methods, the proposed approach shows an advantage in accurately detecting low-voltage neutral-to-live electric shock faults.

The following conclusions can be drawn from the analysis: (1) By incorporating the time-varying impedance of biological tissues, variations in contact resistance, and breakdown arcs, the dynamic characteristics of faults were examined, revealing two effects of neutral-to-live electric shock faults on the main circuit current: changes in current magnitude and variations in high-frequency components. These findings served as the basis for constructing feature vectors. (2) The contribution of individual features to distinguishing between neutral-to-live electric shock faults and normal operating conditions is limited, resulting in significant inter-class ambiguity that can easily disrupt the sample fitting performance of traditional pattern recognition models. However, if features can exhibit a certain degree of sensitivity across different classes, the combination of multidimensional features can facilitate comprehensive discrimination. (3) Due to its inherent resilience to disturbances, the ensemble model can effectively mitigate interference caused by inter-class ambiguity and demonstrate strong generalization capabilities.

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.

The linear induction machine (LIM) drive system can get direct thrust and linear motions without transmission, which enjoys strong climbing capability, high acceleration or deceleration ratio, and small mechanical losses. The LIM drive systems have been developed and commercialized in over 20 linear metro lines worldwide. However, due to the large air gap, end effects, and high-power, low-switching frequency drive, the LIM drive system in urban rail transit needs better efficiency. Although the existing efficiency optimization control strategies have improved machine efficiency, the parameter robustness and system efficiency still need to be addressed. This paper proposes a robust efficiency optimization strategy for three-level inverter-fed LIM systems under low switching frequency.

Firstly, the primary flux-based LIM loss model considering end effects is built, where the loss is expressed as a convex function of primary flux. Its parameter sensitivity and limitation are analyzed. Furthermore, combined with the gradient descent method, a hybrid optimal primary flux search method is proposed to eliminate the influence of parameter changes on optimal flux selection. Then, the cost function containing multiple objectives, such as primary flux control, switching frequency constraint, and neutral point voltage balance, is derived. A model-free predictive flux control based on the nonlinear-extended state observer is proposed to manipulate optimal flux flexibly under low switching frequency.

Finally, experimental comparisons with the existing methods on a 3 kW LIM confirm that efficiency and parameter robustness can be improved for the drive system under low switching frequency. The system efficiency with the proposed method can be improved by 1.22% and 0.64% compared with the mature control strategy and the existing efficiency optimization strategy under the working conditions of 8 m/s and 200 N.

The following conclusions can be drawn. (1) The proposed method takes the minimum DC-link current as the search objective, which considers the harmonic loss and inverter loss, thus improving the system’s efficiency. (2) Considering multiple objectives, such as the switching frequency constraint and neutral point voltage balance, a model-free predictive flux control with adaptive switching frequency regulation is developed. (3) By combining the hybrid optimal primary flux search method with model-free predictive flux control, the proposed method effectively avoids the influence of parameter changes and modeling errors on optimal flux selection and manipulation. In this way, the parameter robustness of the efficiency optimization control strategy is significantly enhanced.

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 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 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.

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.