Electrically Excited Synchronous Motors (EESM) can effectively avoid friction losses and dust caused by brushes through Inductive Power Transfer (IPT) technology, significantly reducing maintenance requirements and operational costs. In addition, long-term operation of the motor may lead to faults such as short circuits in the rotor windings. To enable rotor condition monitoring and assessment, ensuring stable and safe motor operation, an offline rotor parameter identification method is proposed. First, the excitation circuit is simplified using phasor transformation to establish a two-port network model of the excitation system. Subsequently, an equivalent circuit of the rotor winding is derived based on electromagnetic relationships. The ramp voltage of the IPT system serves as the test signal, and the rotor resistance and inductance are calculated through the two-port network. Compared to traditional solutions, this method meets the accuracy requirements for identification without the need for additional test circuits. Finally, an IPT-EESM system experimental platform was constructed, with estimation errors for resistance and inductance within 4% and 5%, respectively, verifying the correctness and effectiveness of the theoretical analysis.

Electrically excited synchronous motors (EESMs) can effectively eliminate friction losses caused by brushes and reduce maintenance costs by adopting the inductive power transfer (IPT) technology. However, the introduction of IPT technology makes it difficult to directly measure the field current and voltage, posing challenges for precise control and condition monitoring of EESM. Traditional current and voltage estimation methods require the acquisition of exciter-side signals or rely on rotor winding parameters during monitoring, limiting the adaptability of field system state observation. To address the difficulty in observing field current and voltage in EESM, this article proposes an indirect estimation method based on the phasor transformation. First, the electrical relationships of the system compensation network are simplified through phasor transformation. On this basis, a reduced-order model for field current and voltage is established using two-port network functions, enabling indirect estimation of field voltage and current from the primary side of the IPT system. Compared with traditional methods, this approach offers greater adaptability. Finally, an experimental platform for the IPT-EESM system was constructed. The estimation errors of current and voltage are maintained below 5% and 7%, respectively, demonstrating the validity and accuracy of the theoretical analysis.

Inductive power transfer (IPT) technology, leveraging its noncontact advantages, has been widely applied in areas such as electric vehicle charging and robotic power supply. However, electronic devices are susceptible to various influences during operation, potentially leading to failures. Fault-tolerant technology, as an effective means to enhance reliability, has garnered significant attention in electronic conversion, yet remains unexplored in IPT systems. This article proposes a fault-tolerant topology for the rectifier open-circuit fault in constant-current IPT systems, which enables the system to maintain high-transmission efficiency even in the event of a single-diode open-circuit or specified dual-diode faults, without the need for additional switching devices. Furthermore, a novel diagnostic method for secondary faults in the rectifier is introduced, accompanied by a detailed analysis of the secondary-side fault evolution mechanism and system safety margin. Finally, experiments validate the feasibility of the proposed fault-tolerant topology and fault diagnosis method.

The special structure of unmanned aerial vehicles (UAVs) poses challenges to the integrated design method and power transmission capability of the couplers used for their wireless charging. This paper proposes a new inductive and capacitive combined hybrid wireless power transfer coupler for UAV. Among them, the capacitive coupler is designed as a six-plate structure. A receiving plate and a shielding plate are installed on each of the two landing gears of the UAV, and the transmitting plates are installed on the ground. The FR4 epoxy insulating material is filled between the plates to increase the coupling capacitance. The inductive coupler adopts a square coil form, which is installed on the belly of the UAV. Inductive coupler and capacitive coupler compensate each other for reactive power while transmitting power, which eliminates the need for additional compensation network components on the receiving side. Secondly, based on the single-sided LCLC compensation network, this paper presents a parameter design method that can adjust the power transmission ratio of inductive and capacitive couplers. Then, the component stress analysis was conducted. Compared with the inductive power transfer (IPT) and capacitive power transfer (CPT) systems that have the same coupler and similar compensation network, the proposed system significantly reduced the stress on the coupler. Finally, an experimental prototype is established to verify the scheme. The experimental results show that the system can transmit 500W at an efficiency of 80.7%, which means it can be used for wireless charging of UAV.

In underwater inductive power transfer (IPT) systems, the variation of eddy-current losses with frequency can degrade the accuracy of parameter identification. To address this issue, this paper proposes a multi-parameter identification method for a double-sided LCC system. First, based on the circuit model and the frequency dependence of the equivalent eddy-current loss resistance, six sets of equations are established, transforming the parameter identification problem into an optimization problem. Then, to balance global search capability and convergence speed, a hybrid particle swarm optimization algorithm is employed to identify the unknown parameters. Simulation and experimental results show that, under different coil spacings, load conditions, and medium conductivities, the proposed method can accurately identify key parameters, with the overall relative error controlled within 5%. This method is applicable to parameter monitoring and performance regulation of underwater IPT systems.

Inductive power transfer (IPT) technology has become a research focus due to its convenience, flexibility, and environmental adaptability. However, the high failure rate of power electronic devices in IPT systems poses a significant challenge, with the precise diagnosis and localization of rectifier faults being a critical issue that requires immediate attention. This paper proposes a fault diagnosis method based on harmonic analysis for rectifier short-circuit faults in IPT systems. Initially, simulations were conducted to analyze the electrical characteristics of faults at different locations and the potential secondary faults they might cause. Subsequently, a mathematical model of the system was established, and the time-domain expressions of fault characteristics were derived, with their analytical expressions in the frequency domain obtained through Fourier transformation. Based on this, by analyzing the mapping relationship between different fault types and frequency-domain characteristics, a diagnostic scheme capable of fault type identification and localization was constructed. Finally, an experimental platform was set up to verify the variation patterns of characteristics under single-diode and dual-diode short-circuit faults.

Due to factors such as aging and manufacturing variations, the parameter of compensation components in the IPT system inevitably drifts. This drift can affect the accuracy of parameter identification, such as mutual inductance and load resistance, which could impact the precision of the output control. To address this issue, an offline multiparameter identification method based on a multiforest regression model is proposed. This method aims to proofread the parameters of the compensation components before charging, thereby reducing the identification errors caused by parameter drift in the compensation components. The LCC-LCC-type IPT system is utilized as an example. First, the impact of the secondary-side compensation components' parameter drift is analyzed; then, a multiforest regression model is introduced to proofread these parameters. By only measuring the effective value of voltage and current at multiple frequencies on the primary side, all the parameters of the secondary-side compensation components can be estimated. Simulation and experimental results show that the proposed method achieves an average identification error of approximately 1.4% for the LCC-LCC IPT system, and the maximum identification error does not exceed 3% under various coupling and load conditions.

Aiming at the problems of intelligent ship inductive power transfer (IPT) systems under complex marine operating conditions, such as susceptibility to parameter perturbations and power device faults, which result in low modeling accuracy, slow dynamic response and poor post-fault stability, this paper investigates an integrated full-system fault diagnosis and hierarchical fault-tolerant control strategy. Based on the complex Fourier series and generalized state-space averaging (GSSA) method, a complete nonlinear time-domain model of the IPT system is established. The high-order switching-coupled system is accurately reduced to a first-order dominant model, and the inherent over-damping characteristics of the system as well as the influence rules of relevant parameters are clarified. A PI closed-loop regulation strategy is designed, and the trade-off mechanism of proportional integral parameters regarding steady-state accuracy, response speed and fault robustness is revealed. Comparative theoretical analysis and simulation results verify that the established model is highly consistent with the dynamic characteristics of the practical system, with the steady-state error controlled within 2%. Under the open-circuit fault of power switches, the system can still maintain stable output current without instability or sharp current drop, demonstrating excellent fault tolerance. The research findings provide a theoretical basis and technical support for high-precision modeling, parameter tuning and the safe and reliable operation of wireless charging systems for intelligent ships.

Conventional wound-field synchronous machines (WFSMs) suffer from reduced reliability due to inherent issues such as mechanical wear and contact sparking associated with their carbon brushes. To overcome this limitation, this paper proposes a novel grooved disk coupler (GDC) based on CPT. Compared with typical rotary couplers such as the disc plate, cylindrical plate, and concentric ring type, this structure can achieve a higher coupling capacitance at a larger air gap, which can significantly enhance the power transmission capacity. Through finite element analysis, the performance of the GDC and the electromagnetic characteristics of the main motor were comprehensively evaluated. Utilizing the GDC as the core component, a wireless excitation system was developed and integrated into a 15 kW power generation experimental platform with a rated speed of 750 rpm. The experimental results show that at a transmission distance of 5 mm, when the equivalent rotor excitation winding resistance is 3 Omega, the system can achieve an output of 333 W of excitation power and a DC-DC transmission efficiency of 66.93%. Furthermore, the experiment verified the effective regulation effect of the excitation current on the generator's output voltage by adjusting the excitation current and conducted tests under different excitation currents, rotational speeds, and load conditions. The results confirm that the proposed capacitive wireless excitation system successfully meets the excitation requirements of a 15 kW generator.

The escalating demand for efficient maritime power transfer has driven the exploration of wireless power transfer (WPT) solutions. This article aims to develop a novel dual-medium capacitive coupler that leverages the characteristics of air and seawater to overcome limitations in traditional capacitive power transfer. Traditional capacitive couplers that use air alone exhibit low power density, while those relying solely on seawater suffer from high self-coupling due to its conductivity, which impedes effective power transfer. The proposed dual-medium coupler mitigates these issues by situating one set of plates in seawater and another in air, thus eliminating self-coupling constraints and ensuring consistent underwater coupling regardless of distance or misalignment. This innovative approach reduces space and cost requirements, providing a promising alternative for maritime power transfer. The study provides a detailed explanation of the coupler's structure and principles, parameter design methodology, and experimental validation. Notably, the proposed coupler achieves a significant power output of 10 kW with a DC-to-DC efficiency of up to 94.8%. This underscores the potential of the novel coupler to address WPT challenges in maritime environments.

Traditional wound field synchronous machine relies on carbon brushes and slip ring contacts for power, high friction loss and reliability defects, and the high cost of position sensors further constrains its application. For this reason, this paper proposes a capacitive power transfer system that integrates sensorless position identification. First, a novel groove disk rotary variable coupler (GDRVC) featuring continuously variable plate geometry during rotation has been developed. This innovative design maintains coupling capacitance variation within a 10% tolerance range. Second, a double-sided LC compensation network with output voltage decoupled from the coupling capacitance is established, in order to increase the tolerance of the output power to changes in coupling capacitance. Further, a method using impedance analysis to identify the coupling capacitance CM is proposed. And based on the coupling capacitance-rotor position mapping relationship, the sensorless position identification is realized using the look-up table method (LUT). Finally, an experimental prototype was implemented to validate the design. Under the conditions of a 2 mm air gap and a rotational speed of 750 rpm, the system achieved a power transfer of 200 W at 600 kHz with a DC-DC efficiency of 90.05%, thereby fulfilling the excitation requirements of the motor rotor. In the unfiltered case, experiments show that the maximum discrimination error is +/- 10 degrees, the average absolute error is 3.6 degrees, confirming the feasibility of the integrated system.

Parameter identification-based control strategies are considered the preferred solution for achieving constant current (CC) and constant voltage (CV) charging control in communication-free inductive power transfer systems. However, identification errors in mutual inductance, load resistance, and other parameters can affect control accuracy. To improve control accuracy and response speed, a communication-free control strategy based on neural networks and deep transfer learning is proposed. This strategy eliminates the need to identify parameters like mutual inductance and load resistance. Only a few measured datasets are required to train the network model offline, and a trained model can online estimate output voltage/current. By combining with a controller, CV/CC charging control can be achieved under conditions of real-time variations in mutual inductance and load resistance. The experimental results show that the proposed control strategy achieves a static error of only 1.5% and a response time of no more than 24 ms. Compared to the parameter identification-based control strategy, the proposed strategy demonstrates lower static error, shorter response time, and a wider dynamic range.

This article investigates a linear parameter-varying (LPV)-based output voltage mitigation method for the capacitive wireless power transfer (CPT) system employing a series buck converter under varying mutual capacitance conditions. A LPV model is utilized to represent the dynamics of the buck converter under input voltage fluctuations. Based on the estimated model, a robust controller is designed using the normalized coprime factor (NCF) approach to ensure system stability and performance. Experimental results demonstrate the effectiveness of the proposed method. The system achieves rapid voltage regulation and maintains stable output voltage under various disturbance frequencies and load conditions. These findings validate the robustness and adaptability of the proposed control strategy, offering a reliable solution for enhancing the performance of CPT systems.

The hybrid inductive and capacitive wireless power transfer (HWPT) system is confronted with the dual challenges of the eddy current effect brought by the integration of the hybrid coupler and the output fluctuation caused by the misalignment of the coupler. Therefore, this paper proposes a novel HWPT system design featuring a fishbone-shaped capacitive coupler and presents an optimisation strategy. The proposed structure effectively suppresses eddy currents by limiting their circulation paths while enabling independent design of the capacitive and inductive couplers, thus ensuring the system's power transmission capability. Then, based on the proposed efficiency model of the hybrid coupler, this paper analyses the factors affecting the efficiency of the hybrid coupler and gives the conditions for achieving efficiency optimisation of the system in combination with the double-sided LCLC compensation network. Finally, with the goal of minimising the fluctuations in the system output current and efficiency during misalignment, the system parameters are optimised using the particle swarm algorithm. The experimental results demonstrate that the system achieves 3.3 kW power transfer at a 100 mm airgap with 87.6% peak efficiency, confirming effective eddy current suppression. Under 30% horizontal misalignment and 0 degrees-45 degrees rotational misalignment, the output current fluctuation remains below 10%, while the efficiency variation is maintained within 3%.

Multi-transmitter inductive power transfer improves landing-position tolerance for unmanned aerial vehicle charging yet coordinating the transmitter currents to balance dc-to-dc efficiency, target-region field uniformity, and off-target magnetic leakage remains an open problem. This article casts that coordination as a constrained three-objective current-allocation problem. A 3×3 array of overlapping coils is driven by four reusable inverter channels through a shared routing matrix, supporting one-, two-, and four-transmitter modes while reducing the high-frequency switch count from 36 to 16. For each receiver position, Pareto-optimal current vectors are generated offline and stored in a position-indexed lookup table; a two-stage rule—near-knee efficiency screening followed by normalized-utility ranking—selects a single hardware-feasible operating point. On a 350 W, 85 kHz prototype with a 50 mm air gap, peak measured dc-to-dc efficiencies reach 88.6% (2-Tx) and 87.9% (4-Tx). Measured lateral sweeps exceeding 100 mm compare the proposed and balanced-current allocations, while model-based analyses provide comparisons with the mutual-inductance-proportional and efficiency-only baselines. The same operating-point group is retained for 99.4% of sampled weight combinations, indicating low sensitivity to preference selection. A reference-anchored spatial assessment predicts that the 350 W target remains reachable across most of the charging area under a 6 A branch-current limit, enabling position-adaptive operation with explicit control over efficiency and field distribution.

Conventional permanent magnet synchronous motor (PMSM) fault diagnosis methods rely on one-dimensional (1-D) time-series signals. These approaches face challenges such as complex signal processing, difficulty in extracting fault features, and limited noise immunity. To address these issues, a novel approach method is proposed. Its core process includes wavelet packet decomposition (WPD), distributed recurrence plot (DRP) generation, and image transformation. This approach enables feature representation of the original signal across multiple frequency bands, and the shortcomings of traditional recurrence plots in terms of feature redundancy and long-sequence representation are overcome. On this basis, a lightweight multi-frequency-scale fault diagnosis model is developed, consisting of a multi-frequency-scale convolutional neural network (CNN), a convolutional block attention module (CBAM), and a global average pooling (GAP) layer. Experimental results demonstrate that the proposed method achieves high diagnostic accuracy and strong noise immunity. Under identical hardware and dataset conditions, the inference time of the proposed method is only 12.35% as long as that of traditional recurrence plot-based CNN and 50.03% as long as that of asymmetric recurrence plot-based CNN.

This article proposes an electric field-coupled wireless charging system for Uncrewed Aerial Vehicle (UAV) swarms, capable of simultaneously charging multiple drones through a single transmitter-side setup while demonstrating excellent misalignment tolerance and load decoupling capability. First, a single-input multioutput electric field coupler with simple structure and superior structural adaptability is developed. Parameter optimizations are conducted to enhance misalignment tolerance, and its equivalent circuit model is established through finite element simulations. Second, an LCLC-CLL resonant network is designed to achieve constant current output, multiload decoupling, and transmitter-side load-adaptive zero-phase-angle operation. Finally, an experimental prototype is constructed to validate the theoretical analysis. Experimental findings demonstrate that the system attains a maximum single-load output power of 709.9 W with peak dc-dc efficiency reaching 89.06% . Stable power delivery is maintained across lateral misalignment ranges of [-125 mm, +125 mm] and rotational misalignment up to 240 degrees. The system exhibits robust operational adaptability, sustaining high energy transfer efficiency during both load quantity variations and load imbalance scenarios. Furthermore, its advanced load-decoupling characteristics enable independent charging operation for multiple loads without cross interference, significantly enhancing the flexibility and cost-effectiveness of UAV swarm charging systems.

Wireless power transfer systems offer a new approach for supplying energy to Autonomous underwater vehicle (AUV), and inductive power transfer stands out for its high power density and strong underwater anti-interference capability. For different AUV models, unknown charging parameters make it difficult to achieve optimal efficiency, and the equivalent resistance of underwater eddy-current losses varies with frequency. Therefore, identification of mutual inductance, load, and the equivalent resistance of eddy-current losses is required. This paper proposes a multi-parameter identification method based on a hybrid particle swarm optimization algorithm. Using a double-sided LCC Systems as an example, four sets of equations are constructed from the circuit model and the relationship between eddy-current loss equivalent resistance and frequency. Collect the primary-side voltage and current for identification. Compared with traditional methods, this approach incorporates the frequency-equivalent resistance relationship into the identification framework, further improving parameter identification accuracy. Simulation results show that identification errors are basically within 3.5%.

The demand for high-power wireless power transfer systems has been gradually increasing in recent years. In this article, a high-power capacitive power transfer (CPT) system with an integrated multichannel coupler (IMCC) is proposed, which first realizes an output power of more than 10 kW, and the IMCC offers the advantages of reduced compensation inductors, reduced cross-coupling effects, and extendable performance. Since there is a cross-coupling between every two plates, the IMCC results in a circuit model of 15n + 16C2 n coupling capacitors (n represents the number of channels). The induced current source model and induced voltage source model are used to model the IMCC, and the effects of cross-coupling mutual capacitances on the system are analyzed. Compared to the four-plate multichannel coupler, the IMCC can reduce the cross-coupling effects in both aligned and misaligned cases. An M-M compensated three-channel CPT prototype with the IMCC is built, achieving an impressive output power of 10.35-kW and dc-dc efficiency of 94.2% with a 50-mm airgap. Experimental results show that the proposed CPT system with the IMCC is suitable for high-power applications and can effectively minimize the cross-coupling effects.

This paper presents a diagnostic approach for identifying faults in SiC MOSFETs within inverters of IPT(Inductive power transfer, IPT) systems. This method involves analyzing the output voltage signals of constant-voltage inverters without requiring complex hardware circuits. Initially, a detailed model of the MOSFET is constructed, examining the internal structure and operational principles of the enhanced N- channel MOSFET, as well as the primary causes of its failure, such as gate oxide layer aging, drain-source PN junction reverse breakdown, and pin detachment. Next, while the system is in a phase-shift condition, characteristic parameters of the inverter’s output voltage are extracted and used for data partitioning to analyze both soft and hard faults in MOSFETs. The fault diagnosis algorithm, developed using the C language, effectively distinguishes between soft and hard faults in MOSFETs and precisely locates the fault. Experimental results confirm the high accuracy and reliability of this method, ensuring the safe and stable operation of IPT systems.