Iet Electric Power Applications最新文献

Due to their inherent capability to provide short-circuit fault protection, combined with features, such as high torque density and reduced torque ripple, five-phase permanent magnet synchronous motors (PMSMs) driven by current-source inverters are highly suitable for mission-critical applications. However, unlike PMSMs, current-source inverters are more susceptible to faults. Conventional fault-tolerant techniques for mitigating open-circuit faults in current-source inverters typically assume that all the semiconductors in the affected inverter leg are faulty. In reality, the possibility of an open-circuit fault occurring in only one power switch has not been thoroughly studied. Consequently, this article introduces a fault-tolerant control (FTC) approach specifically designed to address single-switch open faults in five-phase PMSMs driven by current-source inverters. First, the paper evaluates the fault-tolerant capabilities under this particular fault condition. Then, two space vector pulse width modulation (SVPWM) strategies are developed and compared with existing SVPWM methods, focusing on winding copper losses and torque ripple. Finally, the effectiveness of the proposed FTC scheme is verified through experiments, demonstrating that this method can effectively reduce torque ripple and decrease winding copper losses.

This paper proposes a smoothed active disturbance rejection control (ADRC) strategy integrated with a hybrid sensorless algorithm to enhance the dynamic performance of a 12-stator/19-pole yokeless and segmented armature axial flux-switching permanent magnet (12S/19P YASA-AFFSPM) motor. The improved ADRC replaces the conventional nonlinear fal function with a smooth, exponentially interpolated function (efal) and employs linear error feedback to simplify tuning while maintaining robustness. A hybrid sensorless scheme, combining a pulsed high-frequency injection method for low speeds and a sliding mode observer (SMO) for medium-to-high speeds, ensures accurate rotor position estimation across the entire operational range. Experimental results demonstrate the outstanding performance of the proposed method: the rotor position error remains within ± 2°, the speed tracking error is limited to ± 5 rpm even during direction reversals and the transient speed deviation during sudden load torque changes (0–5 N m) is kept below 5% of the rated speed. The proposed approach significantly enhances dynamic response, disturbance rejection and operational robustness, validating its suitability for high-performance applications such as electric vehicles and industrial automation.

Large-capacity high voltage direct current (HVDC) transformers are the core equipment of the future power system. The design and operation of these transformers involve the interaction of multiple physical fields. The use of multiphysics simulation technology can comprehensively consider the coupling effects of various physics, which can help optimise the design scheme, improve the efficiency and reliability of the equipment, reduce the system loss and extend the life of the equipment. This paper proposes a multiphysics coupling simulation method for high-voltage DC transformers based on COMSOL multiphysics. Using this method, the distribution characteristics of the electric, magnetic, temperature and stress fields of the key components of the HVDC transformer under intermediate frequency conditions are analysed in detail. Through the analysis of the simulation results at different frequencies, the influence of frequency on the multiphysics distribution of the equipment is revealed, which provides a theoretical basis and practical guidance for the design and performance optimisation of HVDC transformers.

To improve the torque performance of permanent magnet synchronous reluctance machine (PMSRM) for electric vehicles, a novel torque-angle approximation PMSRM (TAA_PMSRM) is proposed in this article. This design utilises asymmetric permanent magnets (PMs) and inter-pole cavity to shift the axis of PM magnetic field, so as to make the peak of the PM torque component approximate to the peak of the reluctance torque component, and to increase the resultant torque without increasing the cost. And asymmetric tangential ribs are introduced to suppress torque ripple effectively. Through the parameter sensitivity analysis, the specific influence of the key structure parameters related to the PM magnetic field shift on the electromagnetic performance of the TAA_PMSRM is clarified, providing a theoretical basis for torque performance optimisation. Based on the step-by-step multi-objective optimisation design, the average torque and torque ripple are optimised while ensuring the mechanical integrity of rotor. A comparative analysis between the proposed TAA_PMSRM and the conventional PMSRM, both optimised using the same method under multiple operating conditions, confirms the torque improvement and overall performance advantages of the proposed design. Finally, a prototype of the TAA_PMSRM is fabricated and tested to validate the simulation accuracy and demonstrate its practical performance benefits.

Large-capacity superconducting (SC) generators have broad application prospects in offshore wind power. Replacing copper armature windings with higher current-carrying capacity SC tapes can further increase the power density of the generator. The phase current in high-capacity SC armature generators can be on the order of kiloamperes. To conduct such high armature current, multiple parallel-stranded SC tapes need to be employed. However, the current-carrying capacity and AC losses of SC armature windings will be affected by both the external magnetic field and their own magnetic field. Because of the effects of the external magnetic field, the current distribution in the parallel SC tapes is uneven, resulting in low tape utilisation. In order to weaken the influence of the external magnetic field on SC tape, the electromagnetic shield is usually utilised, but these shielding components introduce additional losses and reduce reliability. Therefore, this paper proposes a double-pancake coil tape transposition method based on analysis of the coupled magnetic fields between multiple SC tapes. This method can improve the uniformity of current transmission within the SC tapes and the overall current-carrying capacity of the SC coils, thereby further enhancing the power density of the SC generator.

The loosening of fasteners in converter valve saturable reactors presents a significant and often concealed operational hazard. To address the deficiencies in effective feature extraction from acoustic-vibration signals and their incomplete correlation, this study proposes a novel fault diagnosis methodology for these fasteners based on multi-modal feature fusion (MFF). Initially, the Gramian Angular Summation Field (GASF) extracted time-domain features reflecting global information, whereas the continuous wavelet transform (CWT) obtained time-frequency domain features capturing local characteristics. These were subsequently integrated within a 2D feature fusion framework through vertical channel-wise concatenation. Secondly, the methodology employed a gated recurrent unit (GRU) to fuse the temporal sequences of acoustic signals, which were then combined with the 2D features using convolutional neural networks (CNNs) to achieve progressive multi-source feature fusion from local to global scales. Furthermore, the model incorporated a multi-head attention (MA) mechanism to specifically enhance fault-indicative features, culminating in a deep fusion of time-domain, frequency-domain and time-frequency domain information. Finally, this study acquired acoustic data using a bespoke single-valve-layer experimental platform, supplemented by field data from the ± 800 kV Qingnan converter station. These datasets facilitated the analysis of overall acoustic-vibration signals from saturable reactor fasteners under both normal and faulty conditions. The proposed MFF model achieved a maximum detection accuracy of 96% for noncontact loosening faults. This work highlights the feasibility of acoustic-based fault detection in saturable reactor fasteners and provides practical guidance for enhancing predictive maintenance and operational safety in HVDC converter stations.

Under external short-circuit conditions, transformer windings are subjected to axial vibrations induced by axial electromagnetic forces. Due to the unidirectional compressive nature of spacers, separation between winding disks and spacers may occur, threatening the axial mechanical stability of the windings. Extensive research has been conducted on axial vibration calculation models and the vibration characteristics. These efforts have led to the establishment of vibration models based on mass-spring-damper systems, and investigations into the effects of factors such as moisture, ageing and damping on the behaviour of spacers and the vibration process. However, neither the impact of disk–spacer separation on winding stability has been analysed, nor have the critical conditions for its occurrence been defined. In this paper, a winding vibration model incorporating the unidirectional compressive characteristics of spacers was developed to analyse changes in vibration intensity before and after the onset of disk–spacer separation. The study clarified the patterns of separation under varying short-circuit currents, pre-tightening forces and spacer hardness. Furthermore, a rapid evaluation method for axial stability was proposed, using disk–spacer separation as a criterion. The results identify the critical conditions for disk–spacer separation, providing a theoretical basis for improving the axial strength of transformer windings.

This article proposes a novel L-shaped modular consequent-pole permanent magnet (PM) machine with an asymmetrical and hybrid pole structure (namely the AHPLM-CPM machine) designed for in-hub electric bikes (e-bikes). The AHPLM-CPM machine combines L-shaped modules with a consequent-pole structure to enhance the PM utilisation ratio and flux-focusing effect simultaneously. Additionally, a hybrid pole configuration, consisting of PM-iron and iron-PM sequences, is employed to reduce axial leakage flux. A multi-objective optimisation is performed on the L-shaped module parameters to minimise torque ripple while maximising average torque, leading to an asymmetrical pole structure. A comparative study on five proposed machines is conducted to highlight the superiority of the AHPLM-CPM machine in terms of torque characteristics, back-EMF voltage, airgap flux density and cost. Simulation results show that the PM utilisation ratio of the proposed machine is increased by 80.4% compared to a modular surface-mounted PM (MSMPM) machine. Furthermore, the AHPLM-CPM machine exhibits the lowest torque ripple and cogging torque while reducing PM costs by 50% compared to the MSMPM machine. Finally, a 250 r/min 500 W prototype is constructed and tested by considering the effect of the e-bike's gear system to verify the simulation results.

Doubly fed induction generators (DFIGs) are widely used in wind energy conversion systems due to their ability to provide variable-speed operation, offering significant advantages in energy capture. However, the presence of interturn short-circuit (ITSC) faults in the rotor windings of DFIGs poses a serious threat to their reliability and performance. Detecting such faults at an early stage is crucial for preventing damage and minimising maintenance costs. Traditional rotor interturn short-circuit fault detection methods in DFIGs often rely on extracting features from measurement or control signals using techniques such as the fast Fourier transform (FFT) to analyse their frequency components. However, these methods face challenges, especially when the generator operates near synchronous speed, as they may fail to capture subtle changes in the fault indices that are indicative of ITSCs. To address these challenges, this paper proposes a novel approach for ITSC fault detection in DFIGs operating at synchronous speed using a combination of convolutional neural networks (CNNs) and transformer architectures, especially for rotor interturn short-circuits (RITSC) due to their critical impact on system reliability. By combining these two architectures, the proposed diagnostic method significantly improves the fault detection accuracy compared to traditional approaches. The model was tested on rotor and stator current data, achieving classification accuracies of 99.01% and 95.52%, respectively. Additionally, the model demonstrated excellent robustness by achieving near-perfect accuracy (100%) under super-synchronous conditions and 98.93% accuracy at sub-synchronous speeds across varying load conditions. This hybrid CNN–transformer approach provides a robust solution for real-time fault detection in DFIGs, offering enhanced performance and reliability in wind turbine systems.

With the continuous development of new energy vehicle technology, coreless axial flux motors have garnered increasing attention due to their advantages in overload capacity and power density. However, as overload capacity and power density improve, the evaluation and enhancement of the reliability of epoxy resin-encapsulated stators have become critically important. This paper evaluates the risk of epoxy resin fracture during full-load motor operation under high-temperature conditions. Additionally, the risk of coil breakage under axial forces is assessed, considering potential epoxy resin failures. By replacing the rotor auxiliary permanent magnet materials and optimising the coil fixation areas, the reliability of the coils is improved. A prototype with adjusted parameters is fabricated and tested under various operating conditions, demonstrating the structural robustness of the motor. This study contributes positively to preventing coil fractures in coreless axial flux motors.