High AC loss in stator windings is one of the key challenges in realizing fully high-temperature superconducting (HTS) wind turbine generators, which offer significant advantages in compactness and weight compared to conventional machines. Among the sources of AC loss, the perpendicular magnetic field component (relative to the HTS tape surface) is particularly dominant, while the parallel field contributes much less. Therefore, minimizing the perpendicular field in the stator windings is essential when designing a fully HTS generator. In this work, we present a 5 MW-class, air-cored, axial-flux fully HTS wind turbine generator modeled using the finite element method (FEM). The T-A formulation and interpolated Jc(B) characteristics are used to simulate the electromagnetic behavior of the HTS windings. A moving mesh approach is employed to simulate the rotor movement. Simulation results show that the outer-stage stator windings experience significantly higher AC loss than the inner-stage windings, despite delivering the same power output. By optimizing the rotor end-winding geometry, the perpendicular magnetic field in the outer-stage windings was significantly reduced, resulting in a 77% decrease in total AC loss across the HTS stator windings.

High Temperature Superconducting (HTS) machines offer potential for mass reduction in high torque low speed generators for multi-MW direct drive wind turbines and aerospace propulsion. The SuperMachine concept is a fully air-cored HTS machine, containing no iron and permanent magnets, thus eliminating saturation effects. In order to provide flux focussing an array of air-cored rotor field HTS coils is used to produce a pole-pair module in either radial or axial configuration, with the stator consisting of air-cored copper coils. The Biot-Savart method is applied to the SuperMachine topology to give a fast design optimisation tool. Verification of the SuperMachine concept and design tool was achieved by testing a pole-pair HTS coil array module in the axial configuration at 77 K in liquid nitrogen. The Biot-Savart design and optimisation tool is applied to design a 22 MW generator for direct drive wind turbine, and a 2 MW, 6000 rpm aircraft propulsion motor. For the wind study the optimised SuperMachine design is estimated to be half the mass of the equivalent permanent magnet generator. The aerospace study demonstrates the flexibility of the Biot-Savart tool to optimise the power density for active mass (W/kg) for minimum mass or cost, 55 kW/kg and 33 kW/kg respectively.

High-temperature superconducting (HTS) materials enable compact, high-power-density electrical machines and are particularly attractive for offshore wind power generation. This paper reports the integrated design of a Closed-Magnetic-Loop (CML) HTS coil-array module comprising eight coils for an air-cored HTS generator. The critical current of the HTS winding is evaluated using the H-formulation at 35 K, and, to maintain a 40% safety margin, the operating current is set at 500 A. Thermal analysis is carried out to optimize the cooling path, reducing the minimum temperature to below 35 K. Coupled electromagnetic-thermal-mechanical simulations are performed to optimize the mechanical support structure, bringing the maximum Tresca stress within allowable limits.

To achieve global carbon-neutrality goals, magnetic levitation (maglev) technologies offer a promising pathway toward sustainable, energy-efficient transportation systems. In this study, a comprehensive methodology was developed to analyse and optimise the levitation performance of high-temperature superconducting (HTS) maglev systems. Several permanent magnet guideway (PMG) configurations were compared, and an optimised PMG Halbach array design was identified that enhances flux concentration and significantly improves levitation performance. To accurately model the electromagnetic interaction between the HTS bulk and the external magnetic field, finite element models based on the H-formulation were established in both two dimensions (2D) and three dimensions (3D). An HTS maglev demonstrator was built using YBCO bulks, and an experimental platform was constructed to measure levitation force. While the 2D model offers fast computation, it shows deviations from the measurements due to geometric simplifications, whereas the 3D model predicts levitation forces for the cylindrical bulk with much higher accuracy, with errors remaining below 10%. The strong agreement between experimental measurements and the 3D simulation across the entire force–height cycle confirms that the proposed model reliably reproduces the electromagnetic coupling and resulting levitation forces in HTS maglev systems. The paper provides a practical and systematic reference for the optimal design and experimental validation of HTS bulk-based maglev systems.

High-temperature superconducting (HTS) self-switching flux pumps can inject direct current into closed-loop HTS coils without electrical contacts. Targeting practical application, this work investigated the charging capability, losses, and efficiency of the flux pump, explicitly capturing current sharing effect in the bridge tape based on a field-circuit coupled model. This paper focuses on four key design factors: the peak value and duty ratio of input primary-side positive current, secondary (series) resistance, and the copper stabilizer thickness of the bridge tape. The results showed that increasing the positive peak value of primary current can increase charging speed and the pumped current, while the secondary resistance exhibits an optimal value. Variations in the positive duty ratio highlight a trade-off between the pumped current, secondary-side efficiency, initial ramp rate, and ripple level. Finally, changes in the copper stabilizer mainly influence the current-sharing effect of the bridge tape and the bridge voltage, with associated impact on charging performance and efficiency. The modelling framework and findings derived from these studies provide practical guidance for parameter selection and prototype design of the self-switching flux pump.

Axial Flux Permanent Magnet Synchronous Generators (AFPMSGs) are critical in high power-density applications, making effective condition monitoring and fault diagnosis essential for operational continuity. Among various failure modes, interturn short-circuit (ITSC) faults are notoriously difficult to diagnose early. These defects are characterised by extremely weak initial signatures that are hard to detect, yet they tend to escalate rapidly into catastrophic failures. To overcome this early detection bottleneck, we introduce a Dual-Stream Graph Neural Network (DSGNN) fusion architecture. This framework integrates a convolutional feature extractor with two parallel Graph Neural Networks, enabling simultaneous modelling of spatial correlations among multi-source sensor channels and the temporal dependencies within the signals. An attention mechanism adaptively fuses these learned heterogeneous representations. Tested on an AFPMSG experimental platform, the DSGNN framework achieved a diagnostic accuracy of 89.26% for short-circuits as low as 1 to 3 turns in a single coil, significantly surpassing baseline models. This multi-source, structured data fusion framework provides a critical technical reference for detecting early mechanical and electrical defects in rotating machinery.

Permanent Magnet Synchronous Generators (PMSGs) have acquired a pivotal role in recent years, owing to their high-power density, high efficiency, and ability to operate in direct-drive configurations. Despite these advantages, such machines are susceptible to mechanical faults, particularly airgap eccentricity, with axial flux topologies being more vulnerable due to their high ratio of axial to radial length. Given the rapidly increasing deployment rates of these generators, this paper focuses on the electromagnetic analysis of a coreless axial flux dual-rotor direct-drive PMSG, with the analysis focusing on eccentricity faults. Static (SE) and dynamic (DE) eccentricities are investigated under a specific load condition using 3D finite element analysis (FEA) models. For the investigation of the fault scenarios, this work utilizes traditional signature analysis methods, namely Current Fast Fourier Transform (FFT), Voltage FFT, and Electromagnetic Torque Analysis.

High-temperature superconductors (HTS) have shown a promising potential in the realisation of high-power-density and compact machines compared to their conventional counterparts. Among many challenges, cryogenics and cooling system design for superconducting machines are the most critical challenges that researchers, scientists, and engineers have been trying to solve in the last few decades. A lot of success has been achieved, while a lot more has to be done in this field. The University of Edinburgh superconducting group has come up with a modular machine design for HTS wind turbine generators. The electromagnetic design of the machine has been published previously. The next step, i.e., the design of a modular cryogenic system - one of its kind - is currently underway. This work reports the initial progress in the cooling system design. In this article, in addition to the introduction to the overall design of the cooling system, an analytical model will be presented that helps estimate some of the important parameters for gaseous helium circulation design for superconducting coils. Following this publication, experimental results will be published later on.

Wave energy represents one of the most abundant and underutilized renewable energy resources, offering substantial potential to reduce global dependence on fossil fuel–based energy systems. Despite its promise, the practical exploitation of wave energy remains technically challenging, hindering its widespread deployment. This study presents a comparative electromagnetic analysis of inner-rotor and outer-rotor flux-switching permanent magnet (FSPM) generators designed for direct-drive wave energy conversion at a low operating speed of 30 rpm. To ensure a fair comparison, both topologies are designed with identical volumes of ferrite permanent magnets and magnetic materials. Two-dimensional finite element analysis (2D FEA) is employed to assess key performance metrics, including power density, efficiency, and flux characteristics. The results indicate that the outer-rotor configuration exhibits superior performance, achieving higher power density and efficiency, primarily due to its enhanced air-gap flux density and improved flux regulation capability. Both generator designs demonstrate strong potential for application in low-speed, direct-drive wave energy systems.

Conversion of mechanical energy into electrical in wave devices is very challenging due to the wide speed and torque ranges experienced. A wave device reciprocates at peak rotational speed of 1 rpm significantly lower than conventional generators. A gearbox or hydraulics have been used to meet the high speed low torque demands for conventional generators, but reliability issues have resulted in failures or operational limitations. Such mechanical interfaces can be eliminated using direct drive generators, either linear or rotary, but these generators are very large and heavy because of the wave speed and thrust requirements. The use of magnetic gears provides an alternative all electromagnetic drivetrain to direct drive, in which non-contact speed enhancement is achieved. Increasing the speed by even a factor of 10 is of benefit to the generator design. Axial magnetic gears are proposed for this application to integrate seamlessly with an axial permanent magnet generator. The magnetic and mechanical design of axial magnetic gears are presented to ensure that the design is manufacturable and capable of reacting the large magnetic attraction forces as well as the high torque producing forces.

This paper presents an efficient modeling strategy for superconducting motors, combining the time-space extrusion (TSE) method and the T-A formulation. Taking a newly designed air-cored 100-MW fully superconducting double-rotor motor (FSC-DRM) for direct-drive marine propulsion as an example, the proposed TSE and T-A combined method can achieve a 52% reduction in computational time compared to the conventional T-A model. In addition, compared to the AMSC 36.5-MW marine propulsion motor, with the same geometric size, the proposed FSC-DRM achieves a 2.1 times higher power density with an efficiency reaching 98.8%, considering the cooling penalty.

With the increase in wind turbine generator power ratings, achieving high power output while minimizing mass has become critically important. Conventional wind turbine generators rely on massive iron cores, which significantly contribute to the overall weight. In recent years, air-cored designs combined with high-temperature superconducting (HTS) windings have emerged as a promising approach to reducing generator mass and enhancing power capability. In this study, eight YBCO HTS coils were connected in series to form a closed magnetic loop (CML) array, demonstrating a novel ironless topology that replaces permanent magnets with HTS coils to enhance magnetic field strength. The FEM model for the HTS CML module was validated by measuring the magnetic field distribution, power dissipation during current ramping, and back electromotive force (emf) in the copper stator windings. The validated finite element method (FEM) model was subsequently extended to predict the performance of a full-scale HTS generator operating at 30 K. The prediction results confirm the feasibility of the proposed design and highlight its potential for realizing lightweight, modular, and high-power-density HTS generators for future renewable energy systems.

This review paper provides an overview of recent advancements in superconducting generators and cables for wind energy, with a focus on their potential to enable more compact and lightweight designs for large-scale wind energy systems. Superconductors, particularly high-temperature superconductors, offer a promising avenue for developing lightweight wind turbines. Traditionally, the weight of wind turbines increases with higher output; for 20 MW turbines, this can lead to excessive weight and volume. Superconductors can carry high currents and generate stronger magnetic fields while maintaining a lower volume and weight. Another significant advantage of superconducting generators is that their reliance on rare-earth metals is relatively lower than that of permanent magnet generators. However, the benefits of lighter and more powerful turbines come with challenges. Key issues such as high costs, AC losses, and production and supply chain concerns must be addressed to make superconducting generators commercially viable. Over the past two decades, substantial progress has been made in this field. This review highlights the work of researchers worldwide in superconducting wind energy, focusing primarily on superconducting generators. Notable projects, including the EcoSwing, SUPRAPOWER, UpWind, and the Innwind project, are also discussed. The outcomes of these initiatives have significantly contributed to the future development of this technology.

Advancement of renewable energy technologies placed tidal, wave and wind energy systems at the forefront of sustainable power generation. Permanent magnet synchronous generators with high efficiency, modularity, and low power consumption, such as the lightweight and modular C-GEN design, have been applied successfully in these applications. The demagnetisation condition of nonadjacent magnets in direct-drive permanent magnet generators is investigated, and different diagnostic approaches are evaluated. It is shown that nonadjacent demagnetisation can produce false negative diagnostic alarms when familiar condition monitoring methods such as the MCSA are applied. It presents solutions for faulty magnet detection of permanent magnet generators for tidal, wave, and wind energy harvesting, supported by numerical analysis and experimental testing. It is particularly novel that demagnetisation in two nonadjacent magnets is investigated here, something not previously considered.

Permanent magnet synchronous generators (PMSGs) are suitable for offshore applications due to their high efficiency and power density. Inter-turn short circuits (ITSCs) stand as one of the most critical faults in these machines due to their rapid evolution in phase or ground short circuits. It is therefore necessary to detect ITSCs at an early stage. In the literature, ITSC detection is often based on current signal processing methods. One of the challenges that these methods face is the presence of imperfections in the stator coils, which also affects the three-phase symmetry. Moreover, when the stator coils are connected in parallel, this type of fault becomes important, as circulating currents will flow between the parallel windings. This, in turn, increases the thermal stress on the insulation and the permanent magnets, while also exacerbating the vibrations of the generator. In this study, a finite-element analysis (FEA) model has been developed to simulate a dual-rotor PMSG under conditions of coil asymmetry. To further investigate the impact of this asymmetry, mathematical modeling has been conducted. For fault detection, negative-sequence current (NSC) analysis and torque monitoring have been used to distinguish coil asymmetry from ITSCs. While both methods demonstrate potential for fault identification, NSC induced small amplitudes and the torque analysis was unable to detect ITSCs under low-severity conditions, thereby underscoring the importance of developing advanced strategies for early-stage ITSC detection. The innovative aspect of this work is that, despite these limitations, the combined use of NSC phase-angle tracking and torque harmonic analysis provides, for the first time in a core-less PMSG with parallel-connected coils, a practical way to distinguish ITSC from coil asymmetry, even though both faults produce almost identical signatures in conventional current-based indices.

This paper presents a deep learning approach that employs large-scale pre-trained transformer models to predict the critical current density ( J c ) in high-temperature superconducting (HTS) materials under various temperatures and magnetic fields. The current widely adopted J c prediction methods, particularly Kim-like models, exhibit non-negligible errors at high magnetic fields, with the mean absolute percentage error (MAPE) reaching as high as 127.4% in the 5–8 T range on our validation dataset. Moreover, these models require parameter fitting at each temperature, with prediction accuracy reduced significantly when experimental data is sparse. To address these limitations, three encoder-only transformer based models (10 M, 85 M and 446 M parameters) were trained on a public dataset containing 260 823 samples from 20 different HTS tapes. These models can predict J c from the operating temperature, externally applied magnetic field, and tape type. Compared to Kim-like models, the proposed transformer models demonstrate substantial improvements across a wide range of magnetic fields and temperatures. In the 5–8 T range, the transformer models achieve mean absolute error (MAE) reductions of 82%–86%. On the Robinson test dataset (26,083 samples), all transformer models achieved MAE < 20 A cm −1 and MAPE < 10%, maintaining R 2 > 0.99 across all test conditions. Subsequently, three validation cases with extended experimental conditions (4.2–10 K and up to 18 T) were evaluated to test the versatility of the proposed models, with comparison against four established machine learning methods. Validation results indicate that large-scale transformer models maintain high predictive accuracy under extreme extrapolation—in the Shanghai Superconductor case containing 168 experimental samples, yielded an R 2 of 0.9916 and a MAPE of 4.36%, while even the 446M parameters model completed each prediction in about 45 ms, enabling near real-time J c prediction for practical applications. These results verify that the developed models successfully captured the current-carrying capability of HTS materials, enabling accurate predictions far beyond their training boundaries, providing valuable guidance for HTS device design and optimisation. The developed J c prediction tool is available at https://uoesupermachine.github.io/SupermachineGroup/Jcpre .

Inter-turn short circuits (ITSCs) stands as one of the most challenging faults to detect in permanent magnet synchronous machines (PMSMs). This study Focusses on a dual-rotor, air-cored permanent magnet synchronous generator (PMSG) with parallel-connected coils. For the analysis of the ITSC, a finite element analysis (FEA) model has been developed and validated under healthy conditions. In order to investigate the impact of ITSC faults on the PMSG and to understand the progression of fault severity, multiple cases with varying levels of fault intensity were analyzed and validated using mathematical modeling. The severity of the fault depends on two key parameters: the contact resistance and the number of shorted turns. To detect ITSCs in PMSMs, current-based methods are commonly employed, particularly because these machines are typically connected to PWM-based power electronic converters. In this study, motor current signature analysis (MCSA) and the extended park's vector approach (EPVA) were implemented. However, both methods faced challenges in detecting low-severity faults as a result to the generator's low operating frequency. This findings showcases the necessity for alternative diagnostic strategies to detect the ITSC under low fault severity.

A finite-element model of the direct-drive coreless permanent-magnet generator is used to simulate faults individually. Each fault case—rotor magnet demagnetization, a stator inter-turn short circuit, static eccentricity, and dynamic eccentricity—is introduced into the finite-element analysis (FEA) model separately, rather than in combination. For each isolated fault scenario, the stator current signals are processed using the Extended Park’s Vector Approach (EPVA) and the electromagnetic torque is examined in the frequency domain. The EPVA spectra and torque harmonics exhibit unique features for each fault type, allowing for clear discrimination among faults. These results demonstrate that modeling and analyzing faults one at a time yields distinct diagnostic signatures.

This paper presents the design and fabrication of a novel ferrofluid-gap test rig and reports preliminary experimental results on the magnetic behavior of a ferrofluidgap in open-load conditions. A ferrofluid-gap is an unconventional approach for reducing the magnetic reluctance of the air-gap region in electrical machines by filling it with magnetically permeable ferrofluid. With a particular focus on the application of ferrofluid-gaps to direct-drive wind turbine generators, a test rig was designed to characterize both the magnetic and mechanical behavior of ferrofluid-gaps across a broad range of conditions. This includes turbulence and shear rates exceeding what could be expected in full-scale multimegawatt machines. The experimental results demonstrate that the magnetic behavior of a ferrofluid-gap remains unaffected by turbulence and shear. Additionally, the observed increase in test rig open-load voltage output with a ferrofluid-gap is compared against predictions from finite element method simulations, showing good agreement between experiment and theory.

Inter-turn short circuit (ITSC) fault detection is a major challenge for direct-drive permanent magnet synchronous generators in renewable energy applications. In this paper, ITSC phenomena are investigated in a dual-rotor, air-cored Permanent Magnet Synchronous Generator (PMSG) with series-connected coils. An accurate finite element analysis model is developed and mathematically validated to characterize the electromagnetic performance under healthy and faulty conditions. In order to decipher the effect of ITSCs on the stator current distribution, contact resistance, and short-circuit ratio variations are investigated to derive the fault-induced current signatures. Typical conventional diagnostic methods like Motor Current Signature Analysis (MCSA) and Extended Park's Vector Approach (EPVA) are evaluated and found to be less sensitive on low-severity faults, which may lead to misdiagnosis. These findings suggest the need for complementary monitoring strategies towards the early fault detection for better operation reliability and efficiency of renewable energy systems.