The 50 most-cited articles in IEEE Transactions on Magnetics, 2024

This study introduces a novel hybrid modeling approach that combines magnetic equivalent circuit (MEC) and 2-D analytical methods. The proposed method involves placing PMs on the stator bore in two forms: virtual permanent magnets (VPMs) or virtual volume currents (VVCs). To account for the effect of rotor teeth, analytical modeling is completed using virtual surface currents (VSCs). This hybrid modeling approach enables the calculation of the air gap magnetic flux density for the first time in an axial-field flux-switching bar-permanent magnet (AFFSBPM) motor. Because of the stator’s inner PM and doubly salient nature, the 2-D analytical model for AFFSBPMs is more difficult to solve. Therefore, the proposed method accurately with fast 2-D analytical by The Laplace/Poisson equations are solved and boundary conditions are applied to calculate the tangential and vertical flux components of the flux density distribution in the air-gap AFFSBPM motor. The 3-D finite element method (FEM) is used to verify the proposed method and the findings obtained.

With the widespread use of high-power high-frequency transformers in flexible dc transmission, high-power density motor drive control, and high-power charging fields, the vibration and noise of high-frequency transformers have been drawing more and more attention from the industry. The nanocrystalline materials are commonly used in the core structure of high-frequency transformers. Although it is generally believed that the magnetostriction of nanocrystalline materials is extremely low, the vibration noise is still very obvious for the nanocrystalline cores. Therefore, it is necessary to study the vibration and noise characteristics of nanocrystalline cores, especially under the excitation of square or rectangular excitation. This article constructs a non-sinusoidal measurement system, and the vibration and noise characteristics of rectangle nanocrystalline core under sinusoidal and non-sinusoidal excitations up to 5 kHz are measured. Meanwhile, the effect of zero-level times on vibration characteristics is also studied.

Currently, the automotive market is undergoing a vibrant transition toward component electrification driven by the widespread adoption of electric vehicles. The steering system, electric power steering (EPS), has evolved gradually from traditional hydraulic systems (HPSs) to electric systems. The current state sees the majority of commercial vehicles equipped with electric EPS systems. EPS reduces the steering effort applied to the steering wheel during low-speed driving, enhancing driving convenience. It is widely adopted in most commercial vehicles due to numerous advantages such as system simplification, speed-dependent steering control, and vehicle weight reduction compared to traditional HPSs. EPS can achieve a 3%–5% improvement in fuel efficiency compared to traditional HPSs because it operates only when the driver manipulates the steering wheel. However, what matters most in EPS is vibration and noise. Drivers are directly exposed to the vibration and noise of EPS. Therefore, it is crucial to implement electromagnetic designs that reduce cogging torque and torque ripple,…

The high power density, high efficiency, and wide speed range of permanent magnet synchronous motors (PMSMs) are attractive features. However, the cogging torque and unsuppressed torque ripple of PMSMs degrade torque quality and reliability and cause vibration. This article compares the effectiveness of PMSMs in reducing the cogging torque, torque ripple, and vibration by applying each stator tooth chamfer types: inner eccentricity chamfer, outer eccentricity chamfer, linear chamfer, and circular chamfer. First, stator tooth chamfers were applied to the reference model to confirm the tendency of cogging torque, torque ripple, and electromagnetic force according to the design variables by chamfer types, and it was demonstrated that the chamfer needs to be applied in a way that reduces the harmonics of the air-gap magnetic flux density to improve the performances through finite element analysis (FEA). Next, the optimum design for reducing cogging torque, torque ripple, and electromagnetic force was performed for each stator tooth chamfer types for a valid comparison. As a result, it…

Hysteresis modeling is crucial to comprehend the behavior of magnetic devices, facilitating optimal designs. Hitherto, deep learning-based methods employed to model hysteresis face challenges in generalizing to novel input magnetic fields. This article addresses the generalization challenge by proposing neural operators for modeling constitutive laws that exhibit magnetic hysteresis by learning a mapping between magnetic fields. In particular, three neural operators—deep operator network (DeepONet), Fourier neural operator (FNO), and wavelet neural operator (WNO)—are employed to predict novel first-order reversal curves and minor loops, where novel means that they are not used to train the model. In addition, a rate-independent FNO is proposed to predict material responses at sampling rates different from those used during training to incorporate the rate-independent characteristics of magnetic hysteresis. The presented numerical experiments demonstrate that neural operators efficiently model magnetic hysteresis, outperforming the traditional neural recurrent methods on various…

This work presents a flaw detection system consisting of an array of eddy-current (EC) probes based on giant-magnetoresistance (GMR) sensors for mapping the defects on a metal sheet. Before measurement, a spatially dependent calibration process was done to compensate for the inter-channel inconsistency in output offsets and responsivity. The calibrated 8-channel probe array exhibits high sensitivity in revealing tiny features of defects with superior spatial resolution. The proposed system allows for the visualization of the geometric characteristics of the surface defects with an inter-spacing of more than 2 mm. The suggested approach has great potential in the nondestructive testing of metallic sheets for the characterization of minor and intricately shaped flaws.

A segmented asymmetric V-type permanent magnet structure is proposed to address the issues of high output torque ripple and large cogging torque in traditional permanent magnet synchronous motors. First, the relationship between the pole-span angles of the segmented asymmetric V-type permanent magnet structure and the output torque, torque ripple, and cogging torque is investigated. Then, the rationality of the segmented asymmetric V-type permanent magnet structure and the correctness of the theoretical derivation are verified by the finite-element simulation. Subsequently, with the optimization objectives of increasing the average output torque of the motor, reducing the torque ripple, and decreasing the cogging torque, the optimal pole-span angle combination of the motor is determined by using the Pareto frontier distribution and the weight analysis method. The effectiveness of the optimized design is finally verified by the finite-element simulation and prototype tests. The results reveal that the segmented asymmetric V-type permanent magnet structure can ensure ample output…

Electromagnetic actuators based on passively levitating planar magnetic platforms driven by co-planar current-carrying coils find widespread use in precision positioning applications. While these actuators provide nanometer-scale positioning resolution, their in-plane actuation bandwidth is limited to a few tens of hertz due to the small in-plane electromagnetic stiffness. In this study, we optimize the design parameters of the electromagnetic coil and the magnetic platform to maximize the in-plane electromagnetic force and trapping stiffness per unit volume of the magnetic platform. Our approach utilizes closed-form expressions for electromagnetic forces and stiffness, derived in terms of the actuation currents, the pitch of the electromagnetic coil, and the dimensions, position, and magnetization of the magnetic platform. Notably, our investigation reveals that by reducing the pitch of the electromagnetic coil by a factor of 10, the in-plane forces and stiffness per unit volume of the magnetic platform can be increased by two and three orders of magnitude, respectively.…

Electric motors used in electric vehicles (EVs) are robust, efficient machines capable of delivering a wide spectrum of torque across their drive cycle. Throughout their operation, inevitable losses are incurred within the power system, primarily in the form of heat energy, which is directly proportional to the square of the current. Managing this heat energy necessitates suitable cooling methods to effectively counteract the generated heat during operation. Thermal analysis serves as a predictive tool to anticipate and address these thermal challenges and is often executed through finite element analysis (FEA). However, the utilization of FEA comes with extended computation times, prompting the exploration of alternative thermal analysis methods like the lumped parameter thermal network (LPTN). Unlike FEA, LPTNs do not face significant reconstruction time issues during the design stage, presenting an advantage in the development of motors. Presented is an enhancement to the conventional LPTN design while broadening the scope of the motor design process by introducing an LPTN…

A Suboptimal Multiple Fading Extended Kalman Filter (SMFEKF) for a Permanent Magnet Linear Synchronous Motor (PMLSM) is proposed to achieve accurate speed estimation and high reliability of a PMLSM sensorless drive system when under parameter mismatch and sudden load disturbance. First, a dynamic mathematical model of the PMLSM is established. Second, an Extended Kalman Filter (EKF) is presented which can be used to estimate the speed and position of the PMLSM. An SMFEKF is also introduced to improve the estimation performance of the proposed algorithm under parameter mismatch and sudden changes in load conditions. Finally, EKF and SMFEKF-based PMLSM systems are simulated and experimentally compared. Results show that the proposed algorithm can realize accurate estimations of speed and position of the PMLSM under different conditions. This study verifies that the introduction of multiple fading factors can significantly improve the estimation effect of the algorithm.

The design of electromagnetic coils may require evaluation of several quantities that are challenging to compute numerically. These quantities include Lorentz forces, which may be a limiting factor due to stresses; the internal magnetic field, which is relevant for determining stress as well as a superconducting coil’s proximity to its quench limit; and the inductance, which determines stored magnetic energy and dynamics. When computing the effect on one coil due to the current in another, these quantities can often be approximated quickly by treating the coils as infinitesimally thin. When computing the effect on a coil due to its own current (e.g., self-force or self-inductance), evaluation is difficult due to the presence of a singularity; coils cannot be treated as infinitesimally thin as each quantity diverges at zero conductor width. Here, we present novel and well-behaved methods for evaluating these quantities using non-singular integral formulas of reduced dimensions. These formulas are determined rigorously by dividing the domain of integration of the magnetic vector…

Hybrid multiferroic films are fabricated by depositing Pt/Co/Pt multilayers onto [001] and [110] cuts of PMN-PT crystal. The dependence of the interfacial Dzyaloshinskii–Moriya interaction (iDMI) on applied electric field is experimentally investigated in the system by the Brillouin light scattering (BLS) method. A strong variation (from −0.2 to 0.8 mJ/m2) of the iDMI constant is observed when the electric field is applied. In the case of [001] cut, the observed changes in the iDMI have an isotropic character, while in the case of [110] cut, they are anisotropic, which corresponds to the symmetry of the PMN-PT deformations. The change in the iDMI is accompanied by the formation of various unusual domain structures and skyrmion lattices. External control of the DMI with an electric field opens the way to manipulate topological magnetic solitons (such as skyrmions), which are promising objects for information processing and storage.

Energy from ocean surface waves is the most prominent form of marine energy. The waves are produced by gravitational water waves (2.2e5 Hz), in combination with the short wind and swell waves ($0.03-1$Hz). The energy density and predictability of waves make them an extremely interesting form of sustainable energy. Wave energy is therefore an ideal addition to the energy mix. Research has confirmed that (part) synergy is possible with offshore wind farms because the energy production profile over time of wave energy (even on a relatively sheltered inland North Sea) is not synchronous with the energy profile of wind, mainly due to swell waves and therefore is, at least, partly complementary to that of offshore wind. Wave energy can be generated via so-called wave energy converters (WECs). This article describes the potential of an innovative WEC with existing regenerative robots to be used in energy harvesting in the North Sea.

Pulsed eddy current is based on the electromagnetic induction principle, which is widely used in the metal industry for non-destructive testing due to its unique advantages, such as fast response, great penetration depth, and lift-off tolerance. Eddy current diffuses in a complex manner with the diffusion velocity uneven in space and time. A full picture of the diffusion velocity field enhances physical insights into pulsed eddy current detection. This paper proposes a novel point tracing method for velocity field calculation. The eddy current diffusion process is divided into three stages and their velocity fields are calculated respectively. The complete field is then visualized. The calculated results correspond to the phenomenon observed in numerical simulations. Furthermore, the relationship has been analyzed between the properties of the planar conductor, probe lift-off, and the diffusion velocity field, according to the proposed method.

Consequent pole permanent magnet synchronous motors (CP-PMSMs) have received attention because they can reduce the amount of permanent magnets used. Due to structural features, the magnetic flux of the air gap is imbalanced. Furthermore, torque ripple increases due to even harmonics of back electromotive force (back EMF). In this article, we propose an asymmetric design method to reduce torque ripple and magnet usage in consequent pole (CP) surface permanent magnet synchronous motor (SPMSM). First, the iron and magnet pole areas are selected asymmetrically to increase torque and reduce torque ripple. Second, the N pole of the CP-SPMSM (CP-Npole) and the S pole of the CP-SPMSM (CP-Spole) are combined in the axial direction to reduce the even harmonics of back EMF. An air gap is inserted between the two CP-SPMSMs to reduce axial leakage caused by the combination of opposing poles. Then, the location and axis length of the iron pole are designed asymmetrically. Torque ripple is further reduced by reducing the harmonics multiple of 6 of the back EMF. Finally, we compare the…

In this paper, solutions of the magnetostatic Maxwell’s Equation on parametric axisymmetric transformer geometries are approximated by a convolutional approach on Physics-Informed Neural Networks (ConvPINN). The trained ConvPINN is capable of predicting magnetic vector potentials (MVPs) and magnetic flux densities in a matter of milliseconds for a range of geometries described by a total of 18-20 degrees of freedom (DoF). The combination of ConvPINN with an existing framework for core loss prediction yields a super fast workflow for the approximation of core losses on a wide range of geometric setups. The combination of inference speed and accuracy enables new orders of magnitude for the optimization of transformer designs going forward.

With the extensive application of permanent magnet synchronous motors (PMSMs), their vibration and noise performance have also received increasing attention. The traditional reducing vibration method by adjusting the motor topology is not universal and costly. In addition, the zero-order mode of PMSMs always has a low natural frequency, which likely interacts with the zero-order electromagnetic force waves to increase vibration. Therefore, a novel method is proposed to reduce the zero-order vibration of PMSMs by injecting harmonic currents. Based on the zero-order natural frequency of the PMSM stator, this method will selectively adjust the frequency and amplitude of injected harmonic current to reduce vibration. The theoretical basis, simulation verification, and experimental implementation of the novel method are thoroughly researched, exhibiting its ability to reduce zero-order vibration of PMSMs.

This study investigates the performance enhancement of wound field synchronous motors (WFSMs) through a design method that incorporates grain-oriented electrical steel (GOES). Cross-magnetization, resulting from the overlapping fluxes of the d- and q-axes, occurs within the rotor of the WFSM. Consequently, rotor design must enable optimal utilization of cross-magnetization to enhance electromagnetic performance. This study proposes an approach that uses the magnetic properties aligned with the easy axis of GOES, aiming to improve cross-magnetization utilization and reduce copper loss. Electromagnetic torque improvements are demonstrated by analyzing the magnetic flux path in comparison to models using non-oriented electrical steel (NOES). Furthermore, the role of cross-magnetization in performance enhancement is examined through a detailed analysis of the easy axis of GOES. Finally, the superiority of GOES is established through optimal rotor designs based on the type of electrical steel applied.

The sideband current harmonic components are inevitable in a permanent magnet synchronous motor (PMSM) drive system driven by a voltage-source inverter with space vector pulsewidth modulation (SVPWM). The research on the characteristics of sideband harmonic currents would provide guidance to the cause of electromagnetic force waves, vibration, and acoustic noise of the motor. In this article, the main components of sideband harmonic currents in PMSM drive by the SVPWM method are analytically derived. The frequency and spatial order of the sideband harmonics and radial electromagnetic force are calculated based on finite element analysis (FEA). Then, an experimental test of an eight-pole/48-slot interior PMSM with a voltage-source inverter controlled by the classical vector control strategy is carried out, and the phase stator currents, vibration response, and acoustic noise signals are collected. The results finally verify the accuracy of the derivation analysis of sideband currents and indicate the relation between sideband harmonic currents and electromagnetic vibration, which…

This article explores enhancing spoke-type flux-intensifying permanent magnet (SFI-PM) motor performance by strategically placing flux barriers (FBs) in the asymmetric rotor. Integrating multi-FBs into the conventional spoke-type PM (CSPM) rotor topology elevates the d-axis inductance ($L_{d} \gt L_{q}$), intensifying flux density and improving output torque while posing challenges like increased cogging torque, torque ripple, and harmonic distortion. An asymmetric rotor design is proposed to mitigate these issues by strategically placing a higher number of FBs along the forward direction (FD) of the spoke magnet axis (q-axis). Analysis reveals that this configuration reduces torque ripple and enhances output torque. A multi-objective genetic algorithm (MOGA) is applied to optimize this asymmetric design considering mechanical constraints. The analyses are validated by manufacturing and testing a 5-kW asymmetric SFI-PM machine with a higher number of FBs along the FD of the spoke magnet axis.

In this work, the reduced scalar potential is utilized to derive a finite element formulation capable of handling hysteretic nonlinear material laws. The Fréchet derivative is employed to deduce a quasi-Newton scheme in the weak form for solving the nonlinear partial differential equation that describes the magnetostatic field. Methods for evaluating the Jacobian are presented, and their performance is compared on a 3D domain under uniaxial and rotational excitation. The numerical results demonstrate the necessity of a flexible approximation to overcome the non-uniqueness of the Jacobian at reversal points that naturally occurs in hysteresis loops. Consequently, an exact or excessively localized evaluation would give rise to difficulties in states of material magnetization characterized by these reversal points.

The current, electromagnetic force, and dynamic displacement of the high-speed on/off valve’s (HSV) electromechanical converter under stable working cycle are significantly different from those under the initial movement cycle. This phenomenon determines whether the electromechanical converter can continue to operate stably, and it also leads to temperature rise and high energy consumption over long periods of time. Therefore, in this study, a high-precision model is proposed that can fully analyze the characteristics of the electromechanical converter under multiple motion cycles with the consideration of the effects of eddy current and hysteresis. First, the hysteresis loop of the material is tested, and the Jiles–Atherton hysteresis model is identified based on the test data and verified through experiments. Second, the fundamental reasons for the differences in current and electromagnetic forces between initial motion and stable motion are analyzed. On this basis, a new law of dynamic evolution of electromechanical converters under multiple motion cycles is discovered. Finally,…

To address the nonlinear, multimodal, and computationally intensive challenges inherent in the optimal design of metasurface absorbers for radio frequency (RF) energy harvesting, we propose an innovative hybrid algorithm that combines particle swarm optimization (PSO) and fireworks algorithm (FWA). The proposed hybrid algorithm features several enhancements: 1) a quasi-scaling (Q.S.) mechanism, inspired by the frequency response of electromagnetic (EM) devices shifting with the scaling of physical parameters, is developed to balance the exploration and exploitation searches; 2) a self-adaptive inertia weight is introduced to enhance the convergence speed; and 3) an elite-preservation strategy is employed to ensure a global convergence. The effectiveness and merits of the proposed algorithm are validated by solving first mathematical test functions; then, two practical cases: a multi-band absorber (1.8–3 GHz, 5.85 GHz) and a broadband absorber (8–15 GHz), where a new dual-polarized metasurface absorber topology is employed. Both cases are efficiently optimized, demonstrating high…

This article presents the electromagnetic design optimization of a permanent magnet synchronous generator (PMSG) based on machine learning (ML). First, the optimization methodology is presented; then, a correlation and a sensitivity analysis are carried out to determine the set of design variables. The optimization goal is maximizing efficiency, which is equivalent to minimizing electrical PMSG losses. It also considers the core and copper materials by minimizing their weight. A deep neural network (DNN) architecture is developed and trained using PMSG 2D-FE data. The DNN is based on the nonlinear rectified linear unit (ReLU). The resulting DNN was later used to construct the PMSG objective function, which was then solved using non-sorting genetic algorithms. Numerical results and comparisons between two genetic algorithms are given to demonstrate the validity of the proposed approach.

The extended Kalman filter (EKF) is widely applied in the permanent magnet synchronous motor (PMSM) position estimation method. However, the estimation accuracy will be degraded, when measurement noise is not 0-mean random noise. To solve this problem, this article proposes an EKF algorithm with moving horizon estimation (MHE) to estimate the rotor position of PMSM more accurately. The proposed MHE EKF algorithm uses the concept of a moving time-domain window to estimate the motor operating status by integrating the window information of the N moments. By establishing a cost function and adding random noise to replace the measurement error, the prediction problem is transformed into an optimization problem. The simulation and experiment results show that this algorithm can effectively improve the accuracy of estimation position.

This article presents a numerical approach for computing and synthesizing the force between two permanent magnets (PMs) under general conditions. Initially, a general formula for determining the interactive force between two arbitrary PMs is derived, resulting in a unified 6-D integral for any magnet pairs. Following this, a computational algorithm utilizing Monte Carlo (M-C) integration for solving the integral is developed. The significance of the presented method is twofold. First, the derived formula and algorithm are unified, enabling the computation of forces between two magnets under general conditions, allowing for arbitrary shapes, magnetizations, and relative locations of the magnets. Second, the approach is applicable to the design synthesis problems, where the geometries of the magnets are to be designed to achieve the prescribed interactive force. Numerical examples are provided to demonstrate the generality and feasibility of the method for magnet-force analysis and synthesis. In addition, the accuracy and efficiency of the proposed approach are discussed and compared…

In order to model the magnetostrictive hysteresis behavior of grain-oriented electrical steel sheet (ESS) under the dc bias, a Jiles–Atherton (J–A) magnetostrictive model considering the effect of dc bias was constructed based on the J–A hysteresis model. First, according to the separation theory of loss, a dynamic J–A hysteresis model was established; then, considering the impact of dc bias and anisotropy, the expressions for effective magnetic field intensity and non-hysteretic magnetization strength were modified based on the free energy model; next, the improved J–A hysteresis model was combined with the model of secondary domain reversal considering the magnetostrictive hysteresis behavior to construct the J–A magnetostrictive model considering the effect of dc bias; finally, the particle swarm optimization (PSO) algorithm was used to extract parameters of the model combined with experimental data, and the model was verified for accuracy by comparing it with experimental data. It can model the magnetostriction of an oriented ESS plate in a complex working environment.

Electrical tuning of magnetism is crucial for developing fast, compact, ultralow-power electronic devices. Multiferroics offer significant potential due to their ability to control magnetism via an electric field through magnetoelectric (ME) coupling, especially in layered ferroelectric/ferromagnet heterostructures. A key challenge is achieving reversible and stable switching between distinct magnetic states using voltage control. In this work, we present ferroelectric tuning of room-temperature magnetism in a 2-D layered ferromagnet. The energy-efficient control consumes less than 1 fJ per operation, which is normally in the order of several$10^{-3}$fJ, resulting in a ~43% change in magnetization. This tunable multiferroic interface and associated devices provide promising opportunities for next-generation reconfigurable communication systems, spintronics, sensors, and memories.

During the motor design stage, it is crucial to accurately predict the characteristics of the motor at various operating points. Performing finite-element analysis (FEA) for each point is time-consuming and impractical. Therefore, the motor parameters and losses are typically calculated for each load point and used to solve the voltage and torque equations, thereby reducing the time required for motor characteristic analysis. Thus, the accurate prediction of motor parameters is essential for optimizing the motor design. This study proposes a parameter estimation method for the design process of induction motors (IMs). Accordingly, the circuit parameters are estimated using a reduced amount of FEA data. A common approach for evaluating the circuit parameters of IMs is through locked-rotor and no-load tests. However, these methods have limitations, because they use a fixed frequency that may not be suitable for electric vehicle traction motors owing to their various driving points, high torque, and high power density. This article introduces an iterative method for estimating the…

This article introduces an innovative approach utilizing chaos game optimization (CGO) to the design of magnetic materials and plasma-constituted planar absorbers (PAs) and nonplanar absorbers (NPAs) operating within microwave frequencies. The core innovation lies in the meticulous selection of suitable magnetic materials to achieve optimal absorber performance metrics, including minimal reflectivity (MR), minimum thickness (MT), and maximum bandwidth (MBW). In the proposed model, a predefined set of magnetic materials with frequency-dependent medium properties, including permeability, is utilized to fine-tune parameters for respective layers of absorbers. Emphasizing the significance of magnetic materials, the proposed model reliably predicts the appropriate parameters for layered PAs. Furthermore, this study extends its optimization framework to NPAs, specifically focusing on pyramidal absorbers, and evaluates their performance using magnetic materials. A key advancement in this research is the integration of ferrite tile and plasma slabs in the NPAs, which significantly…

Tracking passive magnetic markers plays a vital role in advancing healthcare and robotics, offering the potential to significantly improve the precision and efficiency of systems. This technology is key to developing smarter, more responsive tools and devices, such as enhanced surgical instruments, precise diagnostic tools, and robots with improved environmental interaction capabilities. However, traditionally, the tracking of magnetic markers is computationally expensive due to the requirement for iterative optimization procedures. Moreover, these methods depend on the magnetic dipole model for their optimization function, which can yield imprecise outcomes due to the model’s significant inaccuracies when dealing with short distances between non-spherical magnet and sensor. Our article introduces a novel approach that leverages neural networks (NNs) to bypass these limitations, directly inferring the marker’s position and orientation to accurately determine the magnet’s five degrees of freedom (5 DoFs) in a single step without initial estimation. Although our method demands an…

Synchronous reluctance machines (SynRM) have received much research attention due to their simple structure, wide speed regulation ability, and no need for permanent magnet excitation. However, the SynRM still has the disadvantages of lower output torque, lower power factor, and lower efficiency compared to permanent magnet synchronous machines. In this paper, a novel SynRM with a rotor core made of grain-oriented (GO) silicon sheets (GO-SynRM) is proposed. By taking the merits of the high permeability in the rolling direction of GO silicon sheets, the d-axis magnetization characteristic of the SynRM has been improved. By taking the new rotor topology, the torque ability and power factor of the GO-SynRM can be improved compared to SynRM with a non-grain-oriented (NGO) silicon steel rotor core (NGO-SynRM). Moreover, the shape of the rotor flux barrier of SynRM has a significant impact on the performance of the machine since it determines the flux distribution. Therefore, the segmented linear interpolation method is proposed to determine the boundary of the rotor flux barrier and an…

In this paper, a high-power factor variable leakage flux permanent magnet (VLF-PM) motor is proposed for potential in-wheel applications. The key of this study is to investigate the regulated-flux-barrier (RFB) topology from the perspective of harmonics of air-gap flux density. Then, the derivation of the PM flux linkage expression and the analysis of factors influencing power factor (PF) are conducted in accordance with the principles of the VLF-PM motor. Additionally, the positioning of the regulated-flux-barrier is determined based on the peak of the high harmonic wave of the air-gap flux density. Subsequently, a noticeable decrease in the harmonic wave peak is observed following the implementation of the flux barrier, confirming the effectiveness of the theoretical analysis. The performance of the VLF-PM motor without regulated-flux-barrier and with regulated-flux-barrier is then assessed using the finite element method (FEM), including the air-gap flux density and harmonic distributions, torque and flux regulation ability, power factor under different operating conditions, and…

Additive Manufacturing (AM) has recently been shown as a potential processing method to obtain bonded Nd-Fe-B magnets. Meanwhile, recycling is gaining prominence due to the increasing availability of end-of-life magnets. Thus far most efforts have aimed to obtain sintered magnets via the magnet-to-magnet approach, but recycling strategies can be also rethought towards the fabrication of bonded magnets instead of sintered ones. Our primary objective is to investigate the fabrication of bonded magnets via AM, using feedstocks composed of nanocrystalline powders obtained from scrap. For that purpose, Nd-Fe-B scrap magnets were subjected to hydrogen processing to obtain nanocrystalline powders. The nanocrystalline powders were then used to prepare feedstocks, from which 3D print recycled bonded magnets were fabricated via two AM techniques: Laser Powder Bed Fusion and Stereolithography. For both techniques the recycled nanocrystalline powders were shown to be adequate, with mean values of coercivity and remanence equal to 750 kA/m and 705 mT, respectively. By using feedstocks composed…

In this article, a novel hybrid multi-objective optimization (MOO) algorithm is proposed by combining an improved sparrow search algorithm (SSA) with an improved non-dominated sorting genetic algorithm (NSGA-II). The original SSA is improved by the introduction of population updating mechanism of moth-flame optimization (MFO) algorithm and by adopting adaptive mutation; meanwhile, NSGA-II is enhanced by using Latin hypercube sampling and dynamical selection mechanism of crossover and mutation operators. The performance of the proposed hybrid algorithm is verified using standard test functions and it is applied to the multi-objective optimal designs of TEAM22 benchmark problem and topology optimization problem of an electromagnetic actuator prototype. Numerical results demonstrate the effectiveness and superiority of the proposed algorithm.

As an emerging and highly promising magnetic levitation technology, superconducting (SC) electrodynamic suspension (EDS) can be applied to areas such as high-speed maglev transport, ultrahigh-speed electromagnetic propulsion, and launching. However, the low-damping characteristics of the SC EDS system lead to vibration and even suspension instability during its operation. Therefore, the low damping problem has been a key issue for the EDS system. Aiming to solve the instability problem of the EDS system for a high-speed maglev sled, this article proposes a passive damping scheme based on the permanent magnet damping conductive plate (PMDCP) structure, which utilizes PM Halbach arrays fixed on the sled to induce eddy currents in the conductive plates fixed along the track as the sled is traveling. First, the structure and principle of the PMDCP damping enhancement scheme are introduced, and the second-order vector potential (SOVP) is introduced to deduce the theoretical calculation (TC) formula of the electromagnetic force, and the 3-D finite-element analysis (FEA) is applied to…

This article proposed, optimized, and compared two dual-rotor axial-flux permanent magnet (PM) machines for all-electric aircraft (AEA) propulsion. First, the design requirements are determined, and the initial structures of the yokeless and segmented armature (YASA) machine and the axial-flux vernier PM (AFVPM) machine are designed with identical outer radius, inner radius, and axial length. Several features, including the Halbach array and PM skewing, are introduced to improve power density and efficiency. Then, to reduce the computational burden of finite element analysis (FEA), the surrogate models of machines are constructed by Box-Behnken design (BBD). The electromagnetic performances, such as induced voltage, torque characters, and efficiency of the proposed machines, are simulated. Subsequently, the discussions are carried out, where the strength and weakness of the two machines are evaluated. Finally, it is concluded that the YASA machine is a superior choice for AEA propulsion due to its higher output torque, power density, torque density, and efficiency when compared to…

Magnetic tape, hard disk drives, and NAND flash memory constitute the tiered storage system, also known as the storage pyramid. This review will cover the recent advancements and prospects of these technologies, explore the shifting dynamics of their interaction, and examine the evolving use cases in the artificial intelligence (AI) field. Additionally, it will briefly address the challenges faced by alternative storage technologies such as optical data storage and DNA data storage.

This article presents a design method of biplanar coils to realize precise compensation for residual magnetic fields inside magnetic shielding rooms (MSRs) based on an improved particle swarm optimization (IPSO) algorithm with the Moore-Penrose pseudoinverse. The mirror image method (IM) is introduced into the traditional target field method (TFM) to weaken the coupling effect between the magnetic shielding material and the magnetic field generated by the coil. An IPSO algorithm with the Moore-Penrose pseudoinverse is used to obtain the coils’ parameters, thus determining the shapes of the coils. The simulation results show that the maximum deviations of$B_{x}$and$B_{z}$coil designed by this method are improved by 74.7% and 59.5%, respectively.

Flux reversal permanent magnet (FRPM) motors have been perceived as promising candidates for various applications, such as electric vehicles and aerospace. However, FRPM motors usually confront low torque density due to an inherent characteristic of low utilization of permanent magnets. In this article, an uneven magnetomotive force shift design is employed for an FRPM motor to emerge new working harmonics and improve the torque density. Based on the general field modulation theory, the principle is discussed. Moreover, by finite element analysis, the electromagnetic performance comparisons are made among the proposed motor and its two counterparts. The results reveal that the proposed motor exhibits the highest average torque and efficiency.

This article introduces an ultra-thin self-resonant coupler using nanocrystalline flake ribbon (NFR) material for wireless power transfer (WPT). The self-resonant coupler has garnered certain attention in the industry due to its ability to eliminate the compensating capacitor, resulting in a notable increase in power density. However, most research endeavors have primarily focused on WPT systems operating at megahertz frequencies with low power levels. Nanocrystalline materials exhibit high magnetic saturation and lower core loss in comparison to conventional MnZn materials. In addition, NFR materials offer ultra-thin profiles and flexibility, enabling the creation of compact WPT systems. In this study, the self-resonant coupler is fabricated with a double-D (DD) structured, flexible printed circuit (FPC) pad and integrated NFR core. This configuration achieves a power output of 400 W at 32 kHz, rendering it suitable for flexible surface WPT charging systems within a thickness of 0.54 mm.

Hexagonal barium ferrites have a high magnetocrystalline anisotropy, resulting in a ferromagnetic resonance (FMR) in the microwave frequency range, making barium ferrites a useful material for electromagnetic (EM) absorbing applications above 10 GHz. Barium M-type ferrites were doped with titanium and manganese metal ions to reduce the frequency corresponding to the peak in imaginary magnetic permeability. The measured magnetocrystalline anisotropy also shows a similar reduction with the increased substitution of the iron with non-magnetic ions. This allows for composites containing Ti–Mn-doped M-type barium ferrite (BaM) to be tuned as EM absorbers in the 16–26-GHz range.

Model-free predictive current control (MFPCC) has the advantage of strong motor parameter robustness because of the unused motor parameter. However, the torque ripple of this method is extremely high since only seven basic voltage vectors are utilized. To bypass this shortcoming, an MFPCC with an extended control set for permanent magnet synchronous motors (PMSMs) is proposed in this article. First, an extended control set is constructed by the discrete space vector modulation (DSVM) technique. Then, a novel current gradient establishment approach is developed to void the current gradient update stagnation problem along with a high computational burden. After that, a vector preselection strategy is carried out to reduce the candidate voltage vector number, thus dropping computation cost. Finally, compared experiments of the conventional MFPCC and the proposed method are implemented in a 2 kW PMSM drive experimental platform to validate the effectiveness and feasibility of the proposed method.

Transformers often encounter electromagnetic transients, such as ferromagnetic resonance and inrush currents. An accurate low-frequency modeling of transformers is essential for analyzing power system faults. However, the lack of accurate magnetic characteristic modeling in most commercial software results in the electromagnetic transient calculations of the shell-type transformer remaining challenging. In this article, a low-frequency shell-type transformer model for analyzing electromagnetic transients is proposed. By combining the static Jiles-Atherton (J-A) hysteresis model with loss separation theory, a modified dynamic J-A hysteresis model is established. The nonlinear excitation inductance module considering loss and hysteresis characteristics is developed. An improved topology-based shell-type transformer model is established based on the duality principle. The inrush current test results of shell-type transformers verified the accuracy of the proposed model.

Direct-drive wave energy converter (DDWEC) is more widely used due to its simple structure and high conversion efficiency. Different kinds of linear machines are used in DDWEC to improve the power density. Among them, transverse flux linear machine uses perpendicular magnetic flux path and axial stacked silicon steel sheets to reduce iron loss and enhance power density. In this paper, a flux-reversal transverse flux permanent magnet linear generator is proposed. The winding connection type of this configuration is elaborated. Circumferential three-phase type, axial three-phase type and the proposed one are compared to obtain higher power density and lower thrust ripple. The proposed three-phase winding configuration has the lowest thrust ripple (0.76%) and decent average thrust (247.01N). A prototype was manufactured and an experimental testing platform was built. The measured back EMF values in the experiment showed a consistent trend with the FEA values. Owing to the convenience in changing the armature winding connection and excitation winding connection, the proposed machine has…

A novel thermodynamically consistent macroscopic magnetic hysteresis model is presented. Magnetization is calculated from the reversible part of the magnetic field, while the evolution law of the irreversible part involves physically meaningful material constants: the coercive field and the initial susceptibilities of the hysteretic and anhysteretic curves. It is possible to invert the model through an iterative procedure, allowing either the magnetic field or the flux density as an input to the model. The model is tested on both soft and hard magnetic materials for major and minor loops.

With rapidly increasing edge intelligence, domain-specific computers in heterogeneous fabrics are likely to rule the roost. Judicious choice of device technology and computational paradigms can drastically reduce the size, weight, and power (SWaP) of such computers, while also making them fully autonomous (clockless) and resilient against malicious attacks. Here, we review the promise of an emerging device technology –magnetic straintronics– in implementing extremely energy-efficient hardware for a wide variety of computing paradigms: neuromorphic, probabilistic, Bayesian belief networks, Boltzmann and Ising machines, matrix multipliers for deep learning networks, and reconfigurable stochastic neurons for p-computing. Magnetic straintronics has two important features – non-volatilty and very low energy expenditure – which are conducive to edge processing. We discuss some unconventional computing paradigms implemented with magnetic straintronics, while pointing out the remarkable energy efficiency in all cases.

Aiming at the common faults of demagnetization and rotor eccentricity (RE) in permanent magnet (PM) synchronous motor, the electromagnetic field analysis under the faults and a nonintrusive fault diagnosis and localization technique are investigated in this article. Initially, a PM segmentation model is developed, and a general solution is derived for surface-mounted PM motor with local irreversible demagnetization fault (LIDF) accounting for core saturation, which can precisely simulate LIDF in arbitrary regions. Additionally, an equivalent transformation method is introduced to emulate the nonuniform magnetic field arising from RE. The validity and correctness of the proposed models are confirmed by finite element analysis and experiments. Furthermore, the effects caused by the faults on the no-load electromagnetic performance are analyzed, based on which a diagnosis technique for rotor faults using coil BEMF (CBEMF) is proposed. The localization of the LIDF is achieved by integration with the least square method, and the eccentric angle and ratio are determined by combining with…

The conventional mechanical and power electronic (MPE) hybrid dc circuit breakers (DCCBs) face challenges in balancing efficiency and performance. This study proposes an efficient MPE hybrid DCCB to address these limitations. The proposed topology reduces ON-state losses to a negligible magnitude utilizing only mechanical switches, such as the residual current switch (RCS), mechanical fast switch (MFS), and monostable mechanical switch in the main branch. Additionally, it reduces the number of semiconductor devices by employing a series connection between the MFS and the main current breaker (MCB). The dc interruption capability of the proposed MPE hybrid DCCB topology was verified through simulations based on an equivalent electric circuit, while its medium-voltage (MV)-class performance was confirmed through dc interruption tests. The proposed MPE hybrid DCCB offers an effective solution for improving the performance and reliability of dc power systems.

A new volume integral equation (VIE) approach is introduced to study transcranial magnetic stimulation (TMS) and high-contrast media at low frequencies. This new integral equation offers a simple solution to the high-contrast breakdown observed in low-frequency electric field (E-field) dosimetry of conductive media. Specifically, we employ appropriate approximations that are valid for low frequencies and stabilize the VIE by introducing a basis expansion set that removes solutions associated with high eigenvalues in the equation. The new equation is devoid of high-contrast breakdown and does not require the use of auxiliary surface variables or projectors, providing a straightforward practical solution for the VIE analysis of TMS. Our results indicate that the novel VIE formulation matches boundary element, finite element, and analytical solutions. This new VIE represents a first step towards including anisotropy in integral equation E-field dosimetry for brain stimulation.