In linear transport systems, varying the transport speed according to task demands is important for improving overall efficiency. This study proposes a magnetic lead screw structure that achieves stepwise variation in the nut's axial speed, determined by its position and without the need for active control. The proposed system consists of multiple screw shaft sections with different numbers of thread starts and lead configurations, which are axially connected and driven at a constant rotational speed. A conceptual design is presented, and the effect of thread variation on thrust is evaluated through magnetic field analysis. The results indicate that the thrust transmission remains effective even when the number of thread starts differs between the screw and the nut. Furthermore, dynamic simulations based on a two-mass model confirmed that stepwise changes in linear velocity can be achieved without varying the motor rotational speed.
Background: Polymeric hollow fibers containing magnetic nanoparticles (MNPs) have potential for use as oxygen-selective gas separation membranes. Objective: To demonstrate the fabrication of MNP-containing polymeric hollow fibers using microfluidic devices and to evaluate the effects of process parameters on fiber geometry. Methods: A polymer solution containing MNPs and liquid paraffin were used as the shell and core fluids. Hollow fibers were formed via nonsolvent-induced phase separation (NIPS). Effects of core/shell flow-rate ratios were examined. Results: MNP-containing polymeric hollow fibers were successfully fabricated, and their inner diameter increased as the core/shell flow-rate ratio increased. Conclusions: The proposed method enables low-cost fabrication and structural control of MNP-containing polymeric hollow fibers.
This paper presents the design and performance evaluation of a compact hybrid fractal-based reconfigurable microstrip antenna optimized for millimeter-wave (mmWave) RF energy harvesting in low-power Internet of Things (IoT) applications. The proposed antenna employs a Minkowski–Sierpinski hybrid fractal geometry implemented on a Rogers RT/duroid 5880 substrate to achieve miniaturization, wideband operation, and enhanced radiation performance within the 25–35 GHz frequency range. Frequency reconfigurability is introduced using strategically positioned PIN diodes, enabling dynamic tuning across multiple mmWave sub-bands to adapt to varying ambient RF conditions. The proposed design demonstrates the potential for RF energy harvesting in IoT applications based on simulation and analytical evaluation.. The antenna design was developed and analyzed using ANSYS HFSS full-wave electromagnetic simulations. Performance metrics including reflection coefficient (S 1 1 ), voltage standing wave ratio (VSWR), gain, and radiation characteristics were evaluated for multiple switching configurations. The proposed design achieves a reflection coefficient below −14 dB, VSWR less than 2 across the operational band, and a peak gain of 5.1 dBi, demonstrating strong impedance matching and stable radiation behavior. The hybrid fractal configuration improves current distribution, enhances effective electrical length, and supports multiband resonance without increasing physical dimensions. Furthermore, the antenna's reconfigurable capability enhances RF energy capture efficiency in dynamically varying 5G environments, making it suitable for self-powered IoT sensor nodes. The proposed design establishes a scalable framework for compact, energy-aware, and frequency-agile antenna systems supporting next-generation sustainable wireless networks.
Acquiring low-cost magnetic flux leakage (MFL) signals while accurately inverting defect geometric parameters remains a significant challenge in magnetic flux leakage non-destructive testing. To address this issue, this paper proposes a simulation-driven defect inversion framework, termed the Simulation-Driven Magnetic Dipole Convolutional Neural Network (SDMD-CNN), which integrates an improved magnetic dipole model with convolutional neural networks. By incorporating Gaussian convolution into the conventional magnetic dipole model, a high-fidelity simulated dataset consisting of 2500 sets of parameterized MFL signals with accurately labeled defect widths and depths is constructed. A one-dimensional convolutional neural network is designed to learn the nonlinear mapping between MFL signals and defect geometric parameters, enabling reliable prediction of defect width and depth on an independent test dataset. The proposed method achieves coefficients of determination of R 2 = 0.9837 and R 2 = 0.9960 for width and depth estimation, respectively, and demonstrates strong robustness under severe noise conditions with a signal-to-noise ratio of −5 dB. Experimental validation further shows that, without training on real defect samples, the proposed model attains an average relative error below 6% when applied to actual measurements, indicating strong simulation-to-reality transferability. These results demonstrate that the proposed approach provides an effective solution for quantitative defect inversion in MFL testing and offers a low-cost strategy for constructing labeled training data.
Background With the continuous upgrading of global energy efficiency standards, high-efficiency high-voltage motors have become dominant in the market. However, the open slots of stator cores in such motors lead to uneven air-gap permeability, reducing motor efficiency and causing electromagnetic vibration, which affects operational reliability. Objective This study aims to investigate the impact of replacing conventional insulating slot wedges with magnetic slot wedges on the electromagnetic performance, losses, and vibration characteristics of a 1.4 MW high-voltage flameproof asynchronous motor, providing a basis for the proper selection and application of slot wedges. Methods A two-dimensional transient magnetic field finite element model was established, and a field-circuit coupling method was applied. Comparative analyses were conducted on magnetic flux density, magnetic field distribution, speed and torque response, current response, and air-gap magnetic field harmonics for both conventional and magnetic slot wedges. The influence of magnetic slot wedges on motor parameters such as air-gap coefficient, tooth harmonics, stator slot leakage reactance, maximum torque, no-load current, starting performance, and various losses was quantitatively evaluated. Results The results indicate that magnetic slot wedges effectively improve the distribution of air-gap magnetic flux density, reduce harmonic content and amplitude, decrease no-load current and additional losses, and enhance motor power factor and efficiency. However, increasing the magnetic permeability of the slot wedges reduces the maximum torque and starting torque of the motor. Conclusions Magnetic slot wedges can significantly optimize the electromagnetic performance and reduce losses in megawatt-level high-voltage flameproof motors. Nevertheless, their negative impact on torque characteristics must be considered. Comprehensive evaluation of electromagnetic parameters and performance is essential for the appropriate application of magnetic slot wedges.
Background Superconducting magnetic bearings (SMBs) using high-temperature superconductors (HTS) offer omnidirectional stability without control, but face issues with HTS bulk material and cooling costs. Objective This study investigates whether the restoring force can be enhanced using the same HTS by controlling the magnetic flux penetrating the HTS and hybridizing it with a passive magnetic bearing (PMB). Methods Permanent magnets (PM) were placed in the stator section of the SMB. The radial and axial characteristics were analyzed when forming a PMB with part of the levitated rotor. Changes in restoring force characteristics and vibration characteristics were investigated. Results An improvement in radial restoring force was confirmed. Although axial restoring force decreased, the HTS pinning characteristics were found to suppress this reduction. An increase in damping force was also observed in dynamic characteristics. Conclusions These results demonstrate the usefulness of hybrid magnetic bearings combining annular permanent magnets and superconductors. Note This study does not contain any studies with human or animal subjects performed by any of the authors.
Background Traditional automotive anti-collision beams usually rely on the plastic deformation of metal parts to absorb impact energy, which often leads to irreversible structural damage and high repair costs. Objective To address these limitations, this paper proposes a novel crash beam design based on eddy current damper (ECD), which replaces the traditional energy absorption method with a non-contact electromagnetic damping mechanism. Methods First, the basic structure and operating principle of the ECD were elaborated in detail. The accuracy of its finite element model was verified through impact tests. Subsequently, an electromagnetic-structural-thermal Multiphysics coupled model was established to analyze the ECD's dynamic response, deformation patterns, and thermally induced demagnetization effects under high-speed impact conditions. Results Compared with traditional designs, the ECD-based anti-collision beam significantly improves energy absorption efficiency and effectively reduces damage to the vehicle body during collisions. In addition, the ECD exhibits excellent impact resistance during collisions, with its damping force being minimally affected by the impact temperature rise and the damping attenuation phenomenon being insignificant. Conclusions The applicability of ECD in automotive crash beams is demonstrated.
Background Functional materials such as piezoelectrics can be used as sensors. Increases in the performance and output power of functional materials will open up new applications. Piezoelectric materials generate electricity when pressure is applied or when they are deformed. Piezoelectrets are materials that store electric charge when a high voltage is applied and generate electricity when electrodes are brought closer or moved apart. This study focused on inexpensive, mass-producible general-purpose rubber. Previously conducted testing with general-purpose rubber mixed with various amounts of lead zirconate titanate revealed that rubber without lead zirconate titanate can also generate electricity.Objective In this study, a piezoelectret composed of isobutylene isoprene rubber (IIR) and fluorinated ethylene propylene film (FEP) is proposed. IIR is made of commonly used materials. The power generation model of the proposed piezoelectret is developed and evaluated.Methods Surface potential measurements and a cyclic forced overload experiment were conducted. The results obtained using the power generation model for the piezoelectret were compared to experimental results.Results The surface potential and piezoelectric stress constant d33 decreased immediately after the corona charge process but were maintained beyond day 7. The average d33 value after 2 weeks was 475.2 pC/N, which is much higher than that for polyvinylidene fluoride (similar to 40 pC/N), a representative piezoelectric material. The results obtained using a power generation model that considers piezoelectric- and electrostatic-type generation showed qualitatively reasonable agreement with the experimental results.Conclusions A piezoelectret made of IIR has potential for high power generation. It was confirmed that piezoelectrets based on general-purpose rubber exhibit high power generation performance. The power generation model showed qualitative agreement with the experimental results.
Background The demand for biocompatible materials has increased substantially in recent years as a result of the growing complexity and precision requirements of medical devices, particularly implants. However, the process of manufacturing these materials remains challenging, particularly in terms of preserving biocompatibility while attaining a high level of surface quality. Objective The objective of this study is to present a concise summary of Powder-Mixed Electrical Discharge Machining (PMEDM) and Electrical Discharge Machining (EDM) for biomedical materials, with an emphasis on their potential to circumvent the constraints of traditional methods. Methods In order to ascertain the capabilities, limitations, and contributions of EDM and PMEDM to biomedical applications, a review of recent studies and discussions was conducted. Results The results emphasize that EDM and PMEDM can efficiently process challenging biomedical materials without causing mechanical stress, while simultaneously enhancing surface characteristics and maintaining biocompatibility. These techniques demonstrate potential for improving the precision and quality of biomedical components. Conclusions EDM and PMEDM are prospective manufacturing techniques for biomedical applications, assuring the reliable biological integration of implants in clinical practice, long-term performance, and structural accuracy.
The paper aims at presenting the results from numerical studies of the heating in a low-voltage power distribution block at transient mode. For this purpose, a 3D computer model of the power distribution block in COMSOL software package has been developed. Coupled electric field – thermal field – fluid mechanics problem has been solved taking into account the constructive peculiarities of the block. The thermodynamic processes within the volume of the terminal block have been taken into account. The heat transfer from the surface of the power distribution block and the current-carrying elements to the surrounding environment through radiation and convection have also been accounted for. Results have been obtained for the heating of the power distribution block in transient mode under different current loads. The comparison between computed and experimental results shows good agreement. The developed model can be used for prediction of the thermal behavior of the power distribution block, as well as for estimating the maximal current that does not lead to a temperature rise above the standard limited value.
Background Torque ripple in Interior Permanent-Magnet (IPM) Machines is influenced by the spatial harmonic components of the air-gap flux density and related magnetic field harmonics, which limit its performance gains. An effective solution through rotor structure optimization is urgently required. Objective This study introduces a new rotor topology suitable for IPM Machines. The goal is to suppress spatial harmonics of air-gap flux density and magnetic field harmonics through structural improvements, thereby effectively reducing torque ripple. Methods Design appropriate flux barriers with triangular slots to alter the leakage flux path and inhibit harmonic components. Derive the torque ripple generation mechanism of IPM machines and develop a mathematical model that reveals the relationship between rotor modification and torque ripple. Optimize the design of an 18-slot, 8-pole IPM machine and compare it with the existing design. Analyze key performance metrics including air-gap flux density, no-load back-EMF, and torque ripple using finite-element method (FEM). Results FEM analysis results show that the proposed rotor topology can significantly decrease the spatial harmonic components of the air-gap flux density and suppress the magnetic field harmonics associated with torque ripple, achieving a notable torque ripple reduction. Conclusions The proposed new rotor topology is well-designed and effective. It offers a dependable solution for reducing torque ripple in IPM Machines and has practical reference value for optimizing their performance.
Background Accurate acquisition of the initial rotor position is crucial for permanent magnet synchronous motor (PMSM) control systems. Starting the motor without initial position detection may lead to excessive current or unexpected reverse rotation. However, the traditional voltage pulse injection method often suffers from insufficient accuracy and magnetic pole misidentification, which reduces the reliability and practical applicability of the detection results. Objective To eliminate the magnetic pole misidentification inherent in the traditional voltage pulse injection method and further improve detection accuracy, an improved method based on voltage pulse injection is proposed. Methods Firstly, to eliminate the magnetic pole misidentification observed in the traditional method, a magnetic pole identification (MPI) strategy is introduced. The MPI strategy determines whether the detected initial rotor position is consistent with the rotor polarity. If a polarity reversal is identified, the detected position is corrected by adding 180°. Next, to reduce the influence of sampling errors on detection accuracy, the magnetization effect of the injected current is enhanced. The difference among the feedback current responses becomes more pronounced, thereby mitigating the influence of sampling errors. Finally, a curve-fitting method is employed to further improve the detection accuracy. By utilizing the acquired current and position information, the current response curve near the actual rotor position is fitted, and the position corresponding to the peak current is selected as the final detection result. Results The effectiveness of the improved method has been validated through experiments conducted on a PMSM drive platform. The experimental results demonstrate that the improved method reduces the position detection error by an average of 32% and eliminates magnetic pole misidentification in the traditional method. Conclusions Compared with the traditional voltage pulse injection method, the improved method effectively enhances the accuracy of initial position detection, providing a strong basis for the stable operation of PMSM.
Electromagnetic vibration is a primary factor affecting the performance of permanent magnet (PM) machines. Fractional-slot concentrated-winding (FSCW) permanent magnet (PM) machines are characterized by their use of specific pole-slot combinations, which enables them to achieve high torque density and excellent fault tolerance. High-order radial electromagnetic forces (REFs) can be modulated into lower-order components through the teeth modulation effect, thereby increasing machine vibration. In this paper, the modulation mechanism of stator teeth on REFs and machine vibration are validated through finite element analysis (FEA) and experiment. Based on these findings, a novel stator teeth structure design methodology is introduced. By introducing auxiliary slots into the stator teeth, the equivalent number of stator teeth is increased, thereby mitigating the effect of tooth modulation of higher-order REFs and reducing machine vibration. To optimize the vibration reduction effect of the novel stator structure, a parameter matching design is conducted by the Taguchi method. In this paper, the original machine is validated by both experiment and finite element analysis, while the optimized structure is verified only by finite element analysis. The FEA results demonstrate that the novel stator teeth structure design methodology effectively mitigates vibration levels in the FSCW PM machine while preserving machine performance.
In virtue of the exceptional material characteristics, Polyethylene (PE) components are broadly utilised in various engineering applications such as pressure-rated gas, water systems and sustainable energy systems, etc. However, during practical applications, PE components could be vulnerable to such damages as the Backside Wall-thinning Defect (BWD) which is resulted from the improper installation process or lateral impact, etc. The structural integrity and safety of PE components are severely threatened by the defect. Therefore, efficient testing, imaging and evaluation of BWDs are highly demanded for non-intrusive inspection of PE components. Complementary to other non-destructive evaluation techniques, Microwave Testing (MWT) has been found to be superior in the inspection of dielectric structures. In light of this, in this paper the visualised evaluation of BWDs in the planar PE component via the Ka-band MWT is intensively scrutinised. In an effort to evaluate the planar dimension and depth of a BWD, the 3D profiling of the BWD based on the U-Net is investigated together with the multiple hypothesis test-based signal-feature selection. The feasibility and applicability of MWT, along with Ka-band (26.5 similar to 40 GHz) microwave reflectometry and the proposed algorithms, for the detection, visualisation, and assessment of BWDs in PE components are demonstrated by the experimental results.
The Halbach array arrangement optimizes the magnetic field distribution and enhances the conversion efficiency of electromagnetic energy conversion. In this experiment, the Halbach array arrangement was used to design and build a microgenerator system that integrates three parts: brushless motor drive, energy conversion, and high-precision measurement and recording. By innovatively combining field-oriented control (FOC) with an Arduino high-precision acquisition system, real-time precise measurement of mechanical input power and electrical output power was achieved. The influence of ten key factors, including the properties of the magnetic field lines, air gaps, and coils, on energy conversion efficiency was systematically investigated. The performance advantages of the Halbach array in improving energy conversion efficiency were verified. At the optimal parameter combination (air gap 1 mm, strong magnet, 6 coils, load 30 Omega, speed 360 r/min), the energy conversion efficiency reached 83.9%, about 20% higher than the traditional arrangement, providing experimental basis for efficiency optimization design of micro-generators.
Purpose: To develop and evaluate an embedded Traffic Sign Recognition (TSR) system for electromobility applications, emphasizing the role of realistic data augmentation in improving model generalization.Methods: A two-stage pipeline was deployed on a Raspberry Pi with Intel Movidius NCS2. It utilizes a fine-tuned SSD MobileNetV2 detector and a lightweight CNN classifier. The model was trained on 60,000 European traffic signs using context-aware augmentations including brightness variation, Gaussian blur, and contrast adjustment.Results: The detection network achieved a mean average precision of 0.93 at IoU=0.5. The classification module exceeded 95% accuracy in real-world scenarios. The integrated system sustained real-time operation at 12-15 fps, maintaining high accuracy within the strict thermal and power constraints of the embedded platform.Conclusions: Context-aware data augmentation significantly mitigates overfitting and improves robustness against environmental domain shifts. The proposed architecture ensures reliable TSR performance suitable for automotive mechatronics and advanced driver assistance systems (ADAS).
Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) have shown great potential in biomedical applications, yet conventional micro-scale PMUTs face challenges due to thick diaphragms and large membrane dimensions, which limit electromechanical coupling and reduce acoustic output. Also, full-area electrodes often excite unwanted higher-order vibration modes, while small electrodes limit the effective coupling. Thus, this research offers a solution to these problems by proposing a Nano-Scale Circular Double-Lamination AlN-based PMUT design. The proposed design reduces the diaphragm radius to 500 nm, improving strain transfer and electromechanical coupling. Additionally, this design adopts a partial electrode configuration of 156.25 nm with a top central electrode to enhance the electric field, while eliminating higher-order vibration modes and maximizing displacement at the diaphragm. Moreover, PZT's complex perovskite crystal structure and polarization mechanisms cause a high dielectric constant and dielectric losses, which restrict its use in implantable devices. Thus, this design uses lead-free Aluminum Nitride (AlN) with a wurtzite crystal structure, which provides low dielectric loss and ensures efficient energy conversion even at high frequencies. COMSOL Multiphysics simulations demonstrate a resonant frequency of 18.883 MHz, a broad bandwidth of 10 MHz, an energy density of 1.8 J/m 3 , and high central displacement, making the device ideal for high-frequency superficial clinical imaging and wearable biomedical applications.
In order to further improve motor output torque, a harmonic-oriented design and analysis method is proposed for a dual-airgap flux modulated permanent magnet (FMPM) motor. In this paper, based on flux modulation theory, airgap flux harmonics are investigated, and the torque generation mechanism under different operation modes is analyzed in detail. Also, the leading airgap flux harmonics have a significant influence on the motor output torque. Then, numerical optimization methods are employed to specifically optimize key design parameters such as the tooth widths of inner and outer rotors, aiming to increase leading airgap flux harmonics under different operation modes. The results indicate that the motor performance following optimization demonstrates a significant enhancement in the effect of specific working harmonics, thereby improving the torque characteristics of the motor. The prototype was fabricated and tested, verifying the feasibility of the proposed DSFMPM motor and the effectiveness of the harmonic-oriented optimization design. This research not only elucidates the relationship between the mechanism of torque generation, airgap harmonics, and motor design parameters but also provides a new perspective and methodology for the design of efficient and high-performance dual-stator motors.
This study focuses on optimizing a high-speed multiphase electrical machine intended for aerospace power generation (2.25 MW/15,000 rpm). The proposed approach relies on analytical modeling to capture both electromagnetic and thermal phenomena. A direct stator winding cooling strategy, based on oil circulation within the slots and end-windings, is investigated. The objective is to minimize the mass of the active components while satisfying specific design constraints. To ensure fault tolerance, the influence of the number of phases and the winding distribution on machine performance is analyzed. Particular attention is devoted to the machine's ability to withstand short-circuit currents.
