Search Results (4,793)

To enhance the electromagnetic performance of flat-wire permanent magnet synchronous motors, three different groove structures were designed for the rotor, and a multi-objective optimization algorithm combining a genetic algorithm (GA) with the TOPSIS method was proposed. Firstly, an 8-pole 48-slot flat-wire motor model was established, and the cogging torque was analytically calculated to compare the motor’s performance under different groove schemes. Secondly, global multi-objective optimization of the rotor groove dimensions was performed using a combined simulation approach involving Maxwell, Workbench, and Optislang, and the optimal rotor groove size structure was selected using the TOPSIS method. Finally, a comparative analysis of the motor’s performance under both rated-load and no-load conditions was conducted for the pre- and post-optimization designs, followed by verification of the mechanical strength of the optimized rotor structure. The research results demonstrate that the combined optimization approach utilizing the genetic algorithm and the TOPSIS method significantly enhances the torque characteristics of the motor. The computational results indicate that the average torque is increased to 165.32 N·m, with the torque ripple reduced from 28.37% to 13.32% and the cogging torque decreased from 896.88 mN·m to 187.9 mN·m. Moreover, the total distortion rates of the air-gap magnetic flux density and the no-load back EMF are significantly suppressed, confirming the rationality of the proposed motor design. Full article

This study investigates the sustainable production of NdFeB permanent magnets using powder extrusion molding (PEM) with in situ magnetic alignment, utilizing recycled powder from an end-of-life (Eol) wind turbine magnet obtained via hydrogen processing of magnetic scrap (HPMS). Finite Element Method (FEM) simulations were conducted to design and optimize alignment tool geometries and magnetic field parameters. A key challenge in the PEM process is achieving effective particle alignment while the continuous strand moves through the magnetic field during extrusion. To address this, extrusion experiments were performed using three different alignment tool geometries and varying magnetic field strengths to determine the optimal configuration for particle alignment. The experimental results demonstrate a high degree of alignment (B_r/J_s = 0.95), exceeding the values obtained with PEM without an external magnetic field (0.78). The study confirms that optimizing the alignment tool geometry and applying sufficiently strong magnetic fields during extrusion enable the production of anisotropic NdFeB permanent magnets without post-machining, providing a scalable route for permanent magnet recycling and manufacturing. Moreover, PEM with in situ magnetic particle alignment allows for the continuous fabrication of near-net-shape strands with customizable cross-sections, making it a scalable approach for permanent magnet recycling and industrial manufacturing. Full article

The growing need for high-efficiency and reliable propulsion systems in naval applications, particularly within the evolving landscape of submarine warfare, has led to an increased interest in multiphase Permanent Magnet AC motors. This study presents a modelling and simulation approach for a 3MW, seventeen-phase Permanent Magnet AC motor designed for submarine propulsion, integrating an AI-based drive control system. Despite the advantages of multiphase motors, such as higher power density and enhanced fault tolerance, significant challenges remain in achieving precise torque and variable speed, especially for externally mounted motors operating under deep-sea conditions. Existing control strategies often struggle with the inherent nonlinearities, unmodelled dynamics, and extreme environmental variations (e.g., pressure, temperature affecting oil viscosity and motor parameters) characteristic of such demanding deep-sea applications, leading to suboptimal performance and compromised reliability. Addressing this gap, this research investigates advanced control methodologies to enhance the performance of such motors. A MATLAB/Simulink framework was developed to model the motor, whose drive system leverages an AI-optimised dual fuzzy-PID controller refined using the Harmony Search Algorithm. Additionally, a combination of Indirect Field-Oriented Control (IFOC) and Space Vector PWM strategies are implemented to optimise inverter switching sequences for precise output modulation. Simulation results demonstrate significant improvements in torque response and control accuracy, validating the efficacy of the proposed system. The results highlight the role of AI-based propulsion systems in revolutionising submarine manoeuvrability and energy efficiency. In particular, during a test case involving a speed transition from 75 RPM to 900 RPM, the proposed AI-based controller achieves a near-zero overshoot compared to an initial control scheme that exhibits 75.89% overshoot. Full article

Electromagnetic pneumatic microvalves, widely used in knitting machines, typically operate based on a spring-return mechanism. When the coil is energized, the electromagnetic force overcomes the spring force to attract the armature, opening the valve. Upon de-energization, the armature returns to its original position under the restoring force of the spring, closing the valve. However, most existing electromagnetic microvalves adopt a radially asymmetric magnetic yoke design, which generates additional radial forces during operation, leading to armature misalignment or even sticking. Additionally, the inductance effect of the coil causes a significant delay in the armature release response, making it difficult to meet the knitting machine’s requirements for rapid response and high reliability. To address these issues, this paper proposes an improved electromagnetic microvalve design. First, the magnetic yoke structure is modified to be radially symmetric, eliminating unnecessary radial forces and preventing armature sticking during operation. Second, a permanent magnet assist mechanism is introduced at the armature release end to enhance release speed and reduce delays caused by the inductance effect. The effectiveness of the proposed design is validated through electromagnetic numerical simulations, and a multi-objective genetic algorithm is further employed to optimize the geometric dimensions of the electromagnet. The optimization results indicate that, while maintaining the fundamental power supply principle of conventional designs, the new microvalve structure achieves a pull-in time comparable to traditional designs during engagement but significantly reduces the release response time by approximately 80.2%, effectively preventing armature sticking due to radial forces. The findings of this study provide a feasible and efficient technical solution for the design of electromagnetic microvalves in textile machinery applications. Full article

The efficiency of electric motors is highly dependent on their operating temperature, with lower temperatures contributing to enhanced performance, reliability, and extended service life. This study presents a comprehensive review of state-of-the-art cooling technologies and evaluates their impact on the thermal behavior of a commercial motor–generator system in high-demand applications. A baseline model of a permanent magnet synchronous motor (PMSM) was developed using MotorCAD 2023^® software, which was supported by reverse engineering techniques to accurately replicate the motor’s physical and thermal characteristics. Subsequently, multiple cooling strategies were simulated under consistent operating conditions to assess their effectiveness. These strategies include conventional axial water jackets as well as advanced oil-based methods such as shaft cooling and direct oil spray to the windings. The integration of these systems in hybrid configurations was also explored to maximize thermal efficiency. Simulation results reveal that hybrid cooling significantly reduces the temperature of critical components such as stator windings and permanent magnets. This reduction in thermal stress improves current efficiency, power output, and torque capacity, enabling reliable motor operation across a broader range of speeds and under sustained high-load conditions. The findings highlight the effectiveness of hybrid cooling systems in optimizing both thermal management and operational performance of electric machines. Full article

Interior-mounted permanent magnet (IPM) machines have been widely used in recent years due to their high efficiency, high torque/power densities, and so on. These machines can produce reluctance torque whereas their surface-mounted (SPM) counterparts cannot. Hence, IPMs are attractive in industrial applications that require high torque density. ${\mathrm{I}}_{\mathrm{d}}=0$ control is commonly adopted to drive permanent magnet (PM) machines, and the strategy is attractive due to its simplicity. However, although it is suitable for SPMs, adopting it in IPMs sacrifices the reluctance torque that can be obtained from the machine. Hence, it is vital to control IPMs using the maximum torque per ampere (MTPA) strategy. This paper adopts the MTPA strategy for a 4.1 kW prototype IPM machine. Test system configuration is discussed step by step by paying particular attention to potential practical issues and inspirational discussions on their solutions. The issues associated with misaligned rotor positions or whistling problems pertinent to inappropriate power conversion strategies are addressed to overcome such issues in practical IPM drives. Comprehensive discussions and extensive comparisons of well-matched simulation and experimental results of both ${\mathrm{I}}_{\mathrm{d}}=0$- and MTPA-controlled drives at different evaluation metrics will be quite insightful to achieve efficiency-optimized IPM drives. Full article

Recovering oil by fracturing fluid imbibition has demonstrated significant potential for enhanced oil recovery (EOR) in tight oil reservoirs. White mineral oil (WMO), kerosene, or saturated alkanes with matched apparent viscosity have been widely used as “crude oil” to investigate imbibition mechanisms in light shale oil or tight oil. However, the representativeness of these simulated oils for low-maturity crude oils with higher viscosity and greater content of resins and asphaltenes requires further research. In this study, imbibition experiments were conducted and T₂ and T₁–T₂ nuclear magnetic resonance (NMR) spectra were adopted to investigate the oil recovery characteristics among resin–asphaltene-rich Jimusar shale oil and two WMOs. The overall imbibition recovery rates, pore scale recovery characteristics, mobility variations among oils with different occurrence states, as well as key factors influencing imbibition efficiency were analyzed. The results show the following: (1) WMO, kerosene, or alkanes with matched apparent viscosity may not comprehensively replicate the imbibition behavior of resin–asphaltene-rich crude oils. These simplified systems fail to capture the pore-scale occurrence characteristics of resins/asphaltenes, their influence on pore wettability alteration, and may consequently overestimate the intrinsic imbibition displacement efficiency in reservoir formations. (2) Surfactant optimization must holistically address the intrinsic coupling between interfacial tension reduction, wettability modification, and pore-scale crude oil mobilization mechanisms. The alteration of overall wettability exhibits higher priority over interfacial tension in governing displacement dynamics. (3) Imbibition displacement exhibits selective mobilization characteristics for oil phases in pores. Specifically, when the oil phase contains complex hydrocarbon components, lighter fractions in larger pores are preferentially mobilized; when the oil composition is homogeneous, oil in smaller pores is mobilized first. Full article

Objectives: This study investigates whether scan time in the high-resolution magnetic resonance imaging (MRI) of human embryos can be reduced without compromising spatial resolution by applying zero-shot self-supervised learning (ZS-SSL), a deep-learning-based reconstruction method. Methods: Simulations using a numerical phantom were conducted to evaluate spatial resolution across various acceleration factors (AF = 2, 4, 6, and 8) and signal-to-noise ratio (SNR) levels. Resolution was quantified using a blur-based estimation method based on the Sparrow criterion. ZS-SSL was compared to conventional compressed sensing (CS). Experimental imaging of a human embryo at Carnegie stage 21 was performed at a spatial resolution of (30 μm)³ using both retrospective and prospective undersampling at AF = 4 and 8. Results: ZS-SSL preserved spatial resolution more effectively than CS at low SNRs. At AF = 4, image quality was comparable to that of fully sampled data, while noticeable degradation occurred at AF = 8. Experimental validation confirmed these findings, with clear visualization of anatomical structures—such as the accessory nerve—at AF = 4; there was reduced structural clarity at AF = 8. Conclusions: ZS-SSL enables significant scan time reduction in high-resolution MRI of human embryos while maintaining spatial resolution at AF = 4, assuming an SNR above approximately 15. This trade-off between acceleration and image quality is particularly beneficial in studies with limited imaging time or specimen availability. The method facilitates the efficient acquisition of ultra-high-resolution data and supports future efforts to construct detailed developmental atlases. Full article

Electromagnetic and magnetic devices are increasingly prevalent in sectors such as transportation, industry, and renewable energy due to the ongoing electrification trend. These devices exhibit nonlinear behavior, particularly under signals rich in harmonics. They require precise and appropriate modeling for accurate sizing. Identifying model-specific parameters, which depend on frequency, is crucial. This article focuses on a specific frequency range where a circuit model with series resistance and inductance, along with a parallel resistance to account for iron losses (${\mathrm{R}}_{\mathrm{iron}}$), is applicable. While the determination of series elements is well documented, the determination of ${\mathrm{R}}_{\mathrm{iron}}$ remains complex and debated, with traditional methods neglecting operating conditions such as magnetic saturation. To address these limitations, an innovative experimental method is proposed, comprising two main steps: determining the complex impedance of the magnetic device and extracting ${\mathrm{R}}_{\mathrm{iron}}$ from the model. This method aims to provide a more precise and representative estimation of ${\mathrm{R}}_{\mathrm{iron}}$, improving the reliability and accuracy of electromagnetic and magnetic device simulations and designs. The obtained values of the iron loss equivalent resistance are different by at least 300% than those obtained by an impedance analyzer. The proposed method is expected to advance the understanding and modeling of losses in electromagnetic and magnetic devices, offering more robust tools for engineers and researchers in optimizing device performance and efficiency. Full article

This article analyzes the operating principle of the BMM sensor emitter in order to improve the accuracy of the wireless determination of the BMM sensor coordinates under a massif of destroyed rock in the context of the problem of determining the shift of rocks during gold ore mining. Using numerical simulations, FEM has been developed to develop digital models reflecting individual cases of the propagation of the magnetic field of the emitter located in various geological conditions and positions relative to the rock surface and the vertical axis. The accuracy of determining the coordinates of the radio beacon in the rock has been analyzed, and data on the deviation of the coordinates of the peaks of the magnetic field strength from the radio beacon axis have been obtained in cases of a heterogeneous composition of the rock massif, the influence of the deviation of the emitter axis angle from the vertical, the influence of the unevenness of the collapse relief, and the influence of the superposition of fields from different radiation sources. A study has been carried out to determine the direction of the radio beacon search based on the resulting vector of the emitter’s magnetic field strength. Full article

The dynamic model of a wheeled wall-climbing robot exhibits stage-specific changes when traversing different types of obstacles and during various stages of obstacle negotiation. Previous studies often employed remote control methods for obstacle-crossing control, which fail to dynamically adjust the torque distribution of magnetic wheels in response to real-time changes in the dynamic model. This limitation makes it challenging to precisely control the robot’s speed and attitude angles during the obstacle-crossing process. To address this issue, this paper first establishes a staged dynamic model for the wall-climbing robot under typical obstacle-crossing scenarios, including steps, 90° concave corners, 90° convex corners, and thin plates. Secondly, an adaptive controller based on a radial basis function neural network (RBFNN) is designed to effectively compensate for variations and uncertainties during the obstacle-crossing process. Finally, comparative simulations and physical experiments demonstrate the effectiveness of the proposed method. The experimental results show that this method can quickly respond to the dynamic changes in the model and accurately track the trajectory, thereby improving the control precision and stability during the obstacle-crossing process. Full article

Measuring weak magnetic fields proposes significant challenges to the sensing capabilities of magnetic field sensors. The magnetic field detection capacity of tunnel magnetoresistance (TMR) sensors is often insufficient for such applications, necessitating targeted optimization strategies to improve their performance in weak-field measurements. Utilizing magnetic flux concentrators (MFCs) offers an effective approach to enhance TMR sensitivity. In this study, the finite element method was employed to analyze the effects of different MFC geometric structures on the uniformity of the magnetic field in the air gap and the magnetic circuit gain (MCG). It was determined that the MCG of the MFC is not directly related to the absolute values of its parameters but rather to their ratios. Simulation analyses evaluated the impact of these parameter ratios on both the MCG and its spatial distribution uniformity, leading to the formulation of MFC design optimization principles. Building on these simulation-derived principles, several MFCs were fabricated using the 1J85 material, and an experimental platform was established to validate the simulation findings. The fabricated MFCs achieved an MCG of 7.325 times. Based on the previously developed TMR devices, a detection sensitivity of 2.46 nT/$\sqrt{\mathrm{Hz}}$ @1Hz was obtained. By optimizing parameter configurations, this work provides theoretical guidance for further enhancing the performance of TMR sensors in magnetic field measurements. Full article

The current paper presents a comprehensive intelligent system designed to optimize the performance of a barrier eddy current separator (BECS), comprising a conveyor belt, a vibration feeder, and a magnetic drum. This system was trained and validated on real-world industrial data gathered directly from the working separator under 81 different operational scenarios. The intelligent models were used to recommend optimal settings for drum speed, belt speed, vibration intensity, and drum angle, thereby maximizing separation quality and minimizing energy consumption. the smart separation module utilizes YOLOv11n-seg and achieves a mean average precision (mAP) of 0.838 across 7163 industrial instances from aluminum, copper, and plastic materials. For shape classification (sharp vs. smooth), the model reached 91.8% accuracy across 1105 annotated samples. Furthermore, the thermal monitoring unit can detect iron contamination by analyzing temperature anomalies. Scenarios with iron showed a maximum temperature increase of over 20 °C compared to clean materials, with a detection response time of under 2.5 s. The architecture integrates a Digital Twin using Azure Digital Twins to virtually mirror the system, enabling real-time tracking, behavior simulation, and remote updates. A full connection with the PLC has been implemented, allowing the AI-driven system to adjust physical parameters autonomously. This combination of AI, IoT, and digital twin technologies delivers a reliable and scalable solution for enhanced separation quality, improved operational safety, and predictive maintenance in industrial recycling environments. Full article

Permanent magnetic couplings provide critical advantages for deep-sea systems through static-sealed, contactless power transmission. However, conventional metallic isolation sleeves incur significant eddy current losses, limiting efficiency and high-speed operation. Limited torque capacities fail to meet the operational demands of harsh marine environments. This study presents a novel permanent magnet coupling featuring a ceramic isolation sleeve engineered for deep-sea cryogenic ammonia submersible pumps. The ceramic sleeve eliminates eddy current losses and provides exceptional corrosion resistance in acidic/alkaline environments. To withstand 3.5 MPa hydrostatic pressure, a 6-mm-thick sleeve necessitates a 10 mm operational air gap, challenging magnetic circuit efficiency. To address this limitation, an improved 3D magnetic equivalent circuit (MEC) model was developed that explicitly accounts for flux leakage and axial end-effects, enabling the accurate characterization of large air gap fields. Leveraging this model, a Taguchi method-based optimization framework was implemented by balancing key parameters to maximize the torque density. This co-design strategy achieved a 21% increase in torque density, enabling higher torque transfer per unit volume. Experimental validation demonstrated a maximum torque of 920 Nm, with stable performance under simulated deep-sea conditions. This design establishes a new paradigm for high-power leak-free transmission in corrosive, high-pressure marine environments, advancing applications from deep-sea propulsion to offshore energy systems. Full article

As the range of applications for amphibious robots expands, higher demands are being placed on their working time and working range. This paper proposed a power supply system for an amphibious robot based on wave energy generation, which can convert wave energy into electric energy to enhance endurance. First, the no-load induced electromotive force, magnetic line distribution vector diagrams, and magnetic density cloud diagrams of the cylindrical and flat generators were compared by finite element simulation, which determined that the cylindrical structure has better power generation performance. Then, the electromagnetic parameters of the cylindrical generator were analyzed using Ansys Maxwell, and the final dimensions were determined. Finally, the wave motion was simulated using a swing motor, and the effects of different cutting speeds for the actuator before and after rectification, as well as series-parallel capacitance on the power generation performance of the designed generator, were experimentally analyzed. This provides a potential solution to enhance the working time and working range of amphibious robots. Full article