Search Results (187)

This paper presents a strategy to mitigate electromagnetic noise in induction motors for electric vehicles by optimizing the rotor slot count and skewing distance. Initially, the magnetomotive forces (MMF) of the stator and rotor windings, air-gap permeance, and the predominant radial electromagnetic force waves in the air-gap magnetic field were analytically determined and compiled. A finite element model of the original 36/42 straight-slot configuration was established for simulation validation. Subsequently, a preliminary optimization scheme for rotor slot number was proposed. A systematic analysis was conducted of the circumferential distribution of radial force waves and their harmonic components in both temporal and spatial orders by comparing electromagnetic vibration characteristics across different rotor slot configurations (42 versus 53 slots) using two-dimensional Fourier decomposition. Furthermore, building upon the mechanism of tooth harmonic suppression via rotor skewing, an advanced optimization strategy for skewing distance was developed. Comparative analysis of harmonic content in air-gap flux density under three configurations (straight slot, 1.0× skewing, and 1.2× skewing) revealed the optimal solution. Experimental vibration tests demonstrated significant improvements: the optimized 53-slot rotor with 1.2× skewing reduced vibration amplitudes by 5 dB·Hz at the 2nd-order natural frequency, 5 dB·Hz at the 3rd-order natural frequency, and 18 dB·Hz at the 3rd-order resonance peak compared to the original 42-slot straight-slot design. These results confirm that coordinated optimization of rotor slot number and skewing distance effectively mitigates electromagnetic vibration and noise in traction motors. Full article

We present three dimensional particle-in-cell simulations of current-voltage characteristics of the hemispherical Langmuir probe (LAP), onboard the China Seismo-Electromagnetic Satellite (CSES). Using realistic plasma parameters and background magnetic fields obtained from the International Reference Ionosphere (IRI) and International Geomagnetic Reference Field (IGRF) models, we simulate probe–plasma interactions at three locations: the equatorial region and two magnetically conjugate mid-latitude sites: Millstone Hill (Northern Hemisphere) and Rothera (Southern Hemisphere). The simulations, performed using the PTetra PIC code, incorporate realistic LAP geometry and spacecraft motion in the ionospheric plasma. Simulated current voltage characteristics or I–V curves are compared against in-situ LAP measurements from CSES Orbit-026610, with Pearson’s correlation coefficients used to assess agreement. Our findings indicate how plasma temperature, density, and magnetization affect sheath structure and probe floating potential. The study highlights the significance of kinetic modeling in enhancing diagnostic accuracy, particularly in variable sheath regimes where classic analytical models such as the Orbital-Motion-Limited (OML) theory may be inadequate. Full article

As a key component for maintaining the efficient and stable operation of flexible DC transmission systems, the arm reactor often suffers from uneven loss distribution and localized overheating in its windings due to the superimposed AC and DC currents, which adversely affects its operational lifespan. Furthermore, arm reactors are frequently deployed in offshore environments for long-distance, high-capacity power transmission, imposing additional requirements on energy utilization efficiency and seismic resistance. To address these challenges, this study proposes an optimization design method for arm reactors based on a triple-constraint mechanism of “equal resistive voltage–equal loss density–equal encapsulation temperature rise,” aiming to achieve “low loss–low temperature rise–low weight.” First, an equivalent electromagnetic model of the arm reactor under combined AC and DC operating conditions is established to analytically calculate the self- and mutual-inductance-distribution characteristics between winding layers and the loss distribution across windings. The calculated losses are then applied as heat sources in a fluid–thermal coupling method to compute the temperature field of the arm reactor. Next, leveraging a Kriging surrogate model to capture the relationship between the winding temperature rise in the bridge-arm reactor and the loss density, encapsulation width, encapsulation height, and air duct width, the revised analytical expression reduces the temperature rise error from 43.74% to 11.47% compared with the traditional empirical formula. Finally, the triple-constraint mechanism of “equal resistive voltage–equal loss density–equal encapsulation temperature rise” is proposed to balance interlayer current distribution, suppress total loss generation, and limit localized hotspot formation. A prototype constructed based on the optimized design demonstrates a 44.51% reduction in total loss, a 39.66% decrease in hotspot temperature rise, and a 24.83% reduction in mass while maintaining rated inductance, validating the effectiveness of the proposed design algorithm. Full article

In consequent-pole permanent magnet (CPPM) machines, the configuration where PM poles and iron poles are alternately arranged causes distortion in the air-gap magnetic field. This results in significant differences in magnetic circuit characteristics compared to conventional PM machines. To address the requirements of reducing torque ripple and enhancing average output torque, the cogging torque and optimization methods for CPPM machines were investigated. A general analytical model for cogging torque was established. This model accounts for asymmetric pole configurations and is particularly well-suited for analyzing CPPM machines. The mechanism through which the consequent-pole (CP) structure improves the utilization rate of PM material was explored, and the parameters influencing the main flux were analyzed. By replacing PMs with soft magnetic materials, the conventional topology of a 12-slot/8-pole surface-inserted PM machine with stator skewing was directly converted into a CP topology. Performance optimization was conducted based on this original scheme. This approach ensures manufacturing convenience while maximizing the sharing of identical components. Simulation results demonstrate that, compared to the benchmark machine, the optimized CPPM machine uses only 60.16% of the PM material while producing 88.19% of the electromagnetic torque, resulting in a 46.61% increase in torque generated per unit volume of PM material. Finally, the benchmark and optimized CPPM prototypes were fabricated, and their torque output capabilities were tested. The finite element simulation results and the measured data show good consistency, validating the correctness of the theoretical analysis and the effectiveness of the finite element model. This study provides a theoretical basis and engineering reference for the performance analysis and optimal design of CPPM machines. Full article

We compare the semiclassical and quantum predictions for the unitary dynamics of a two-level atom interacting with a single-mode electromagnetic field under parametric modulation of the atomic parameters in the regime of multiphoton atom–field resonances. We derive approximate analytic solutions for the semiclassical Rabi model when the atomic transition frequency and the atom–field coupling strength undergo harmonic external modulations. These solutions are compared to the predictions of the quantum Rabi model, which we solve numerically for an initial coherent state with a large average photon number (on the order of ${10}^4$), in the regime of three-photon resonance. We show that, for short enough times and sufficiently intense coherent states, the semiclassical dynamics agrees quite well with the quantum dynamics, although it inevitably fails at longer times due to the absence of collapse–revival behavior. Furthermore, we describe how the field state evolves throughout the interaction, presenting numerical results for the average photon number, entropies (related to atom–field entanglement), and other quantities characterizing the photon number statistics of the electromagnetic field. Full article

The ironless tubular permanent magnet synchronous linear motor (TPMSLM) is in high demand for high-precision servo control applications due to its advantages of having zero cogging effect and high dynamic response. However, its electromagnetic field analysis model has not yet been perfected. This paper aims to accurately predict the magnetic field distribution and electromagnetic performance parameters of an ironless TPMSLM. Taking the axially magnetized ironless TPMSLM as an example, and disregarding the influence of the armature magnetic field on the air gap magnetic field, a simplified analytical model of the TPMSLM is established in the cylindrical coordinate system based on the equivalent magnetization current method (EMC), and the analytical formula for the air gap magnetic flux density is then derived. Subsequently, by applying electromagnetic field theory and the analytical formula for the magnetic flux density in the air gap, analytical expressions for the back electromotive force (back EMF) and thrust are derived, reducing analytical complexity while maintaining accuracy. The accuracy and practicality of the proposed analytical formulas are validated through comparisons with finite element analysis (FEA) and experimental prototypes. This analytical approach facilitates the optimization of linear motor parameters and the study of thrust fluctuation suppression, thereby laying the foundation for high-precision servo control of linear motors. Full article

Electromagnetic field (EMF) exposure mapping is increasingly important for ensuring compliance with safety regulations, supporting the deployment of next-generation wireless networks, and addressing public health concerns. While numerous surveys have addressed specific aspects of radio propagation or radio environment maps, a comprehensive and unified overview of EMF mapping methodologies has been lacking. This review bridges that gap by systematically analyzing computational, geospatial, and machine learning approaches used for EMF exposure mapping across both wireless communication engineering and public health domains. A novel taxonomy is introduced to clarify overlapping terminology—encompassing radio maps, radio environment maps, and EMF exposure maps—and to classify construction methods, including analytical models, model-based interpolation, and data-driven learning techniques. In addition, the review highlights domain-specific challenges such as indoor versus outdoor mapping, data sparsity, and model generalization, while identifying emerging opportunities in hybrid modeling, big data integration, and explainable AI. By combining perspectives from communication engineering and public health, this work provides a broader and more interdisciplinary synthesis than previous surveys, offering a structured reference and roadmap for advancing robust, scalable, and socially relevant EMF mapping frameworks. Full article

A homogenisation procedure for energy-buffering structural layers with integrated electrical energy storage systems (capacitors) is described with the aim of calculating their shielding effectiveness to the electromagnetic waves when they are installed inside building walls. In fact, these storage systems may attenuate electromagnetic fields in the frequency ranges employed by mobile telephony, radio broadcasting, and wireless data transmission, thus impairing the operation of Internet of Things infrastructures. The capacitors inside the individual energy-buffering modules have a multilayered structure, in which the layers have very small thicknesses, making an analytical solution of the electromagnetic field for this kind of object practically impossible. Similarly, numerical solutions may not be practical due to the very small thickness of the layers compared to the overall object size. Therefore, this paper presents a simple and effective analytical method to model multilayered structures consisting of homogenising the whole capacitor, which can then be treated as a unique block of material with fictitious (but effective) electric and magnetic parameters. The method is based on multi-section transmission lines, and a quick and reliable analytical methodology is proposed to evaluate the shielding capabilities using the homogenised capacitor’s effective parameters. Moreover, experimental measurements on a real prototype have also been carried out to validate the methodology. Results show that the trend of the simulated and measured SE is the same, proving that the method can be employed to obtain a conservative estimation of the SE from numerical simulations. Full article

Electromagnetic implosions of hollow lithium cylinders can be utilized to compress magnetized plasma targets in the context of Magnetized Target Fusion (MTF). Two small-scale experiments were conducted at General Fusion as a stepping stone toward compressing magnetized plasmas on a larger scale. The first experiment is an electromagnetic implosion of a lithium ring, and the second is a compression of toroidal magnetic flux by imploding a hollow lithium cylinder onto an hourglass-shaped central structure. Here we present the methodology and results of modelling these experiments with OpenFOAM. Our in-house axisymmetric compressible MHD multi-phase solver was further extended to incorporate: (i) external RLC circuit model for electromagnetic compression coils and (ii) diffusion of the magnetic field into multiple solid materials. The implementation of the external RLC circuit model for electromagnetic coils was verified by comparison with results obtained with FEMM software and with the analytical solution. The solver was then applied to model both experiments and the main conclusions are as follows: (i) modelling solid lithium as a high-viscosity liquid is an adequate approach for the problems considered; (ii) the magnetic diffusivity of lithium is an important parameter for the accurate prediction of implosion trajectories (for the implosion of the lithium ring, higher values of magnetic diffusivity in the range $0.2 \le {\eta }_{\mathrm{ring}}[{\mathrm{m}}^2/\mathrm{s}] \le 0.5$ resulted in a better fit to the experimental data with a relative deviation in the trajectory of $\lesssim 20\%$); (iii) simulation results agree well with experimental data, and in particular, the toroidal field amplification of 2.25 observed in the experiment is reproduced in simulations within a relative error margin of 20%. The solver is proven to be robust and has the potential to be employed in a variety of applications. Full article

The force ripple of a permanent magnet synchronous linear motor (PMSLM) caused by multi-source disturbances in practical applications seriously restricts its high-precision motion control performance. The traditional single-mechanism model has difficulty fully characterizing the nonlinear disturbance factors, while the data-driven method has real-time limitations. Therefore, this paper proposes a hybrid modeling framework that integrates the physical mechanism and measured data and realizes the dynamic compensation of the force ripple by constructing a collaborative suppression algorithm. At the mechanistic level, based on electromagnetic field theory and the virtual displacement principle, an analytical model of the core disturbance terms such as the cogging effect and the end effect is established. At the data level, the acceleration sensor is used to collect the dynamic response signal in real time, and the data-driven ripple residual model is constructed by combining frequency domain analysis and parameter fitting. In order to verify the effectiveness of the algorithm, a hardware and software experimental platform including a multi-core processor, high-precision current loop controller, real-time data acquisition module, and motion control unit is built to realize the online calculation and closed-loop injection of the hybrid compensation current. Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions. Full article

In this study, we investigate the fractional Tzitzéica equation, a nonlinear evolution equation known for modeling complex phenomena in various scientific domains such as solid-state physics, crystal dislocation, electromagnetic waves, chemical kinetics, quantum field theory, and nonlinear optics. Using the (G′/G, 1/G)-expansion approach, we derive different categories of exact solutions, like hyperbolic, trigonometric, and rational functions. The beta fractional derivative is used here to generalize the classical idea of the derivative, which preserves important principles. The derived solutions with broader nonlinear wave structures are periodic waves, breathers, peakons, W-shaped solitons, and singular solitons, which enhance our understanding of nonlinear wave dynamics. In relation to these results, the findings are described by showing the solitons’ physical behaviors, their stabilities, and dispersions under fractional parameters in the form of contour plots and 2D and 3D graphs. Comparisons with earlier studies underscore the originality and consistency of the (G′/G, 1/G)-expansion approach in addressing fractional-order evolution equations. It contributes new solutions to analytical problems of fractional nonlinear integrable systems and helps understand the systems’ dynamic behavior in a wider scope of applications. Full article

This paper concerns the experimental validation of optimized near-field (NF) spherical spiral scannings employing a minimum number of samples, when an offset-mounted elongated antenna under test (AUT), i.e., with its center shifted with respect to that of the measurement sphere, is considered. In order to perform the standard NF/far-field transformation (NF/FFT) technique, a non-centered AUT would generally require the collection of a significantly increased amount of voltage data if compared to the onset scenario. This issue is addressed here by using the non-redundant (NR) sampling representations of electromagnetic (EM) fields. These representations, by leveraging the analytical properties of the EM field, allow one to perform the NR NF/FFTs for offset-mounted AUTs by using only a minimum number of (offset acquired) samples, equal to that required by the NR approaches for the onset case (over 85% fewer samples compared to the standard NF spherical scanning). In particular, these NR NF/FFTs are obtained by modeling the AUT with a prolate spheroid or a rounded cylinder and their effectiveness is fully assessed by the reported experimental results. Full article

This paper proposes an improved analytical model for a line-start explosion-proof magnet synchronous motor that considers the effect of magnetic bridge saturation. Under the condition of maintaining the air-gap magnetic field unchanged, and taking into account the topological structures of embedded magnets, squirrel cages, and rotor slot openings, a subdomain model partitioning method is systematically investigated. Considering the saturation effect of the magnetic bridge of the rotor, the equivalent magnetic circuit method was utilized to calculate the permeance of the saturated region. It not only facilitates the establishment of subdomain equations and corresponding subdomain boundary conditions, but also ensures the maximum accuracy of the equivalence by maintaining the topology of the rotor. The motor was partitioned into subdomains, and in conjunction with the boundary conditions, the Poisson equation and Laplace equation are solved to obtain the electromagnetic performance of the motor. The accuracy of the analytical model is verified through finite element analysis. The accuracy of the analytical model is verified through finite element analysis (FEA). Compared to the FEA, the improved model maintains high precision while reducing computational time and exhibiting better generality, making it suitable for the initial design and optimization of industrial motors. Full article

The integration of the Internet of Things (IoT) and artificial intelligence (AI) has reshaped modern agriculture by enabling precision farming, real-time monitoring, and data-driven decision-making. This systematic review, conducted in accordance with the PRISMA methodology, provides a comprehensive overview of recent advancements in smart sensing technologies for arable crops and grasslands. We analyzed the peer-reviewed literature published between 2020 and 2024, focusing on the adoption of IoT-based sensor networks and AI-driven analytics across various agricultural applications. The findings reveal a significant increase in research output, particularly in the use of optical, acoustic, electromagnetic, and soil sensors, alongside machine learning models such as SVMs, CNNs, and random forests for optimizing irrigation, fertilization, and pest management strategies. However, this review also identifies critical challenges, including high infrastructure costs, limited interoperability, connectivity constraints in rural areas, and ethical concerns regarding transparency and data privacy. To address these barriers, recent innovations have emphasized the potential of Edge AI for local inference, blockchain systems for decentralized data governance, and autonomous platforms for field-level automation. Moreover, policy interventions are needed to ensure fair data ownership, cybersecurity, and equitable access to smart farming tools, especially in developing regions. This review is the first to systematically examine AI-integrated sensing technologies with an exclusive focus on arable crops and grasslands, offering an in-depth synthesis of both technological progress and real-world implementation gaps. Full article

This paper presents a comprehensive analytical framework for investigating loss mechanisms and thermal behavior in high-speed magnetic field-modulated motors for flywheel energy storage systems. Through systematic classification of electromagnetic, mechanical, and additional losses, we reveal that modulator components constitute approximately 45% of total system losses at rated speed. Finite element analysis demonstrates significant spatial non-uniformity in loss distribution, with peak loss densities of 5.5 × 10⁵ W/m³ occurring in the modulator region, while end-region losses exceed central-region values by 42% due to three-dimensional field effects. Our optimized design, implementing composite rotor structures, dual-material permanent magnets, and integrated thermal management solutions, achieves a 43.2% reduction in total electromagnetic losses, with permanent magnet eddy current losses decreasing by 68.7%. The maximum temperature hotspots decrease from 143 °C to 98 °C under identical operating conditions, with temperature gradients reduced by 58%. Peak efficiency increases from 92.3% to 95.8%, with the η > 90% region expanding by 42% in the speed–torque plane. Experimental validation confirms model accuracy with mean absolute percentage errors below 4.2%. The optimized design demonstrates 24.8% faster response times during charging transients while maintaining 41.7% smaller speed oscillations during sudden load changes. These quantitative improvements address critical limitations in existing systems, providing a viable pathway toward high-reliability, grid-scale energy storage solutions with extended operational lifetimes and improved round-trip efficiency. Full article