Search Results (85)

Conventional finite element method (FEM) has a complex model and a long optimization time for Halbach array PM machines. This paper proposes a hybrid analytical method that combines the subdomain method (SM) and the magnetic circuit method (MEC) for analyzing a high-torque-density, three-segment Halbach array rotor permanent magnet (PM) machine, accounting for Halbach array magnetization and end leakage flux. Firstly, to address the challenge posed by complex PM shapes in the Halbach array PM machine, a novel subdivision equivalence method is conducted. Then, the magnetic equivalent circuit (MEC) of the stator and rotor is established, and the axial leakage flux and nonlinearity of the iron core are taken into account. In addition, electromagnetic performance, such as air gap flux density, cogging torque, electromagnetic torque, and back electromotive force (back-EMF), is obtained based on the proposed hybrid analytical model. The analytical results are verified by using the finite element method (FEM), and the results show that the error is less than 2%. Finally, a 15 kW prototype PM machine with a Halbach array PM rotor is manufactured and tested, and the results validate the accuracy and efficiency of the analytical method. Full article

Accurate measurement of spool displacement is essential for achieving high-performance closed-loop control and condition monitoring in hydraulic systems. However, conventional inductive displacement transducers typically rely on sinusoidal excitation and complex analog signal conditioning circuits, resulting in higher hardware cost and limited system integration. To address these issues, this paper proposes a software-based demodulation method for a differential inductive displacement transducer under symmetric complementary square-wave excitation. First, the structure and operating principle of the transducer are analyzed, and an electromagnetic model describing the nonlinear relationship between coil inductance and the position of the inductive core is established, along with its electrical characteristics. Then, a simplified signal acquisition circuit is designed to enable digital extraction of inductance variations using a microprocessor. Compared with conventional approaches, the proposed scheme significantly reduces hardware complexity and cost while being more suitable for embedded system integration. A simulation model is developed to analyze the inductance variation and to validate the proposed hardware circuit. In addition, a test platform is built to conduct static calibration and dynamic response experiments. The experimental results show that the proposed method achieves a linearity of 2.36% and a sensitivity of 155.6 mV/mm and exhibits strong robustness against switching noise. Finally, application tests in a hydraulic valve system demonstrate that the proposed transducer and demodulation method enable accurate and stable spool position measurement, providing a low-cost and easily integrated solution for embedded hydraulic control systems. Full article

To address the insufficient accuracy of conventional permanent magnet synchronous motor (PMSM) models caused by neglecting magnetic saturation nonlinearity and periodic parameter disturbances, a nonlinear motor system model integrating a Physics-Informed Neural Network (PINN) is developed. By exploiting the differential relationships among incremental inductance, flux linkage, and magnetic energy, the voltage and torque equations considering rotor position variation are derived, and analytical expressions for the derivatives of incremental inductances are obtained. To reduce the computational burden of PINN in system-level simulations, linear and nonlinear approximation strategies based on incremental inductances and their derivatives are proposed, which significantly reduce the frequency of PINN calls while maintaining model accuracy. CPU/GPU collaborative computation and cross-frequency-domain scheduling are further implemented to improve simulation efficiency. Considering the influence of the test bench mechanical dynamics, an electromechanical–magnetic coupled simulation model is established. The accuracy of the proposed nonlinear motor model is validated through two-phase short-circuit tests as well as simulations and test bench experiments under sinusoidal and non-sinusoidal excitations. The results demonstrate that the proposed model accurately captures the nonlinear electromagnetic characteristics of PMSMs while significantly improving system simulation efficiency. Full article

All-medium metamaterial absorbers (MMAs) have attracted considerable attention for ultra-broadband electromagnetic wave (EMW) absorption. Herein, a lightweight graphene aerogel (GA) was synthesized through a low-temperature, atmospheric-pressure reduction route. Benefiting from its 3D porous network, enriched oxygen-containing functional groups, and improved graphitization, the GA offers diverse intrinsic attenuation pathways and a limited effective absorption bandwidth (EAB) of only 6.46 GHz (11.54–18.00 GHz at 1.95 mm). To clarify its attenuation mechanism, nonlinear least-squares fitting was used to quantitatively separate electrical loss contributions. Compared with graphene, the GA shows markedly superior attenuation capability, making it a more suitable medium for MMA design. Guided by equivalent circuit modeling, a stacked frustum-configured GA-based MMA (GA-MMA) was developed, where structure-induced resonances compensate for the intrinsic absence of magnetic components in the GA, thereby substantially broadening its absorption range. The GA-MMA achieves an EAB of 40.7 GHz (9.1–49.8 GHz, reflection loss < −10 dB) and maintains stable absorption under incident angles up to ± 70°. Radar cross-section simulations further indicate its potential in electromagnetic interference mitigation, human health protection, and defense information security. This work provides a feasible route for constructing ultralight and broadband MMAs by coupling electrical loss with structural effects. Full article

Accurate fault localization in rail transit train cables is hindered by impedance mismatch, which induces overshoot interference and attenuates reflected signals, causing traditional peak-detection methods to fail. This study proposes a novel traveling wave dual-peak identification method to address this challenge. The approach employs signal polarity normalization to eliminate phase inversion, Gaussian-weighted filtering to suppress noise and distortion, and local extrema screening to robustly isolate incident and reflected wave peaks amidst complex backgrounds including overshoot oscillations and electromagnetic crosstalk. A dual-Gaussian model is optimized via nonlinear fitting to precisely quantify peak arrival times while compensating for waveform broadening. Fault distance is derived from the optimized time difference and wave velocity. Experimental validation across single-core coaxial, twin-core coaxial, and harness cables with open/short-circuit faults at multiple distances confirms the method’s effectiveness. Results demonstrate strong linear relationships between time differences and fault distances for all cable types, with successful peak identification achieved even under severe signal attenuation or strong coupling interference. This method significantly enhances localization accuracy for rail transit cable systems under impedance mismatch conditions. Full article

The hysteresis model can be used to accurately predict the magnetic hysteresis characteristics of ferromagnetic materials. Incorporating the hysteresis model into finite element calculations enables precise prediction of field distributions, voltage or current variations in circuits, and losses, which is essential for electromagnetic transient analysis involving remanent magnetization. When incorporating the hysteresis model into finite element analysis, prohibitively small time-steps are required to resolve hysteresis loops, leading to excessive simulation times compared to simplified BH curve approaches. Furthermore, numerical instabilities arise near zero-crossing points of magnetic flux density, where erroneous negative differential reluctivity values may lead to the divergence of the nonlinear solving process. A finer time resolution needs to be utilized to ensure the convergence of the nonlinear solver. This leads to more time-steps and longer computational time. This work proposes a localized stabilization strategy for regulating the differential reluctivity in instability-prone regions of the hysteresis loop, which can stabilize the nonlinear iteration while avoiding the local refinement of time resolution and thus reduce the overall computation time. Full article

This study examines the contrast in the nonlinear dynamics of Thrinax radiata Lodd. ex Schult. & Schult. f. Seed germplasm explored by optical and electrical signals. By integrating chaotic attractors for the modulation of the optical and electrical measurements, the research ensures high sensitivity monitoring of seed germplasm dynamics. Reflectance measurements and electrical responses were analyzed across different laser pulse energies using Newton–Leipnik and Rössler chaotic attractors for signal characterization. The optical attractor captured laser-induced changes in reflectance, highlighting nonlinear thermal effects, while the electrical attractor, through a custom-designed circuit, revealed electromagnetic interactions within the seed. Results showed that increasing laser energy amplified voltage magnitudes in both systems, demonstrating their sensitivity to energy inputs and distinct energy-dependent chaotic patterns. Fractional calculus, specifically the Caputo fractional derivative, was applied for modeling temperature distribution within the seeds during irradiation. Simulations revealed heat transfer about 1 °C in central regions, closely correlating with observed changes in chaotic attractor morphology. This interdisciplinary approach emphasizes the unique strengths of each method: optical attractors effectively analyze photoinduced thermal effects, while electrical attractors offer complementary insights into bioelectrical properties. Together, these techniques provide a realistic framework for studying seed germplasm dynamics, advancing knowledge of their responses to external perturbations. The findings pave the way for future applications and highlight the potential of chaos theory for early detection of structural and bioelectrical changes induced by external energy inputs, thereby contributing to sample protection. Our results provide quantitative dynamical descriptors of laser-evoked seed responses that establish a tractable framework for future studies linking these metrics to physiological outcomes. Full article

Traditional Hopfield neural networks (HNNs) suffer from limitations in generating controllable chaotic dynamics, which are essential for applications in neuromorphic computing and secure communications. Memristors, with their memory-dependent nonlinear characteristics, provide a promising approach to regulate neuronal activities, yet systematic studies on attractor offset behaviors remain scarce. In this study, we propose a fully memristive electromagnetic radiation neural network by incorporating three distinct memristors as external electromagnetic stimuli into an HNN. The parameters of the memristors were tuned to modulate chaotic oscillations, while variations in initial conditions were employed to explore multistability through bifurcation and basin stability analyses. The results demonstrate that the system enables large-scale amplitude control of chaotic signals via memristor parameter adjustments, allowing arbitrary scaling of attractor amplitudes. Various offset behaviors emerge, including parameter-driven symmetric double-scroll relocations in phase space and initial-condition-induced offset boosting that leads to extreme multistability. These dynamics were experimentally validated using an STM32-based electronic circuit, confirming precise amplitude and offset control. Furthermore, a multi-channel pseudo-random number generator (PRNG) was implemented, leveraging the initial-boosted offset to enhance security entropy. This offers a hardware-efficient chaotic solution for encrypted communication systems, demonstrating strong application potential. 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

Resistive angle sensors are widely used due to their simple signal conditioning circuits and high cost-effectiveness. This paper presents a resistive angle sensor based on a rotary potentiometer, designed to offer a measurement range of 180° for low-cost angle measurement in industrial automation and electromagnetic interference (EMI)-sensitive applications. The sensor features a specially designed signal conditioning circuit and mechanical housing. Experimental results show that it exhibits excellent linearity and temperature stability over a wide temperature range of −20 °C to 60 °C, with a zero-temperature drift of approximately 0.004°/°C. For the nonlinearity and hysteresis caused by unavoidable friction and manufacturing tolerances between the transmission mechanism and rotary potentiometer, an adaptive linear neuron (ADALINE) technique based on the α-least mean square (α-LMS) algorithm was implemented for software compensation. The results show that the percentage nonlinearity error was reduced from the original 4.413% to 0.182%, and the percentage hysteresis error was decreased from the original 4.061% to 0.404%. The research results of this paper offer valuable insight for high-precision resistive angle sensors. Full article

Wireless power transfer (WPT) is recognized as a critical technology to advance carbon neutrality in transportation by alleviating charging challenges for electric vehicles and accelerating their adoption to replace fossil fuel. To ensure durability under traffic loads and harsh environments while avoiding vehicle obstructions, WPT primary circuits should be embedded within pavement structures rather than surface-mounted. This study systematically investigated the optimization of magnetite-modified asphalt material composition and thickness for enhancing electromagnetic coupling in WPT systems through integrated numerical and experimental approaches. A 3D finite element model (FEM) and a WPT platform with primary-side inductor–capacitor–capacitor (LCC) and secondary-side series (S) compensation were developed to assess the electromagnetic performance of magnetite content ranging from 0 to 25% and pavement thickness ranging from 30 to 70 mm. Results indicate that magnetite incorporation increased efficiency from 80.3 to 84.7% and coupling coefficients from 0.236 to 0.242, with power loss increasing by only 0.25 W. This enhancement is driven by improved equivalent permeability, which directly enhances magnetic coupling efficiency. A critical pavement thickness of 50 mm was identified, beyond which the reduction in transmission efficiency increased significantly due to magnetic flux dispersion. Additionally, the nonlinear increase in power loss is partially attributed to the significant rise in hysteresis and eddy current losses at elevated magnetite content levels. The proposed design framework, which focuses on 10% magnetite content and a total pavement thickness of 50 mm, achieves an optimal energy transfer efficiency. This approach contributes to sustainable infrastructure development for wireless charging applications. Full article

Shaftless propulsion technology delivers high efficiency and low noise for subsea installations and marine vessels. To enhance thrust performance, the streamlined aft-body contour imposes stringent demands on geometric compatibility between the rim-driven thruster (RDT) motor and hull. This necessitates advanced electromagnetic characterization of conical motors. This paper proposes an equivalent magnetic circuit model (EMCM) that accounts for end effects and magnetic saturation in both the stator and rotor cores for the magnetic field analysis of conical permanent magnet synchronous motor (CPMSM). A 3D EMCM is developed by decomposing the air-gap flux into radial/axial/tangential components. End-field nonlinearities are addressed via lumped-parameter network modeling. Innovatively, a trapezoidal expanded magnet layout and magnet-pole-trimming technology are adopted to ensure sinusoidal flux distribution. Finally, a 10.5 kW prototype with a conical angle of 6.7 degrees is designed using the EMCM and verified through a finite-element analysis (FEA) and experiments. This research provides a theoretical framework for the rapid electromagnetic analysis of the CPMSM. Full article

The power transformer is a critical primary device in the power grid, and the verification of its winding mechanical stability is of paramount importance in ensuring the safe and stable operation of the power grid. In the conventional numerical calculation methods for verifying the mechanical stability of power transformer windings, the influence of temperature variations at the winding hot spots on winding mechanical stability has not been taken into account. In reality, factors such as the transformer’s operating load rate, ambient temperature, and the duration of short-circuit fault currents passing through will affect the mechanical stability margin of the transformer windings. Under conditions such as winding aging, deformation, or other reasons, the transformer windings may become unstable due to material parameter degradation, leading to insufficient mechanical stability margin. This paper analyzes the mechanical stability of power transformer windings considering the impact of the temperature field. Initially, a numerical model for calculating short-circuit currents in transformers was established to compute the short-circuit current under three-phase short-circuit-to-ground conditions as an excitation. Subsequently, a 3D electromagnetic force finite element calculation model was developed to determine the electromagnetic forces experienced under this condition. The results of the calculated electromagnetic forces were then used in a numerical calculation method to assess the mechanical stability of the windings. Furthermore, a 3D transformer electromagnetic–thermal flow finite element model was created to calculate the steady-state temperature rise under various operating conditions of the transformer. This model is validated through transformer temperature rise tests, and transient temperature rises under different operating conditions are calculated. The obtained data are fitted using the nonlinear least squares method to derive a fitting function for the winding hot spot temperature concerning load rate, ambient temperature, and short-circuit time. Taking into consideration the influence of temperature on the yield strength and modulus of elasticity of transformer winding materials, the variation in mechanical stability margin of transformer windings due to temperature effects is analyzed. Additionally, the operating domain for preventing the transformer from becoming unstable under three-phase short-circuit impacts is calculated for different degrees of material parameter degradation. This method provides an effective reference for transformer design and operation, demonstrating clear practical value. Full article

Interior permanent magnet synchronous motors (IPMSMs) exhibit significant nonlinear electromagnetic behaviour due to the effects of saturation, cross-coupling, spatial harmonics, temperature, and iron losses. In order to effectively capture the actual electromagnetic behaviour of IPMSMs, this paper proposes an improved IPMSM nonlinear model. The proposed model is based on the nonlinear flux-linkage model and progressively incorporates the effects of spatial harmonics, temperature, and iron losses. In this paper, the discrete-time form of the improved nonlinear model is established directly. It is suitable not only for embedding into the Matlab/Simulink environment as an alternative to field circuit coupling simulation but also for deployment into field programmable gate arrays (FPGA) as the model basis for hardware-in-the-loop testing. The effectiveness and feasibility of the improved model are verified by experimental results. Full article

In this paper, a novel dual-band metasurface filter (MSF) designed for accurately differentiating pulse waves (PWs) and continuous waves (CWs) is proposed, which is based on a complementary cross resonator (CSR) structure adhered on a dielectric substrate integrated with a capacitive nonlinear circuit. The unit cell of the designed dual-band MSF comprises two identical CSR structures: one of the capacitive nonlinear circuits is configured in parallel with a capacitor (C₁) within one CSR structure. These structures loaded with nonlinear circuits are fabricated on a dielectric substrate. The simulation outcomes reveal that, for normally incident CWs with an input power of 10 dBm, the transmittance of the designed dual-band MSF reaches as high as 97.1% at 2.0 GHz and 93.9% at 3.45 GHz. In contrast, when it comes to 50 ns short PWs, the transmittance remains consistently below 6% throughout the entire frequency range from 1 GHz to 5 GHz. In addition, the transmittance of the dual-band MSF for normally incident PWs increases significantly as the pulse width widens at the aforementioned two discrete frequencies. The ensuing simulation data corroborates that within the input power range of −15 to 15 dBm, the transmittance difference between CWs and PWs of the dual-band MSF first rises and then falls as the input power increases. Specifically, when the input power is specified as 10 dBm and the angle of oblique incidence ranges from 0° to 60°, in the context of TE and TM modes, the transmittance of CWs exceeds 80% around both 2.0 GHz and 3.45 GHz, while that of PWs remains below 15%. Finally, the effects of resistance and capacitance on the transmittance of the dual-band MSF for the incident PWs and CWs are also studied. The dual-band MSF proposed herein showcases its potential applications in wireless communication as well as in the realm of anti-electromagnetic interference. The electromagnetic (EM) waveform modulation in the frequency band of 1–5 GHz has great development prospects in low-frequency working fields such as radar antennas and EM protection. Full article