Search Results (42)

Introductory and intermediate electrical-engineering education commonly models fundamental circuit and device parameters, including inductance, capacitance, resistance, permeability, permittivity, conductivity, characteristic impedance, transformer turns ratio, machine constants, amplifier gain, resonant frequency, propagation velocity, and mutual inductance, as numerical constants. While this approximation is valid within the intended small-signal operating regime, it becomes methodologically incomplete when these coefficients exhibit measurable state dependence. This paper presents a comparative audit of thirteen such coefficients by systematically contrasting their textbook formulations with the established engineering literature and interpreting the results through two complementary frameworks: the JCGM GUM-6:2020 measurement-model methodology for omitted effects, and the Heckmann–Nye/Gasik multidomain coupling architecture for multi-axis physical interactions. The analysis demonstrates that mainstream engineering practice routinely exploits state-dependent coefficients without invoking new physical laws, and that relaxing the constant-coefficient assumption naturally introduces physically meaningful terms, including the inductive contribution $I\mathrm{d}L/\mathrm{d}t$, the capacitive counterpart $V\mathrm{d}C/\mathrm{d}t$, and the mutual-inductance term $i_2\mathrm{d}M/\mathrm{d}t$. The principal scientific contribution is the development and experimental validation of a unified theoretical and engineering framework for high-power resonant transformers and orthogonal Metglas AMCC-1000 paraformers. The proposed approach combines a new physics-based modal theory of octave ($2:1$) parametric excitation with simultaneous optimization of magnetic-core resonance, electrical resonance, nonlinear inductance modulation, resonant conductor lengths selected as integer multiples of the operating resonant wavelength, multi-stranded high-frequency Litz-wire windings, resonant capacitor synthesis, and the nonlinear magnetic characteristics of the AMCC-1000 amorphous core. The modal analysis demonstrates how coupled resonant eigenmodes and engineered state-dependent inductance can be used to satisfy the conditions for stable octave parametric excitation. Experimental results obtained from both the symmetric two-leg resonant transformer and the orthogonal paraformer are in close agreement with analytical predictions and numerical simulations, thereby validating both the proposed electromagnetic design methodology and the underlying modal theory. Full article

All rotating electrical machines are susceptible to vibrations arising from electromagnetic (EM) forces, electrical faults, mechanical defects, imbalance, and structural resonance. In Doubly Fed Induction Generators (DFIGs), such electromechanical vibrations are especially important because they can degrade reliability, increase noise, and lead to severe damage if resonance-prone operating conditions are not identified in time. Although fault diagnosis in DFIGs has been widely investigated using current, voltage, and flux signatures, comparatively fewer studies have examined fault-specific vibration behaviour under stator and rotor interturn faults (ITTFs), particularly through a coupled EM structural framework. In addition, prior vibration-based studies have not examined the influence of end winding ITTFs, its location, severity, and modal interaction investigating resonance risk. This paper considers vibration characteristics of a variable-speed 2.8 MW DFIG used in a grid-connected Type-3 wind turbine unit (WTU) at no-load operating condition. The DFIG is modelled in ANSYS Academic Research v 2022 R2 Maxwell for EM behaviour assessment for ITTFs in both stator and rotor windings along with modal analysis (MA) in ANSYS Workbench to examine the undamped stator and rotor modes over a range of frequencies. This coupled approach enables identification of vibration signatures associated with different ITTF types. The results show the magnetic flux density near faulty end-winding region increases with fault severity and ranges from 4.19 T to 4.39 T in proximity to faulty windings. A dominant modal frequency band of 60–65 Hz is identified, where stator and rotor modes coincide, creating probable resonance conditions. A severe vibration response is observed for single-phase stator ITTF, showing an amplitude of 2116 mm/s at 480 Hz for a larger number of shorted turns, indicating that asymmetric faults can produce stronger EM excitation than multi-phase faults. The main contribution of this paper is demonstration of a fault-specific, MA and vibration-based Condition monitoring system (CMS) implementation workflow for a DFIG. Unlike prior vibration-based studies that primarily focus on general machine vibration, mechanical faults, bearings, etc., this paper links stator and rotor ITTF induced EM excitation to modal characteristics, resonance behaviour, and measurable vibration signatures, establishing vibration analysis (VA) as a practical complementary technique for CMS of ITTFs in DFIGs. Full article

Externally excited synchronous machines (EESMs) are a rare-earth-free solution for traction applications. However, variable field excitation and magnetic coupling increase control complexity. Efficient validation of the resulting control functionalities can be carried out using hardware-in-the-loop (HIL) testing, which requires high-fidelity real-time simulation models. This paper presents a semi-analytical, discrete-time EESM model tailored for HIL applications. Nonlinear magnetic saturation and magnetic coupling are captured using an inverted flux–current characteristic combined with a rotating coordinate transformation, which improves resource utilization. Spatial harmonics are included through a Fourier decomposition of the angle-dependent inverse characteristics. Additionally, different loss mechanisms are considered to accurately represent the physical behavior of the machine. The model is parameterized using finite element analysis (FEA) results from a 100$\mathrm{k}$$\mathrm{W}$ salient-pole EESM. It is implemented on a field-programmable gate array to achieve real-time capability at a simulation frequency of $2.5$$\mathrm{M}$$\mathrm{Hz}$. Validation results for the typical operating range show deviations below $0.1$% compared to detailed FEA results, demonstrating accurate real-time simulation of the electromagnetic behavior. Full article

Aviation permanent magnet synchronous motors (PMSMs) operate with high power density under high-altitude conditions, where the thermal sensitivity of permanent magnet materials and reduced air density make them prone to demagnetization faults. Even small performance degradation can therefore pose a risk to operational safety, and reliable demagnetization diagnosis is required. This paper analyzes the operating characteristics of an aviation interior PMSM under demagnetization faults and develops a dedicated diagnostic approach. A coupled electromagnetic–thermal finite element model is established to evaluate no-load and rated performance, compute losses under rated conditions, and obtain temperature distributions; the electromagnetic model is further corroborated using an RT-LAB semi-physical real-time simulation of the motor body. Altitude-dependent ambient air properties corresponding to 5000 m are then incorporated to assess the magneto–thermal field distribution and reveal the impact of high-altitude operation on temperature rise and demagnetization risk. Based on the thermal analysis, overall demagnetization faults are classified into several temperature-based levels, and representative local demagnetization cases are constructed; for each fault case, time-domain torque and phase-voltage signals and their frequency-domain components are extracted to form a fault dataset. Building on these features, an intelligent diagnostic method integrating a deep belief network (DBN) and an extreme learning machine (ELM) optimized by an enhanced fireworks algorithm (EnFWA) is proposed. Comparative results show that the proposed DBN–ELM–EnFWA framework achieves a favorable trade-off between diagnostic accuracy and training time compared with several benchmark deep learning models, providing a practical and effective tool for demagnetization fault diagnosis in aviation interior PMSMs. Full article

An efficient cooling configuration is critical for ensuring the safe operation of electrical machines and is key for optimizing the iterative design of motors. To improve the heat dissipation performance of high-power, explosion-proof, integrated variable-frequency permanent magnet motors used in mining and reduce the risk of permanent magnet demagnetization, this study considers a 1600 kW mining explosion-proof variable-frequency permanent magnet motor as its research object. Based on the zigzag-type water channel structure of the frame, a novel rotor-cooling scheme integrating axial–radial ventilation structures and axial flow fans was proposed. The temperature field of the motor was simulated and analyzed using a fluid–thermal coupling method. Under rated operating conditions, the flow characteristics of the frame water channel and the temperature distribution law inside the motor were compared when the water supply flow rates were 5.4, 4.8, 4.2, 3.6, 3, 2.4, and 1.8 m³/h, respectively, and the relationship between the motor temperature rise and the variation in water flow rate was revealed. A production prototype was developed, and temperature rise tests were conducted for verification. The test results were in good agreement with the simulation calculation results, thereby confirming the accuracy of the simulation calculation method. The results provide an important reference for enterprises in the design optimization and upgrading of high-power explosion-proof integrated variable-frequency permanent-magnet motors. Full article

This article presents a gear selection methodology for electric vehicle powertrains employing two identical Permanent Magnet Synchronous Machines (PMSMs) arranged in a twin-drive configuration. Both machines are coupled through a shared output shaft and operate with coordinated torque–speed characteristics, enabling efficient utilization of the available gear stages. The proposed approach establishes a control-oriented drivetrain framework that incorporates mechanical dynamics together with real-time thermal states and loss mechanisms. Unlike conventional strategies, which rely mainly on static or speed-based shifting rules, the method integrates detailed thermal and electromagnetic loss modeling directly into the gear-shifting logic. By accounting for the dynamic thermal behavior of PMSMs under variable load conditions, the strategy aims to reduce cumulative drivetrain losses, including electromagnetic, thermal, and mechanical, while maintaining high efficiency. The methodology is implemented in a MATLAB/Simulink R2024a and LabVIEW 2024Q2 co-simulation environment, where thermal feedback and instantaneous efficiency metrics dynamically guide gear selection. Simulation results demonstrate measurable improvements in energy utilization, particularly under transient operating conditions. The resulting efficiency maps are broader and flatter, as the motors’ operating points are continuously shifted toward zones of optimal performance through adaptive gear ratio control. The novelty of this work lies in combining real-time loss modeling, thermal feedback, and coordinated gear management in a twin-motor system, validated through experimentally motivated efficiency maps. The findings highlight a scalable and dynamic control framework suitable for advanced electric vehicle architectures, supporting intelligent efficiency-oriented drivetrain strategies that enhance sustainability, thermal management, and system performance across diverse operating conditions. Full article

The no-insulation (NI) technique improves the stability and defect-tolerance of high-temperature superconducting (HTS) coils by enabling current redistribution, thereby reducing the risk of quenching. NI–HTS coils are widely applied in DC systems such as high-field magnets and superconducting field coils for electric machines. However, the presence of turn-to-turn contact resistance makes current distribution uneven, rendering traditional simulation methods unsuitable. To address this, a finite element method (FEM) based on the T–A formulation is proposed. This model solves coupled equations for the magnetic vector potential (A) and current vector potential (T), incorporating turn-to-turn contact resistance and anisotropic conductivity. The thin-strip approximation simplifies second-generation HTS materials as one-dimensional conductors, and a homogenization technique further reduces computational time by averaging the properties between turns, although it may limit the resolution of localized inter-turn effects. To verify the model’s accuracy, simulation results are compared against the H formulation, distributed circuit network (DCN) model, and experimental data. The proposed T–A model accurately reproduces key transient characteristics, including magnetic field evolution and radial current distribution, in both circular and racetrack NI coils. These results confirm the model’s potential as an efficient and reliable tool for transient electromagnetic analysis of NI–HTS coils. Full article

In practical applications, the fully enclosed structure is always required by self-starting permanent magnet synchronous motors for safety. However, internal heat dissipation can be obstructed as a result, which affects operational reliability. To resolve the issue, this study takes a 3 kW self-starting permanent magnet synchronous motor as the research object. Based on fluid dynamics and fluid solid coupling heat transfer theory, the model is reasonably simplified according to the characteristics of the structure of motor cooling, and basic assumptions and boundary conditions are given to establish a three-dimensional, whole machine solution domain model. The finite element method is used to numerically analyze and calculate under rated conditions. The fluid flow characteristics, heat transfer characteristics, motion trajectories of the cooling medium on the surface of the external casing, fan, and internal stator and rotor domains, and winding ends are analyzed. Therefore, the internal rheological characteristics and temperature rise distribution law of the self-starting permanent magnet synchronous motor can be revealed. Based on the aforementioned research, a novel method to design the wind spur structure on the surface of the rotor end is proposed. By comparing the simulation results of the fluid field and temperature field of the motor under wind spur structures with different lengths and equidistant distributions in the circumferential direction of the rotor end, the influence of the convective heat characteristics can be systematically studied. Lastly, the accuracy of the calculation results and the rationality of the solution method are verified through experiments of temperature rise, and the flow temperature distribution characteristics of the motor can be optimized by the wind spur structure, which can be used in practical applications. Full article

Owing to the distinct advantages of stator–permanent magnet (PM) motors over other PM machines, their prominence in high-power-density applications is surging dramatically, capturing growing interest across diverse applications. This article proposes an innovative design procedure for two primary stator–PM motor types, flux switching and biased flux, yielding 30 novel motor designs. The procedure involves splitting teeth, incorporating a flux reversal effect, and embedding flux barriers into the conventional structure. The analytical reasons behind the novel motors’ architecture are mathematically expressed and verified using finite element analysis (FEA). Through an effective optimisation based on a multi-objective genetic algorithm, various feasible stator/rotor pole combinations are explored, with over 36,000 samples evaluated using FEA coupled with the algorithm. The electromagnetic characteristics of promising motors are analysed, revealing that adding the flux reversal effect and flux barriers, which reduce PM volume while decreasing leakage flux and enhancing air gap flux, improves torque production by up to 68%. Beyond torque enhancement, other electromagnetic parameters, including torque ripple, core loss, and the power factor, are also improved. The proposed motors enhance the PM torque density significantly by about 115% compared to conventional motors and reduce the motor costs. A generalised decision-making process and thermal analysis are applied to the top-performing motors. Additionally, the prototyping measures and considerations are thoroughly discussed. Finally, a comprehensive conclusion is reached. Full article

This study proposes a rotational speed measurement machine based on the flux-switching principle with a 6-stator-slot/19-rotor-pole (6s/19p) topology. With a rotor shape similar to a variable reluctance sensor (VRS), the proposed machine features a simple and robust structure while ensuring the same output frequency as VRS. Additionally, compared to the conventional 12s/10p topology, the 6s/19p configuration reduces permanent magnet (PM) consumption by half while maintaining high induced voltage characteristics. A nonlinear analytical model (NAM), which incorporates the harmonic modeling (HM) technique and an iterative process, is presented. This model more accurately captures the rectangular shape of the PM and stator teeth while accounting for core saturation effects. Based on this model, the optimal dimensions of the proposed machine are investigated to achieve the best performance for speed measurement applications. A coupling FEA simulation between Ansys Maxwell and Twin Builder further analyzes the machine’s performance. Compared to a commercial product of the same size, the proposed machine achieves 31.5% higher output voltage while ensuring lower linearity errors. Moreover, superior load characteristics are observed, with a voltage drop of only 1.58% at 1500 rpm and 30 mA. The proposed machine and NAM provide an improved solution and analytical tool for speed measurement applications. Full article

With the rapid development of precision instruments, aerospace, and automotive industries, the demand for compact vibration isolators capable of suppressing low-frequency vibrations has surged. Although prior reviews have established the theoretical framework of quasi-zero stiffness (QZS) isolators, critical gaps persist in addressing their compact design under strong nonlinear dynamics and diverse engineering constraints. This review systematically analyzes the dynamic characteristics of QZS systems under nonlinear effects and evaluates five innovative design methodologies for compact QZS isolators: special spring type, magnetic type, bionic type, metamaterials-based type, and origami-inspired type. Key findings reveal that special spring-type isolators are simple to design and space-efficient but difficult to machine. Magnetic-type isolators achieve ultra-low start-up frequencies but face thermal instability. Metamaterial designs enable multifunctional integration at the cost of manufacturing complexity, while bionic-inspired and origami-inspired isolators are difficult to abstract for practical applications. We find that current research tends to prioritize miniaturization over the synergistic optimization of load capacity, broadband isolation, and adaptability. Future research should focus on multi-degree-of-freedom systems, coupled metamaterials-bionic structures, and active magnetic control. This work provides a key roadmap for advancing compact QZS technology in space-constrained applications. Full article

The purpose of this study is to provide a comprehensive resource for the selection of data representations for machine learning-oriented models and components in solar flare prediction tasks. Major solar flares occurring in the solar corona and heliosphere can bring potential destructive consequences, posing significant risks to astronauts, space stations, electronics, communication systems, and numerous technological infrastructures. For this reason, the accurate detection of major flares is essential for mitigating these hazards and ensuring the safety of our technology-dependent society. In response, leveraging machine learning techniques for predicting solar flares has emerged as a significant application within the realm of data science, relying on sensor data collected from solar active region photospheric magnetic fields by space- and ground-based observatories. In this research, three distinct solar flare prediction strategies utilizing the photospheric magnetic field parameter-based multivariate time series dataset are evaluated, with a focus on data representation techniques. Specifically, we examine vector-based, time series-based, and graph-based approaches to identify the most effective data representation for capturing key characteristics of the dataset. The vector-based approach condenses multivariate time series into a compressed vector form, the time series representation leverages temporal patterns, and the graph-based method models interdependencies between magnetic field parameters. The results demonstrate that the vector representation approach exhibits exceptional robustness in predicting solar flares, consistently yielding strong and reliable classification outcomes by effectively encapsulating the intricate relationships within photospheric magnetic field data when coupled with appropriate downstream machine learning classifiers. Full article

The autonomous displacement and displacement measurement functions of the maglev ruler are performed by the mover core. The magnetic levitation ruler can serve as a viable alternative to the linear measurement system of a coordinate measuring machine. The stability of the four magnetic fields in air gaps and the levitation position of the maglev ruler is one of the key factors for the stability of the thrust force on the power core, and it is also one of the key factors for ensuring the precision of the maglev ruler. There is cross-coupling between the two ends of the mover core of the maglev ruler, resulting in a strongly coupled, nonlinear, multi-input and multi-output system for the levitating system of the maglev ruler. This paper establishes a mathematical model for the levitating system of the maglev ruler and designs a levitating control system for the maglev ruler based on an active disturbance rejection control algorithm to achieve decoupling and disturbance suppression. Through simulation analysis and experimental testing of the levitating system with starting and disturbance, it is proved that the levitating control system of the maglev ruler has good dynamic characteristics, static characteristics, and robustness. Full article

The use of interior permanent-magnet synchronous machines (IPMSMs) is prevalent in automotive and vehicle traction applications due to their high efficiency over a wide speed range. Given the high-power-density requirements of automotive IPMSMs, it is imperative to consider the effect of nonlinearities, such as saturation and cross-coupling, on the motor model. The aforementioned nonlinearities render conventional linear motor models incapable of accurately describing the operating characteristics of the IPMSM, including the maximum torque per ampere (MTPA) trajectory, the flux-weakening (FW) trajectory, and the maximum torque per volt (MTPV) trajectory. With respect to the linear motor model, the nonlinear flux-linkage model is gradually receiving attention from researchers. This modeling method represents the nonlinear behavior of the motor through the direct establishment of a bidirectional mapping relationship between flux-linkage and current. It is capable of naturally incorporating the effects of magnetic saturation and cross-coupling factors. However, the analysis of the current trajectory optimal criteria based on this model has not yet been reported. In this paper, the optimal criteria for the MTPA and MTPV current trajectories are analyzed based on the nonlinear flux-linkage model of IPMSMs. Firstly, the nonlinear flux-linkage model of the tested IPMSM is established by the experimental calibration method. The mathematical analytical expressions of the MTPA and MTPV optimal criteria are then analyzed by constructing and solving optimal problems with different objectives. Finally, the current command table applicable to actual motor control is constructed by calculating the current command for different operating conditions according to the optimal criteria proposed in this paper. The validity and feasibility of the optimal criteria proposed in this paper are verified through experimental tests on different operating conditions. Full article

Synchronous reluctance machines are considered a cost-effective solution for several industrial applications and present potential efficiency benefits compared to induction motors. In industrial applications, power supply oscillations can lead to short-term disturbances that can affect the drive operation; therefore, the control must be robust to guarantee high efficiency and service continuity. The focus of this study was to identify the speed boundaries considering different values of applied DC-link voltage, taking into account the highly nonlinear magnetic behavior of the machine and its cross-coupling characteristics. In addition, a comprehensive carrier-based implementation of a pulse width modulation strategy was proposed to achieve optimal efficiency in both the machine and converter, which is essential in the presence of “weak” grids. The proposed technique was demonstrated to meet the desired reference torque and rated speed, even during DC-link voltage drops (up to 7.4% of the rated voltage). The proposed methodology was experimentally validated on a 90 kW SynRM drive with a broader modulation range and higher efficiency. This work considered several different supply voltage levels to assess the stability and continuity of torque output and further proved the proposed method. Full article