Search Results (219)

The core outlet temperature is an important safety parameter for pressurized water reactors (PWRs), and its accurate determination depends on highly reliable thermocouple sensors. In this study, two typical commercial K-type thermocouple alloys (de1 and de2) were used to fabricate mineral-insulated metal-sheathed (MIMS) thermocouples. A comparative severe accelerated aging test at 500 °C for 168 h was performed to investigate electromotive force (EMF) stability under high-temperature exposure conditions. After aging, both alloy types exhibited obvious positive EMF drift, and the maximum drift magnitude appeared at the calibration temperature of 400 °C. The measured irreversible EMF drift of de2 thermocouples was lower than that of de1 thermocouples. For the same de2 alloy, thermocouples fabricated with pre-oxidized thermoelement wires presented smaller irreversible drift than those made of bright wires. Reversible EMF drift and heating–cooling calibration hysteresis were more significant for de1 specimens. Stabilization treatment at 570 °C for 2 h followed by furnace cooling effectively reduced the thermal hysteresis of both alloys during temperature cycling. This study provides straightforward experimental data and practical processing references for optimizing the manufacturing route of nuclear-grade MIMS thermocouples with improved high-temperature EMF stability. Full article

The permanent magnet synchronous linear motor (PMSLM) is a key technology for the ultra-high-speed acceleration in maglev transport systems over short distances. It has attracted significant research interest owing to its high power density, high efficiency, and excellent control performance. Nevertheless, the design of such motors faces several challenges. These include the accurate calculation of inductance parameters and the achievement of high thrust force density. To overcome these issues, this study first derives analytical expressions for per-unit-length inductance and thrust force. Based on these, key electromagnetic parameters and structural parameters of the motor are designed. A segmented design scheme is also proposed. A finite element model of a bilateral long-stator PMSLM is then established using Ansys Maxwell. Simulations are performed to analyze the motor’s back electromotive force (EMF), electromagnetic thrust force, inductance distribution, and induced voltage. The results show a good agreement between the simulation and theory. The error in inductance calculations ranges from −5.5% to +6.65%. The absolute error between the calculated and simulated thrust force values is below 0.8 kN. Furthermore, the non-uniformity in inductance distribution and the causes of thrust force fluctuation are investigated. Odd-order harmonics, such as the third and fifth, are identified in the induced voltage. This research offers a design methodology and simulation verification for ultra-high-speed PMSLMs. It lays a foundation for the future development of end-effect compensation and harmonic suppression strategies. Full article

Field-oriented control and direct torque control of induction-motor (IM) drives, and conventional finite-control-set model predictive control (FCS-MPC), all depend explicitly on machine parameters that drift with temperature and saturation, degrading current quality and, for the predictive case, even threatening closed-loop stability. This paper develops a parameter-robust, weighting-factor-less model-free predictive current control (MFPCC) for IM drives, in which the lumped disturbance of an ultra-local model is reconstructed online by a linear extended-state observer (ESO) and the inverter state is chosen by a current-only cost function. A two-step ($k+2$) prediction horizon is utilized to explicitly compensate for the one-sample microprocessor computation-and-actuation delay inherent to digital predictive control. The speed loop is governed by a model-free intelligent-proportional controller; thus, no proportional-integral current regulator and no machine parameter appear in the control path, with the single exception of the ultra-local model design gain $\mathsf{\alpha }$, which is fixed at the nominal input gain $1/\left(\mathsf{\sigma } {\mathrm{L}}_{\mathrm{s}}\right)$ to establish parameter robustness. A comparative disturbance-observer study shows that the finite-difference estimator amplifies measurement noise and that an adaptive super-twisting observer cannot track the fast back electromotive force (back-EMF)-dominated lumped term of the IM at practical sampling rates, whereas the ESO tracks it faithfully (correlation 0.98). Under full inverter non-idealities (3 µs dead-time, 12-bit quantization, 50 mA offset, and 3% DC-link ripple), the proposed scheme attains 3.2% stator-current THD, matching an accurately tuned model-based FCS-MPC (3.9%) and significantly outperforming the finite-difference baseline (11.3%) while using none of the five machine parameters. Closed-loop stability and robust tracking are confirmed via a 50-run Monte-Carlo study, while a DSP timing estimate confirms real-time feasibility. Full article

This study investigates the influence of cold-working deformation on the electromotive force (EMF) calibration characteristics, hysteresis behavior, and long-term stability of the Type-K mineral-insulated metal-sheathed (MIMS) thermocouples used in Combination Fixed In-Core Detector Assemblies for pressurized water reactor nuclear power plants. Reduction ratios of 12%, 28%, and 38% were investigated, and samples were subjected to heating–cooling calibration and in situ aging tests. The results show that increased cold-working deformation leads to greater negative EMF deviation and larger heating–cooling hysteresis, mainly affected by the degradation of the positive KP thermoelement. Cold-working lowers the atomic diffusion activation energy and accelerates element migration, resulting in pronounced EMF drift during isothermal aging at 350 °C for 720 h. After aging below the order–disorder transition temperature, stable ordered structures form in the thermoelement alloys and hysteresis is significantly reduced. However, within the range investigated in this study, deformation above 28% imparts irreversible effects. The EMFs of 28% and 38% deformed samples remained lower than that of the undeformed state even after isothermal aging at 700 °C for 500 h. These findings reveal that excessive cold-working deformation severely impairs the measurement accuracy and long-term stability of the thermocouples, highlighting the necessity of the strict control of drawing deformation to ensure the reliability of nuclear-grade thermocouples under both normal and abnormal reactor operating conditions. Full article

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

As the offshore wind industry scales toward 15 MW capacity, the reliability of Direct-Drive Permanent Magnet Synchronous Generators (DD-PMSGs) becomes critical. However, real-world run-to-failure data for these massive, multi-pole machines is virtually non-existent, creating a barrier for developing effective data-driven diagnostic systems. This study proposes a high-fidelity framework for detecting permanent magnet faults in the International Energy Agency (IEA) 15 MW Reference Wind Turbine. Using Finite Element Analysis (FEA), a dataset (magnetic flux and back electromotive-force (EMF)) capturing the electromagnetic signatures of healthy and faulty states of a PMSG under varying severities is generated. To improve the power of computer vision, 1D time-series signals were transformed into 2D images. Specifically, Gramian Angular Fields (GAFs) and Recurrence Plots (RPs) were applied to magnetic flux density signals, while Markov Transition Fields (MTFs) were applied to back-EMF signals. These representations were then fused into multi-channel Red-Green-Blue (RGB) images and processed via a ResNet-18 Deep Transfer Learning model using a strictly non-overlapping, leakage-free dataset partitioning strategy. The proposed framework achieved a classification accuracy of 99.45% on noise-free data. Furthermore, robustness testing under varying levels of Additive White Gaussian Noise (AWGN) (30 dB, 40 dB, and 50 dB Signal-to-Noise Ratio (SNR)) demonstrated sustained high performance, maintaining over 90% accuracy even under severe 30 dB noise conditions. Comparative analysis proved that this multi-channel fusion significantly outperforms single-channel encoding methods, which collapse under heavy noise, validating the scalability of the framework and applicability for next-generation condition monitoring in harsh offshore environments. Full article

Interior permanent magnet synchronous motor (IPMSM) has advantages with high power density, wide speed range, small size, and high efficiency, and is widely used in the drive system of electric vehicles. Compared to other types of motors, permanent magnet synchronous motors (PMSMs) have some irreplaceable advantages, but there are also some disadvantages. As a type of PMSM, IPMSMs have problems with large fluctuations in permanent magnet (PM) magnetic field and demagnetization. At present, irreversible demagnetization of PMs is the most serious problem faced by IPMSMs. Once irreversible demagnetization of PMs occurs, it can cause a decrease in the performance of IPMSMs and can even damage the entire drive system. This paper takes an IPMSM with 48 slots, 8 poles, and 66 kW as the research object. Based on the reasons for PM demagnetization, a PM demagnetization model is established to obtain the demagnetization law of PMs. Firstly, the magnetic properties of PM materials were described based on their characteristic curves. The demagnetization mechanism of PMs was analyzed, and the demagnetization process of PMs was studied in combination with the reasons for demagnetization. Secondly, the basic parameters and torque performance of IPMSMs were calculated and analyzed. We analyzed the demagnetization curves of PM materials at different temperatures, calculated the operating points of PMs under various working conditions, and analyzed whether PMs undergo irreversible demagnetization based on the relationship between the operating points of PMs and the knee points of demagnetization curves. A high-fidelity electromagnetic–thermal coupling simulation model has been established, combined with the characteristics of electric vehicle driving conditions, to accurately characterize the temperature rise distribution and electromagnetic parameter changes of IPMSMs under different operating conditions and achieve multi-physics field collaborative analysis. Finally, a finite element model is adopted to simulate uniform and local demagnetization of PMs, and the changing characteristics of motor performance parameters under demagnetization are summarized. Different magnitudes of d-axis reverse current are applied as demagnetization excitation to analyze PM behaviors under various demagnetization degrees. The variations in magnetic flux density, output torque, and no-load back electromotive force (EMF) before and after demagnetization are simulated and analyzed. For the investigated motor and specific magnet grade, this work summarizes the irreversible demagnetization characteristics and corresponding practical judgment references. Full article

To address the increasingly prominent challenges of “low inertia” and “weak damping” in modern power systems, grid-forming (GFM) control technologies with inertia and damping support capabilities are being extensively adopted. However, distributed generation units interfaced with GFM inverters are highly susceptible to overcurrent phenomena during grid short-circuit faults. Existing research primarily focuses on current-limiting control strategies for virtual synchronous generators (VSGs), while investigations into their fault current characteristics remain insufficient. Given this, this paper proposes a short-circuit current calculation methodology for VSG-based PV-storage grid-connected systems. First, a model of a grid-forming PV-storage grid-connected system based on virtual synchronous control is established. Subsequently, the virtual impedance is solved within the timescale of current inner-loop stabilization, and the virtual internal electromotive force (EMF) equation for the VSG is formulated. This leads to the derivation of an analytical expression for the VSG short-circuit current, accounting for variations in the virtual internal potential. Furthermore, the impacts of diverse control parameters and fault severities on the short-circuit current are investigated based on this expression. Finally, simulations are conducted on the MATLAB/Simulink(R2024b) platform to validate the accuracy of the proposed short-circuit current calculation method and the correctness of the analysis regarding the influencing factors. Full article

Under ideal trapezoidal back electromotive force (EMF) conditions, a brushless direct current (BLDC) motor can produce constant instantaneous electromagnetic torque when supplied with ideal three-phase square-wave currents. However, this operating mode may result in relatively high copper loss. In practical applications, where both the back-EMF and the current waveforms deviate from their ideal shapes, significant torque ripple is introduced. To address these issues, this paper proposes a maximum torque per ampere (MTPA) control strategy for BLDC motors based on zero-sequence current injection. An improved Park (3s–3r) is employed to develop the mathematical model, in which the synthesized non-zero-sequence components are mapped exclusively onto the q-axis. By properly regulating the d-axis and 0-axis reference currents, the proposed strategy achieves minimum copper loss operation. Based on this framework, a torque control system incorporating zero-sequence current injection is established to further enhance performance. The feasibility and effectiveness of the proposed control strategy are validated through digital signal processing (DSP)-based experimental results. Full article

This study presents a stator-focused electromagnetic optimization of a 350 W, 27-slot, 30-pole outer-rotor brushless direct current (BLDC) motor developed for electric scooter applications. Unlike conventional redesign approaches that modify rotor topology or overall motor dimensions, the proposed methodology preserves the rotor structure and external geometry of a commercially validated reference motor and improves performance primarily through targeted stator geometric refinement, with minor adjustments in the winding configuration. A two-stage optimization strategy combining parametric analysis and genetic algorithm (GA)-based multi-objective optimization is implemented to minimize cogging torque and torque ripple while maximizing efficiency. Finite element analyses (FEA) were conducted to evaluate back electromotive force (back-EMF) characteristics, magnetic flux density distribution, torque behavior, and current density. Experimental validation confirms a 54.86% reduction in cogging torque (from 257 mNm to 116 mNm), a 19.6% decrease in torque ripple, a 6.17% reduction in maximum current density, and a 2–3% improvement in efficiency within the nominal load range (5.2–6.45 Nm), reaching 85.69% efficiency at 350 W output power. The results demonstrate that systematic stator geometry optimization, supported by minor winding modifications, can significantly enhance efficiency, torque smoothness, and thermal margin without increasing motor size, rated power, or manufacturing complexity. This work provides a practical and manufacturable design pathway for high-performance outer rotor BLDC motors in light electric vehicle (LEV) propulsion systems. Full article

In order to simplify the stator winding structure of traditional variable reluctance (VR) resolvers and enhance their performance under high-speed operating conditions, this paper proposes a design for a variable reluctance self-coupling resolver based on ultrahigh-frequency (UHF) square wave excitation. The proposed solution optimizes the traditional winding structure by eliminating the separate excitation winding and integrating both excitation and detection functions into the two-phase sine and cosine windings. By optimizing the arrangement of the sine and cosine windings, a single-layer equal-turn winding design is successfully implemented, significantly simplifying the winding layout and reducing copper usage. In terms of excitation signal, this paper innovatively replaces the traditional sinusoidal excitation with UHF square wave excitation. Compared to sinusoidal excitation, square wave excitation not only generates higher electromotive force (EMF) peaks but also simplifies engineering implementation, reducing the complexity of system hardware. To validate the feasibility and advantages of the proposed structure, a complete experimental testing platform was built, and comparative experiments were conducted under various rotational speeds. The experimental results show that the proposed self-coupling resolver can achieve high-precision rotor position detection across the entire speed range, significantly improving the detection accuracy and dynamic response of traditional methods under high-speed conditions. Ultimately, the design demonstrates strong engineering application potential and provides a new solution for high-precision, high-dynamic response rotor position detection. Full article

Advances in semiconductor technologies, particularly in power transistors and switching diodes, have enabled higher switching frequencies and converter efficiency, renewing interest in Switched Reluctance Motors (SRMs) for electric vehicles. This work presents a data-driven approach utilizing a Long Short-Term Memory (LSTM) network capable of effectively managing temporal dependencies for estimating rotor position without sensors in SRMs. The motor investigated was custom-designed, subsequently manufactured as a prototype. The LSTM was trained and validated with experimental data collected at various speeds and load conditions. The outcomes demonstrate the model’s strong performance, with a mean squared error (MSE) of ${1.77}^{{°}^2}$, a mean absolute error (MAE) of 1.09°, and 97.35% accuracy. Compared to typical estimation methods such as back-electromotive force (EMF)-based techniques, fuzzy logic, model predictive control, feed-forward neural networks (FFNNs), and back-propagation neural networks (BPNNs), the LSTM stands out as one of the most effective and widely used models. Previous neural networks (NN)-based studies typically report ±5° accuracy, whereas LSTM keeps the error about 1° in this study. This strategy eliminates position sensors, reduces cost and complexity, and enables reliable real-time SRM control. Results indicate that the method has significant potential for electric motor drives, particularly for SRMs. Full article

Recently, the demand for electric motors that can achieve high performance while ensuring stable magnet supply has continued to increase across various industrial sectors. Although rare-earth permanent magnets, such as neodymium and samarium cobalt, enable superior electromagnetic performance, their high cost and supply instability have motivated growing interest in motors employing non-rare-earth permanent magnets, such as ferrite magnets. Due to the relatively low remanent flux density and coercivity of non-rare-earth magnets, spoke-type rotor structures are commonly adopted to enhance flux concentration. However, spoke-type configurations inherently suffer from axial leakage flux, in which a portion of the magnetic flux generated by the permanent magnets fails to link with the stator and instead leaks along the axial direction. This axial leakage flux reduces the effective air-gap flux density, leading to a degradation of back electromotive force (back-EMF) and overall motor performance. In this study, a double-spoke-type motor employing asymmetric permanent magnet geometry is investigated. Finite element analysis (FEA) is performed to identify an effective rotor structure that reduces axial leakage flux without increasing magnet usage, demonstrating the feasibility of performance improvement in non-rare-earth permanent magnet motors. Full article

In this paper, a sensorless field-oriented vector control (FOC) strategy combining an improved adaptive sliding mode observer (IASMO) and a finite-position-set phase-locked loop (FPS-PLL) is proposed for a surface permanent magnet synchronous motor (SPMSM) operating in the medium- and high-speed range. Firstly, a sliding mode observer (SMO) that can realize the observation of back electromotive force (back-EMF) is proposed, and an adaptive reaching law that can reduce the sliding mode coefficient is designed to help the SMO observe the back-EMF for the purpose of reducing chattering as well as verifying the stability of the system. Then, the FPS-PLL is used instead of a phase-locked loop (PLL) to extract the rotor position information from the observed back-EMF, thus avoiding the time-consuming process of tuning the PI parameters. The proposed FPS-PLL reduces the number of iterations from 64 to 20 while maintaining effective estimation performance. Finally, the effectiveness of the proposed scheme in suppressing chattering and maintaining comparable estimation accuracy while reducing computational burden is demonstrated by experiments. Full article

Nowadays, sensorless control of permanent magnet synchronous linear motors (PMLSM) is widely utilized in industrial applications due to its inherent cost and spatial advantages. However, existing sensorless control methods for PMLMs face insufficient observation accuracy of states and disturbances and poor variable-speed trajectory tracking. To address these issues, this paper proposes a sensorless control method combining multi-observer coordinated perception and robust adaptive control. Firstly, a sliding mode observer based on an improved saturation switching function is designed, which suppresses current noise with a low-pass filter to achieve unbiased estimation of back electromotive force (EMF). Secondly, an extended state observer with back-EMF as input is constructed to synchronously observe disturbances such as the mover speed, position, and thrust ripple of linear machine. Then, a robust adaptive controller is designed to compensate for system uncertainty via an adaptive law, forming closed-loop control with SVPWM. Compared with the traditional methods, the proposed multi-observer coordinated perception scheme can significantly enhance the observation accuracy of the mover speed, position, and lumped disturbances, and the robust adaptive controller can effectively improve the variable-speed trajectory, tracking performance under system uncertainties. Finally, the simulation results have confirmed the effectiveness of the proposed method in accurately observing and tracking speed and position, providing a feasible solution for high-precision sensorless control of PMLSM. Full article