Search Results (4,461)

This paper proposes a parameter identification method for maximum torque per ampere (MTPA) control of an asymmetrical six-phase permanent magnet synchronous motor (PMSM) using a dual three-phase drive without additional motor-terminal voltage sensors. The proposed method measures the common-mode (CM) flux-linkage maps and identifies the CM dq-axis inductances and permanent-magnet flux linkage. For asymmetrical six-phase PMSMs, the CM subspace is equivalent to the fundamental torque-producing subspace in the vector space decomposition (VSD) model. An angle-scanning MTPA strategy is then implemented to determine the optimal current-vector angle. Finally, the identified parameters are validated through torque and power measurements obtained from dynamometer experiments. Experimental results demonstrate that the proposed method can accurately identify the MTPA operating point. The identified parameter model also provides accurate torque prediction, with an error of only 1% at the rated torque of 1363.5 N·m, while the measured torque at 600 rpm differs from the standstill value by only 19 N·m (1.4% of the rated torque). Full article

The new inductor-capacitor-trap (LCT) filter can further suppress high-frequency current harmonics around the switching frequency, so it is important for the permanent magnet synchronous motor (PMSM); however, resonance problems caused by the LCT filter will affect system stability. Active damping is essential to suppress the system resonance. However, with the traditional damping schemes, such as capacitor current feedback (CCF) control, the damping effect and the dynamic response of the LCT-filtered PMSM are difficult to improve simultaneously. In this article, based on the inverter current and motor voltage, a novel two-variable feedback active damping method for the LCT-filtered (TVF-LCT) PMSM is proposed to enhance the damping effect with fast dynamic performance. The TVF-LCT damping parameters are designed; moreover, the stability, damping effect and dynamic performance of the proposed TVF-LCT damping current loop are analyzed. With the undamped LCT, traditional CCF-LCT, and the proposed TVF-LCT damping schemes, the comparative experimental results verify the effectiveness of the proposed TVF-LCT damping scheme. Full article

Sensorless control of surface-mounted permanent magnet synchronous motors (SPMSMs) over a wide speed range is challenged by weak low-speed back electromotive force, limited transient performance of fixed-gain flux observers, and discontinuities during the transition between startup and observer-based control. This study proposes an integrated sensorless control framework combining a current- and frequency-compensated I/F startup strategy, a load-adaptive current-amplitude transition, and a variable-step nonlinear flux observer. The observer adaptively adjusts its gain according to the evolution of the objective function to balance convergence speed and estimation stability, while load-based current compensation and active-power-based frequency compensation improve low-speed load adaptability. The transition gain is further adjusted according to load conditions to coordinate current reduction and control-mode switching. Experiments on an SPMSM drive validate zero-speed startup, I/F-to-closed-loop transition, forward/reverse operation, speed variations up to 2000 rpm, and load disturbances. Under a load step from 0.4 to 0.6 N·m, conventional I/F control lost synchronism, whereas the proposed strategy maintained stable operation. Under medium-to-high-speed load disturbances, the variable-step observer consistently reduced transient speed- and rotor-position-estimation deviations compared with the conventional observer. The results demonstrate coordinated sensorless operation and improved dynamic performance over the tested wide speed range. Full article

This work develops a grid-forming control framework integrated with supplementary energy storage, so that permanent-magnet direct-drive wind turbines can deliver primary frequency regulation and inertial support services. Current stability research commonly concentrates on turbine-grid interactions, yet overlooks coupling dynamics at the DC-link, which motivates this study to establish a quantitative stability evaluation approach for grid-forming wind-storage systems with DC-side coupling taken into consideration. Small-signal impedance representations are firstly constructed for the machine-side converter (MSC), grid-side converter (GSC), and energy-storage converter with respect to the DC-link. On this basis, quantitative investigation is carried out to clarify how grid stiffness, inertia coefficient, droop gain, as well as charging/discharging operating modes of energy storage shape the DC-side stability margin of the hybrid system. To boost DC-link electrical damping, a supplementary stabilizing control scheme is embedded within the control loops of the energy-storage converter. Simulation outcomes reveal that the inertial support loop may inject negative damping and impair DC-link stability. Besides, discharging operation yields better stability performance for the wind-storage configuration relative to the charging condition. The devised stabilizing controller is capable of strengthening DC-side stability, enabling simultaneous inertial response and primary frequency support. Validations based on the PSCAD/EMTDC environment confirm the accuracy of theoretical deductions and the practical performance of the presented control solution. Full article

Accurate, real-time temperature monitoring of traction motors, battery packs, and power electronic modules is a critical requirement for the safety, efficiency, and long-term reliability of electric vehicles (EVs), particularly on the curved, space-constrained, and vibration-prone surfaces found on motor end-windings, battery-module casings, and busbar assemblies. To meet the needs of such automotive curved-surface applications, as well as wearable devices and flexible electronic skin, this paper presents complementary metal-oxide-semiconductor (CMOS) temperature sensor. Its core includes a CMOS sensor chip with an integrated bandgap reference circuit and dual-path electrostatic discharge (ESD) protection, combined with flexible printed circuit board (FPCB/FPC) for conformal mounting on curved surfaces. Circuit-level simulation predicts a typical reference-voltage temperature coefficient of 20 ppm/°C over −40 to 125 °C, while experimental temperature characterization yields a temperature output (TEMP) sensitivity of approximately 5.0 mV/°C over the reported temperature range. Absolute temperature error and linearity are not claimed as independently verified performance metrics in the present revision because the currently available experimental documentation does not preserve the reference-temperature calibration traceability, repeated-measurement information, measurement-uncertainty analysis, or calculation definitions required to substantiate the previously reported ±1 °C and 0.99% values. After flexible integration and 100 bending cycles at a 10 mm radius, the reference-voltage variation remains below 0.1%, while the reported temperature-equivalent TEMP-output shift remains within ±0.5 °C under the tested laboratory conditions. These results demonstrate short-term laboratory bending stability and temperature-sensing performance under the tested conditions rather than long-term fatigue or automotive vibration qualification. The proposed sensor therefore demonstrates potential for curved and space-constrained thermal-monitoring applications, including permanent magnet synchronous motor (PMSM) stator windings and battery-module surfaces, while validation on actual EV components and formal automotive qualification remain necessary for production deployment. Full article

Improving energy efficiency while maintaining accurate force and displacement control is a key requirement for servo deep-drawing die-cushion systems. Electro-hydraulic actuators (EHAs), which combine the high power density of hydraulic transmission with the controllability of electric drives, provide an effective approach for improving the dynamic performance and energy efficiency of metal-forming equipment. This paper investigates the control and energy-efficiency characteristics of an EHA applied to a servo deep-drawing die-cushion system, with particular emphasis on the working mechanism of its hydraulic system, the AMESim-Simulink co-simulation control strategy, and the energy-efficiency distribution characteristics. Firstly, an electro-hydrostatic actuator (EHA) model composed of a permanent magnet synchronous motor, a fixed-displacement pump, valve block unit, accumulator, and single-rod double-acting hydraulic cylinder is established. The power flow relationship of the system in the four-quadrant working condition is analyzed, and the flow distribution characteristics of the main oil circuit, supplementary oil circuit, and bypass branch are studied. Secondly, a joint simulation platform is built based on AMESim and Simulink to achieve bidirectional coupling between the hydraulic actuator and the motor drive control system. In the speed control loop, the traditional PI and fuzzy PI control strategies are compared; in the position control loop, the PID control and sliding mode control strategies are simulated and analyzed. The results show that the fuzzy PI control has better dynamic regulation ability under load torque and speed step change conditions, which can reduce speed overshoot and shorten the regulation process; the position-control results under a step-displacement command show that the sliding-mode controller improves the transient response and steady-state tracking accuracy compared with the conventional PID controller. Finally, the system’s four-quadrant energy efficiency, motor efficiency, pump volumetric efficiency, and mechanical efficiency are analyzed from the perspective of energy conversion. The results show that the system efficiency is affected by load, actuator speed, motor speed, and pump pressure difference, and the efficient working area is mainly distributed in the medium-high speed and moderate load range. Full article

Ultrasonic guided waves acquired using permanently bonded piezoelectric transducers enable large-area monitoring of composite structures. For practical structural health monitoring; however, both the location and the condition of a structural change are critical. This paper presents a data-driven multi-task framework for a carbon-fiber-reinforced polymer plate using a circular PZT array. To generate a large, precise, and repeatable experimental dataset without permanently damaging the specimen, paired magnets were placed on opposite surfaces of the plate and moved using a two-axis positioning system over a uniform grid. Four magnet-pair configurations were used to form four balanced experimental classes. For each case, ultrasonic guided-wave signals from all actuator–sensor paths were concatenated and processed by a shared convolutional neural network and long short-term memory architecture. The model simultaneously estimates the spatial coordinates through two regression branches and identifies the magnet-pair perturbation configuration through a classification branch. An automated hyperparameter search was used to select the principal architectural and training parameters. Performance was evaluated using five-fold training/validation cross-validation. The selected configuration achieved a classification accuracy of $0.9875\pm 0.005$ and a macro F1-score of $0.9876\pm 0.0048$. The mean normalized Euclidean localization error was $0.0228\pm 0.0009$, and $99.43\%$ of the de-normalized localization errors were at or below $20\mathrm{mm}$. The shared architecture therefore performs simultaneous perturbation-configuration classification and two-dimensional localization from the same multi-path guided-wave measurements under the investigated controlled perturbation conditions. Full article

The Gulf of Thailand presents a mild but consistent wave energy resource that remains largely untapped. This study investigates the hydrodynamic and aerodynamic performance of a breakwater-integrated Oscillating Water Column (OWC) coupled with a Wells turbine and a 10 kW direct-drive Permanent Magnet Synchronous Generator (PMSG). A comprehensive 3D Computational Fluid Dynamics (CFD) wave-to-generator model was developed using Ansys Fluent. The Volume of Fluid (VOF) method tracked the air-water interface, while a 6-Degrees of Freedom (6-DOF) dynamic mesh technique resolved the true transient acceleration of the turbine rotor. Regular 5th-order Stokes waves ($H=0.5$ to $2.5\mathrm{m}$, $T=4$ and $6\mathrm{s}$) representing shallow water conditions (depth 10 m) were simulated. The coupled electro-mechanical results demonstrated that under the damping of the PMSG, the turbine operated stably at loaded rotational speeds of 254–340 RPM, safely mitigating free-wheeling overspeed. Notably, the system delivered an average electrical power of 4.37 kW under mild sea states ($H=0.5\mathrm{m}$) due to a hydrodynamic funneling effect between the detached breakwaters and the OWC structure. Conversely, under extreme monsoon conditions ($H=2.5\mathrm{m}$), the average power saturated at 5.08 kW (with a 7.71 kW peak) due to wave breaking and destructive interference from strong backwash. These findings validate the techno-economic feasibility of integrating OWC systems into existing coastal infrastructure to maximize energy extraction in low-wave-energy climates, offering a sustainable power solution for coastal microgrids in Southeast Asia. Full article

The virtual synchronous generator serves as a critical interface between renewable generation systems and the grid, providing inertia to support both active and reactive power. Based on the duality principle, a virtual permanent-capacitor synchronous generator is derived to enhance the inertia of the three-phase current-source inverter, exhibiting dynamic characteristics similar to those of a virtual permanent-magnet synchronous generator. Additionally, this work presents a unified virtual synchronous generator model applicable to both voltage-source and current-source topologies. By constructing a suitable Lyapunov function candidate, the stability criteria of the unified model under standalone operation are established. The Lyapunov function candidate is constructed as a Bregman divergence, whose monotonic decrease characterizes the convergence to synchronous equilibrium. In grid-connected mode, a frequency-locking condition is derived to ensure synchronization of the virtual synchronous generators with the grid. Eigenvalue analysis is employed to assess the stability of the unified model under frequency-locking conditions. The correctness of the derived stability conditions in standalone and grid-connected modes is confirmed through time-domain simulations. Full article

The interest in maximizing sustainable energy sources has recently increased worldwide as a result of an increase in energy demand. For nations with coastal boundaries, electric energy generation from sea or ocean waves represents a possible source of sustainable energy. It turns out that sea wave frequencies as well as heights may differ from one geographical location to another. In other words, maximization of sea wave energy harvesting necessitates tailoring the harvester to the expected coastal conditions. This paper presents a design optimization of a coreless permanent magnet linear generator for southern Mediterranean Sea wave energy conversion. In this work, sea wave data of the aforementioned Mediterranean Sea zone are taken into consideration in the design of the coreless permanent magnet generator. Design and simulation of the generator are carried out using a precise two- and three-dimensional analytical formulation, and optimization is carried out using the particle swarm (PSO) and genetic algorithm (GA) optimization techniques. These simulation results offer qualitative and quantitative insights on numerous aspects, including induced voltage and output power. A coreless sea wave generator design, achieved using three-dimensional analytical computations and PSO, capable of generating 116.54 V and 197.4 W ais presented in the paper. This design offers a maximum induced voltage per unit volume and unit velocity of about 67 K. Details of the design, simulations, and comparisons with samples of similar previously published generators are given in the paper. Full article

Sensor fault diagnosis for direct-drive electric vehicle in-wheel motor systems faces significant challenges under complex operating conditions. Specifically, signal disturbances such as noise interference, model uncertainty, and environmental factors often cause residual distortion, masking fault features and increasing false alarm rates. To address these challenges, a fault diagnosis method based on data-driven subspace identification and residual anti-interference filtering is proposed. Firstly, a state space model of the permanent magnet brushless DC motor is established, and a subspace identification algorithm is combined to construct a discrete system model considering disturbances. An adaptive residual filter is designed to suppress the influence of disturbances on residual signals, and predictive time-domain rolling optimization of residual estimation is introduced. Furthermore, the maximum likelihood ratio is used to construct adaptive thresholds to enhance fault sensitivity and robustness. The bench and real vehicle experiments show that this method can effectively extract fault features under noise and uncertainty interference, significantly improve the fault localization accuracy of current and speed sensors, reduce false alarm rates, and provide technical support for the reliable operation of direct-drive motor systems. Full article

The Permanent Magnet Synchronous Mud Generator (PMSMG) serves as the primary power source for downhole power supply systems in oilfields that operate in high-temperature environments. Given that the PMSMG functions under complex conditions, precise rotor position information is of paramount importance. However, high-temperature mechanical position sensors are not only cost-prohibitive but also face significant challenges regarding lifespan and reliability. While sensorless control technology emerges as a promising alternative, it encounters estimation biases caused by temperature-induced parameter variations. To address these issues, this paper proposes a sensorless control strategy utilizing a super-twisting sliding mode observer (ST-SMO) integrated with phase-locked loop (PLL) parameter perturbation compensation. Two Linear Extended State Observers (LESOs) with distinct bandwidths are employed to estimate system disturbances, and a disturbance decoupling method is proposed to isolate perturbations specifically arising from parameter variations. A feedforward compensation mechanism, based on these parameter-induced disturbances, is introduced before the PLL loop filter. This approach corrects the phase detector zero-point at its source, ensuring that the PI regulator adjusts solely for the authentic phase difference. By circumventing complex parameter identification, this method significantly enhances the robustness and steady-state accuracy of position estimation across the entire speed range. Finally, simulation results validate the effectiveness of the proposed methodology. Full article

The economic value of rare earth elements (REE) is concentrated in Nd, Pr, Dy and Tb. The supply chain for these elements is dominated by a single country, China, which accounts for about 60% of mined production, over 90% of refinement, and nearly 95% of permanent magnet manufacturing. This shifts the critical question from geological availability to the capacity to convert resources into products. Chile hosts several domain types for REE: ion-adsorption regoliths, primary mineralization associated with skarn, iron oxide–apatite (IOA) and iron oxide copper–gold (IOCG) systems, pegmatites and placers, and an Exclusive Economic Zone with marine occurrences. The inventory is organized using a five-level evidence scale, compiled through structured searches of indexed databases and institutional repositories under explicit inclusion criteria. Only one record reaches level 1, Penco, with 27.5 Mt Measured and Indicated at 2292 ppm TREO and 62.9 kt contained TREO. Its grade is two to three times higher than that of ion-adsorption deposits abroad, but its tonnage is one to two orders of magnitude lower. Recoveries vary by element, from 19.53% for Nd to 43.23% for Dy, meaning that the REE oxide it contains does not equate to fully recoverable product. Nahuelbuta reaches 2000 ppm exchangeable, Cerro Carmen contributes 19.81 Mt containing 8203 t of rare earth materials and 1811 t of U, and El Buitre contains 6.6 Mt at 337 mg/kg. Reported concentrations span four orders of magnitude, but only two of the five measurement scales include an associated tonnage. Metallurgical recoverability follows the same pattern: saline desorption is mature and retains Th and U in the solid residue, acid leaching of copper residues reaches 64.5% at laboratory scale, the monazite–xenotime and apatite routes are proven but untested on Chilean material, and no domain has demonstrated separation capability. Opportunities lie in by-product recovery from iron and copper operations, modular development of the central-southern corridor, and domestic separation. Converting the available evidence into comparable figures would reshape the national hierarchy more than additional exploration. Full article

This paper presents a fault diagnosis approach for a five-level Cascaded H-Bridge Multilevel Inverter (CHBMI) supplying an Interior Permanent Magnet Synchronous Motor (IPMSM). The method is based on a two-dimensional Convolutional Neural Network (2D CNN) designed to process voltage signals converted into image representations. In particular, the inverter voltage waveforms are transformed into grayscale images through a time-series reshaping procedure. This allows for the model to capture spatial patterns associated with different fault conditions, including both open-circuit and short-circuit faults. A multi-branch CNN architecture is adopted to simultaneously process multiple voltage signals, improving the ability to distinguish between fault types and locations. The proposed framework is evaluated on a dataset including 17 operating conditions under different speed and load profiles. The results confirm that the proposed approach provides accurate and reliable fault detection and is suitable for real-time diagnostic applications in multilevel inverter-based drive systems. Full article

This article introduces an adaptive fuzzy logic controller with an anti-windup mechanism (AFLC-AW) for enhancing dynamic control of permanent magnet synchronous generator (PMSG)-based wind power plants (WPPs). The proposed controller imposes maximum power point tracking (MPPT), reactive power control, and DC-link voltage regulation while mitigating actuator saturation and improving transient behavior. AFLC-AW’s performance is compared with proportional integral (PI), PI with anti-windup (PI-AW), and adaptive fuzzy logic controllers (AFLCs). AFLC-AW mitigates oscillations and overshoots. PMSG based on WPP is emulated and modeled with the Matlab/Simulink 2026a software. An experimental study was conducted using the Dspace DS 1104 control board in order to verify the simulation results. Results demonstrate that AFLC-AW provides faster tracking, lower overshoot, improved damping, and higher steady-state accuracy under varying wind conditions. Rotor-speed tracking performance improves by 64.32%, 40.36%, and 32.63% compared with PI, PI-AW, and AFLC, respectively. The AFLC-AW reduces the mean of six IAEs by 16.16% compared to the PI-AW, 5.89% relative to the AFLC, and 22.34% in comparison with the conventional PI controller. These results confirm that AFLC-AW enhances tracking accuracy while providing a practical control solution for efficient energy extraction and stable grid integration of PMSG-based wind energy systems. Full article