Search Results (1,090)

In this study, we propose a data-driven diagnostic system that uses Extreme Gradient Boosting (XGBoost) to detect, classify, and assess the severity of multiple faults in permanent magnet synchronous motors (PMSMs). The three main fault categories that are the focus of the suggested method are inter-turn short-circuit (ITSC) faults, stator open-circuit faults, and permanent magnet demagnetization. To capture fault-specific characteristics and their development with severity, discriminative electrical features are retrieved from stator currents, flux linkage, and dq-axis values. Next, using the chosen electrical indications, an aggregated diagnostic index is created to facilitate defect diagnosis and severity quantification in a single learning process. The XGBoost-based model has been shown to produce excellent diagnostic accuracy and robust separation between various fault causes via extensive assessment. It also maintains dependable performance under previously unknown operating or fault situations. These findings show that an XGBoost-only approach offers a scalable and efficient way to monitor advanced PMSM conditions in industrial and safety-critical applications. Full article

With the increasing demand for high speed and high-precision motion control in CNC machine tools, permanent magnet linear synchronous motors (PMLSMs) have been widely adopted in feed drive systems due to their excellent dynamic performance and positioning accuracy. However, existing model predictive current control (MPCC) variants still face challenges regarding high computational overhead and strong dependency on accurate motor parameters, which limit their industrial applicability. To address these issues, this paper proposes an adaptive recursive MPCC for PMLSM drives based on the Cartesian distance minimization principle. An adaptive recursive prediction scheme that is inspired by the feedback structure of recurrent architectures is first introduced. By cyclically utilizing the previously sampled current to predict the next period’s state, the strategy effectively decouples the control law from inductance variations. The dependence on resistance is further mitigated by analyzing the correlation between the ideal current vector and voltage vector deviations. Second, the selection of the optimal voltage vector is transformed into a geometric problem: minimizing the Cartesian distance between the reference voltage and 19 candidate deviations within a proposed virtual voltage vector hexagon. To minimize the computational burden, the vector space is partitioned into eight regions, allowing the optimal candidate to be selected from only two pre-derived deviations. The experimental results demonstrate that the proposed method significantly outperforms existing MPCC benchmarks. Specifically, the execution time is reduced by 63.6%. Under severe parameter mismatch, the current THD is reduced from 14.82% to 6.35%, and the thrust ripple is improved from 12.06 N to 5.25 N, validating its superior robustness and efficiency. Full article

With the growing demand for hybrid and electric vehicles, the accurate prediction of NVH (Noise, Vibration, and Harshness) behavior in Permanent Magnet Synchronous Machines (PMSMs) has become a critical aspect of electric motor design. This paper presents a detailed modeling approach for electromagnetic-induced noise and vibrations in PMSMs, integrating both analytical and numerical methods. The model focuses on quantifying the contributions of radial and tangential electromagnetic forces, which are key drivers of vibro-acoustic responses. The analytical part employs curved beam theory and a simplified acoustic model, offering rapid insights during early design stages. In parallel, a detailed numerical model based on finite element analysis is developed using a physics-based approach that accounts for the actual geometry and material properties of the PMSM prototype. This allows for enhanced accuracy without relying on experimental material parameter identification. Moreover, the detailed model includes the fluid–structure interaction introduced by the channels of the cooling fluid of the electric machine, which, although poorly addressed by the existing literature, was found to play a key role in driving the vibrational behaviour of the structure. By combining analytical speed with numerical precision, the proposed approach enables consistent and physically-based NVH predictions across various design phases, ultimately supporting improved electric machine performance and reducing development time and costs. Validation against experimental data confirms the ability of the model to accurately predict both sound pressure levels and housing surface vibrations. The novelty of this work lies in its integration of fluid–structure interaction and material modeling without the need for empirical parameter tuning, offering a robust tool for NVH design in electric vehicle applications. Full article

This study presents a systematic topological progression and multi-objective optimization of a Permanent Magnet-assisted Non-overlapping Winding Line-Start Synchronous Reluctance Motor (PMaNWLS-SynRM) for industrial applications. To explicitly highlight the core contribution, the research establishes a rigorous comparative framework evaluating the transition from a conventional 4-pole/36-slot distributed winding (DW) to a 2 × 12-slot non-overlapping winding (NW) architecture. Baseline results demonstrate that the NW configuration shortens end-turns, successfully reducing total electromagnetic losses from 417 W to 349 W and improving steady-state efficiency from 93.7% to 95.1%. To overcome the inherent starting limitations of pure synchronous reluctance machines, an aluminum squirrel-cage is integrated to enable robust direct-on-line (DOL) synchronization, while NdFeB permanent magnets are embedded within the rotor flux barriers to mitigate asynchronous spatial harmonics and elevate torque density. Finite element analysis (FEA) confirms this magnetic assistance raises the average synchronous torque to 65.8 Nm while suppressing absolute torque ripple to 1.37 Nm. Finally, an evolutionary genetic algorithm is deployed across 440 iterative configurations to resolve geometric multi-physics conflicts. The finalized optimized design achieves a 13.2 kW output power at 1800 rpm, maximizing average torque to 70.12 Nm and strictly dampening absolute torque ripple to an industry-acceptable 1.04 Nm. Operating with an aggregated total loss of 1382 W, the optimized PMaNWLS-SynRM yields a 90.5% operational efficiency, definitively validating its suitability as an ultra-premium IE4/IE5 alternative to conventional induction motors. Full article

This paper proposes an advanced wind energy conversion and management framework for improving grid integration and mitigating frequency and power fluctuations caused by wind intermittency. The studied system combines a permanent magnet synchronous generator (PMSG), a unidirectional Vienna rectifier on the machine side, a Li-ion battery energy storage system, and a bidirectional Vienna rectifier on the grid side. The main scientific challenge addressed in this work is to ensure efficient wind power extraction, secure battery charging/discharging operation, and stable power exchange with the grid under variable operating conditions. To this end, a comprehensive nonlinear state-space model of the overall system is first established. Then, nonlinear controllers based on integral sliding mode principles are developed to guarantee rotor-speed tracking, DC-bus voltage regulation, battery charging current limitation, and active/reactive power control. In addition, an adaptive observer is designed to estimate the battery open-circuit voltage and support the supervision of the state of charge. An energy management strategy is further proposed to coordinate the operating modes according to grid conditions and battery constraints. Simulation results demonstrate that the proposed approach effectively smooths wind power fluctuations, improves grid support capability, and enhances the overall dynamic performance of the wind energy conversion system. Full article

This study focuses on improving the electromagnetic performance of flux-switching permanent magnet (FSPM) machines as a high-efficiency alternative aligned with the “green industry” concept. FSPM machines offer high torque density and mechanical robustness due to their stator-mounted magnet design; however, they suffer from cogging torque and torque ripple caused by magnet–stator tooth interactions. Three structural optimization methods were applied to a 12-slot, 10-pole reference FSPM machine: rotor notching, unequal rotor slot arc (URSA), and a hybrid approach combining both techniques. Eight models (D0–D7) were analyzed using genetic algorithms and the two-dimensional finite element method (FEM). Results demonstrate significant performance improvements while maintaining power density. The D1 design reduced torque ripple from 9.2% to 1.59%, achieving approximately a sixfold improvement. The D3 design yielded the lowest cogging torque at 0.4 Nm. Hybrid configurations (D5–D7) exhibited consistent performance with high back-EMF amplitude and uniform torque distribution. Physical manufacturability was validated through laser-cut prototype production of the optimized models. These findings highlight the strategic potential of FSPM machines for electric vehicle and industrial automation applications requiring precise positioning and high efficiency. Full article

In the aviation sector, there is a growing demand for high-specific-power electrical machines to realize More Electric Aircraft (MEA). The goals for these machines were set by the National Aeronautics and Space Administration (NASA) as 1 $\mathrm{M}$$\mathrm{W}$ power, >13 kW kg⁻¹ of power density, and efficiency >96%. To address these requirements, this paper proposes an electromagnetic design of a high-speed, power-dense, 1 $\mathrm{M}$$\mathrm{W}$ radial-flux Permanent Magnet Synchronous Machine (PMSM) for aerospace propulsion applications that achieves NASA targets. Achieving high-specific-power objectives necessitates geometry optimization that simultaneously minimizes motor mass while maximizing output power. This paper presents a faster optimization algorithm that hybridizes Genetic Algorithm and Artificial Neural Network (ANN)-based surrogate modeling to optimize the motor for multi-objective goals. The proposed framework employs a multi-objective approach targeting maximum torque output and efficiency within a minimum motor mass. This approach, using an ANN-based surrogate, significantly reduces optimization time by saving 95% of the time compared to FEM simulations. The optimized 1 $\mathrm{M}$$\mathrm{W}$ motor attains 98% efficiency and an active power density of 24.87 kW kg⁻¹. The various stages of the optimization are presented in detail and a comparison of the time saving using the proposed algorithm is outlined. To demonstrate the feasibility of design, a detailed electromagnetic analysis, stator thermal analysis with a jet impingement design, and magnet demagnetization risk analysis were also presented. Full article

This study proposes a vibration reduction strategy for a 12-slot, two-pole permanent magnet brushed DC (PMDC) motor used in automotive blower systems. A multi-parameter optimization framework combining finite element analysis and experimental validation is developed to address cogging torque, a critical source of electromagnetic vibration and acoustic noise. The influence of pole arc coefficient and permanent magnet eccentricity on cogging torque is systematically investigated using response surface methodology, identifying an optimal design with significantly reduced torque ripple and vibration. Furthermore, a machine learning model based on the random forest algorithm is introduced to predict cogging torque, air gap magnetic flux density, and output torque, achieving high accuracy and strong generalizability. The results confirm that the optimized motor structure suppresses resonance-induced noise near 7500 Hz, improving overall motor stability and acoustic performance. The proposed data-driven design approach offers a reliable and efficient pathway for vibration optimization in low-cost automotive PMDC motors. Full article

Tubular flux-switching permanent-magnet linear machines (TFSPMLMs) are difficult to optimize using a single core material because conventional axial laminations suffer from severe in-plane eddy-current loss, whereas soft magnetic composites (SMCs) exhibit lower permeability and higher hysteresis loss. To address this trade-off, three hybrid SMC–laminated steel core configurations were investigated: H1, with radially laminated steel in the yoke; H2, with axially laminated steel in the tooth; and H3, with circumferential laminated steel segments. A reference SMC model (R1) and the three hybrid models were comparatively evaluated using three-dimensional finite element analysis (3D FEA). H1 and H2 showed degraded performance due to an interfacial micro-gap along the main flux path and additional in-plane eddy currents in the laminated steel regions. To mitigate these limitations, circumferential segmentation was applied to the laminated steel parts. With eight segments, H2 achieved a thrust force of 278.8 N, comparable to that of R1, while reducing iron loss by 22.5%; even a two-segment structure provided noticeable improvement. Among the investigated models, H3 showed the best overall performance by avoiding a micro-gap on the main flux path, achieving 285.5 N, and 3.9% higher thrust force and 18% lower iron loss than R1. These results indicate that H3 is the most effective hybrid-core configuration for maximizing both thrust force and loss reduction, whereas segmented H2 is an attractive practical option when manufacturability and low-loss operation are considered. Full article

The increasing demand for electric power in hybrid electric aircraft platforms prompts the development of multi-megawatt generators featuring high specific power, compactness and intrinsic fault tolerance. Air-core machines constitute a promising solution to overcome the magnetic saturation and mass limitations of conventional iron-core designs. This paper presents a comparative electromagnetic design study of two air-core synchronous generator topologies for aircraft applications, namely a permanent magnet machine with a Halbach array rotor and an electrically excited synchronous machine featuring a high-temperature superconducting field winding. Both the generators are designed for identical output and adopt a double three-phase stator winding to enhance safety and redundancy. The Halbach array machine is used as the reference configuration representative of a technologically mature solution, whereas the superconducting generator targets high magnetic loadings by means of the superconducting excitation, to minimize the active volume. The solutions proposed in this paper are developed in the frame of a national (Italian) research project dedicated to the study of stages of multi-megawatt fault-tolerant aircraft generators. Full article

This study presents a systematic literature review on the environmental impact of industrial applications of Rare Earth Elements (REEs), particularly those classified as Critical Raw Materials (CRMs), such as Neodymium alloys. These materials are key components of permanent magnets (PMs) used in electrical machines, including automotive applications, wind turbine generators, and various consumer electronics. A structured methodology began with a comprehensive search across multiple scientific databases utilizing primary and secondary keywords. Studies were selected through a multi-step process, including screening by title, abstract, and full-text review, ensuring the inclusion of relevant and high-quality research. This approach allowed for a rigorous and reproducible assessment of the literature. The review was conducted to address two central issues: the main environmental impacts of using rare earths in permanent magnets for electric motors, and the role of recycling and reuse strategies in reducing them. The review summarizes current knowledge on the life cycle environmental impacts of REEs, from extraction to end-of-life management, highlighting opportunities and challenges in recycling and reuse. While recycling can partially reduce environmental impact, significant gaps remain in efficiency and large-scale feasibility. The literature also emphasizes the substantial impacts of REEs in permanent magnets, including resource depletion, energy use, and emissions. Overall, the study highlights the need to integrate environmental considerations into the design and management of REE-containing systems and identifies research gaps to support more sustainable and efficient materials management. Full article

This work presents the development and validation of a modular low-power wind turbine emulator (WTE) specifically designed for academic research and distributed generation applications. The primary objective is to provide a flexible and cost-effective test bench capable of replicating the aerodynamic and mechanical performance of a bladed rotor without the need for wind tunnels or specific field conditions. The emulator integrates a 4.5 kW three-phase induction machine as the motor and a 1 kW permanent magnet synchronous generator (PMSG). The system is managed by an ARM Cortex M7 microcontroller, which gives instructions to a Siemens Sinamics Variable Frequency Drive (VFD) that is used for torque vector control, offering superior dynamic response to wind speed variations. The aerodynamic characteristics were previously derived using blade element momentum (BEM) theory and validated using MATLAB/Simulink simulations. Unlike traditional steady-state emulators, this study addresses dynamic behavior through an autonomous control algorithm that reduces mechanical stress and compensates for inertia differences. Experimental tests conducted in a grid-connected scenario using a commercial on-grid inverter showed high correlation between the emulator’s output and the field data of a real EOLOCAL AG1000 turbine. The results confirm the system’s reliability as a platform for evaluating power conversion systems and for future expansions, such as blade pitch control emulation. Full article

This paper investigates the electromagnetic performance of an outer-rotor spoke-type permanent magnet synchronous generator intended for small wind turbine applications below 5 kW. The study focuses on the influence of structural ferromagnetic components on magnetic flux distribution and overall machine performance. The generator was initially designed and optimized using 2D finite element analysis, followed by a comprehensive 3D model to account for axial flux leakage and structural details; particular attention was given to the fastening screws used. Experimental validation on a dedicated laboratory test bench confirms the accuracy of the 3D model, mainly at lower wind speeds. The results highlight the necessity of including structural components in three-dimensional electromagnetic modeling for accurate performance prediction of flux-concentrating wind turbine generators. Full article

Online temperature estimation of key components (windings and magnets) in permanent magnet synchronous motors (PMSMs) has emerged as a critical technology for ensuring the safe operation of PMSMs, preventing insulation degradation, and avoiding the demagnetization of magnets. Because of such advantages, online temperature estimation is attracting growing attention from fields with stringent reliability requirements, such as electric vehicles, as well as electrified railway transportation and more/all-electric aircraft, where similar high-reliability demands exist. This paper gives a comprehensive review of the latest and most effective solutions in the online temperature estimation methods for PMSMs. It analyzes the principles, application progress, and limitations of existing methods, including electrical model-based approaches, thermal model-based approaches, and data-driven approaches, in which process the advantages and challenges of different methods are compared. And an outlook on the future application of this technology are summarized. Full article

Permanent magnet synchronous machines (PMSMs) are widely used in high-performance drive systems. However, parasitic torque ripple remains a critical limitation, causing acoustic noise, mechanical vibration, and speed fluctuations. This study presents a compact, model-based torque control strategy for surface-mounted PMSMs (SPMSMs) that suppresses torque ripple by generating a structured current reference. Grounded in the magnetic co-energy principle, the proposed method utilizes a deterministic analytical model to compensate for cogging torque and inductance harmonics, avoiding computationally intensive iterative estimators. A primary contribution involves adapting the harmonic injection profile to varying loads and magnetic saturation levels. Comprehensive finite element analysis (FEA) co-simulations demonstrate that the proposed method reduces torque ripple by approximately 87.5% and speed ripple by over 90% at 1500 RPM compared to conventional maximum torque per ampere (MTPA) strategies. Furthermore, extended dynamic analysis confirms superior robustness during start-up, transients, and low-speed operation (100 RPM), maintaining high control authority even under deep magnetic saturation (2.0 p.u.). Performance evaluations verify that this significant enhancement in torque quality is achieved with a negligible increase in total power losses (~2.1%), presenting a computationally feasible solution for industrial embedded platforms. Full article