Purpose To improve the field-adjustment flexibility of conventional transcranial magnetic stimulation (TMS) coils and reduce the system complexity of multicoil arrays, this study aims to propose a single-coil field-control method based on winding-configuration switching (WCS). Design/methodology/approach An analytical electromagnetic-field calculation model for arbitrarily shaped TMS coils was developed and validated against finite-element simulations. A reconfigurable prototype coil was then fabricated, and its electrical parameters, preliminary high-voltage loading performance and static magnetic-field distributions were experimentally tested. Findings The analytical model agreed well with finite-element results, with maximum errors of 0.83% for the magnetic field and 1.26% for the induced electric field. The calculated results showed quantifiable shifts in the induced electric-field focal positions under two winding configurations. Prototype measurements agreed with analytical predictions, with maximum-field deviations of 0.87% for WC1 and 3.15% for WC2, and peak-normalized errors below 5% along the selected diagonal line. Originality/value The proposed WCS method enables reconfigurable field control by changing the effective turns and current directions within a single coil, providing a new route for low-complexity TMS coil design. This work represents a proof-of-concept study; future work will address automatic high-voltage switching and direct electric-field measurement in conductive phantoms.
Purpose This paper aims to introduce an efficient hybrid model for surface-mounted permanent magnet synchronous machines (SPMSMs) that explicitly takes into account the magnetic nonlinearity in the ferromagnetic regions. Design/methodology/approach The approach combines an analytical subdomain (SD) formulation for the air-gap, magnet and slot regions with a nonlinear 2D magnetic equivalent circuit (MEC) representing the stator teeth and yoke. The SD formulation relies on the exact resolution of Poisson’s and Laplace’s equations using harmonic series. Both models are iteratively coupled through flux sources and a saturation coefficient derived from a variable local permeability scheme. Furthermore, an energetic principle evaluating the stored magnetic energy is introduced to characterize the saturation state. Findings The proposed methodology demonstrates fast numerical convergence and provides a highly detailed description of the magnetic field harmonic spectrum. It successfully quantifies the level of magnetic saturation through the aforementioned energetic principle. Finally, it is validated against time-consuming finite element analysis (FEA) simulations, demonstrating excellent agreement and high accuracy. Originality/value The originality of this work lies in the novel iterative coupling between a precise analytical SD technique and a saturated MEC model, as well as the innovative introduction of an energetic principle to explicitly quantify saturation levels in ferromagnetic circuits. This hybrid concept allows researchers and designers to achieve a substantial computational speed-up compared to purely numerical solutions while successfully preserving accuracy during heavy, localized magnetic saturation.
Purpose Interior permanent magnet synchronous motor (IPMSM) drives may hold speed regulation even after electrical or mechanical faults have changed the stator-current signature. This paper aims to develop a ten-class diagnosis framework that separates healthy, single-fault and compound-fault operation under varying speed and load. Design/methodology/approach A closed-loop IPMSM simulation model generates healthy operation, three inter-turn short-circuit severities, three bearing-related severities and three compound fault cases. From stator-current windows, the features combine wavelet descriptors, speed-normalized frequency bands and electrical-mechanical interaction indicators. ReliefF selects informative variables from the training data, and a hierarchical random forest separates fault-family recognition from severity classification. Direct SVM, k-NN, RF and DQN benchmarks are compared. Findings Under grouped testing, the hierarchical RF with ReliefF gives the best ten-class performance and a clear fault-family path. On the unseen speed/load grid it stays close to the slightly more robust direct RF, and high load is difficult for all classifiers. Family-level recognition on that grid remains at 80.67% accuracy, so the first hierarchical stage generalizes better than the full ten-class decision. Repeating the grouped partition ten times preserves the ordering of the four feature-based classifiers. Noisy currents degrade all models markedly. Originality/value The study combines speed-normalized wavelet features, compound-fault indicators and hierarchical RF classification for IPMSM multi-fault diagnosis; a cautious DQN comparison indicates reinforcement learning is not necessarily superior here. Evaluation uses grouped testing, an unseen speed/load grid, repeated partitions and noise sensitivity.
Purpose This paper aims to compare the magnetic flux saturation characteristics of interior permanent magnet synchronous motors (IPMSM), synchronous reluctance motors (SynRM) and permanent-magnet-assisted synchronous reluctance motors (PmaSynRM) within a single analytical framework. Design/methodology/approach The analysis is based on magnetic equivalent circuits with nonlinear reluctances. A generic circuit is first formulated in the abc frame, then transformed into the dq0 frame and finally simplified to obtain explicit current-flux saturation relationships for the three motor topologies. Findings The resulting model preserves the main electromagnetic features of the machines while highlighting the similarities and differences in their saturation curves. In particular, the approach clarifies how rotor topology affects flux symmetry, saturation behavior and the position of the symmetric point in the current-flux characteristics. Originality/value The paper proposes a unified analytical description, with physical parameters, for comparing the saturation behavior of interior IPMSM, SynRM and PMaSynRM. The model is meant to support comparison and interpretation, rather than to replace high-fidelity models tailored to a specific machine geometry.
Purpose This paper aims to present an optimal direct instantaneous torque control (DITC) based on enhanced linear active disturbance rejection control (LADRC) using a fast modeling approach. Design/methodology/approach First, a fast modeling approach based on the torque balance method and Kriging approximation model is applied, thereby obtaining precise models of magnetic flux and torque. Then, the LADRC with an enhanced extended state observer is designed in the speed controller to improve the speed tracking performance and anti-interference ability of the control system. Furthermore, the firefly algorithm (FA) is used to optimize the angles and tunable parameters in the DITC system to achieve the minimum torque ripple and satisfactory tracking performance. Finally, simulation results verify the effectiveness of the proposed scheme by comparison with conventional DITC with LADRC, the DITC with enhanced LADRC and the proposed DITC using FA. Findings Results show the superiority of the proposed control scheme regarding torque ripple suppression, speed tracking and robustness. Originality/value The proposed scheme is useful for switched reluctance motors to reduce the torque ripple, improve dynamic response and robustness.
