Formation of nanotwins (NTs) is an effective strategy to simultaneously improve the strength and toughness of metallic materials. However, the formation of NTs within the secondary alpha (alpha s) phase of as-cast and heat-treated titanium (Ti) alloys is difficult due to their intrinsically high stacking fault energy (SFE). In this study, NTs are successfully introduced into the alpha s phase of Ti alloys for the first time by precisely tuning the Mo content to tailor the SFE and phase transformation stress to regulate the thermodynamics and kinetics conditions. First-principles calculations reveal that Mo doping reduces SFE and promotes perfect dislocation dissociation into extended dislocations, which creates thermodynamically favorable conditions for twin nucleation. Meanwhile, the localized high internal stress from beta -> alpha s phase transformation provides the kinetic driving force for twinning. As a result, typical lens-shaped NTs with an average width of approximately 21 nm and a volume fraction of 7.4% are successfully activated within the alpha s phase in the 7.5Mo alloy. Benefiting from the higher proportion and the nanoscale, the alloy exhibits an ultrahigh tensile strength of 1358 MPa and a fracture toughness of 84 MPa m1/2 , realizing an excellent strength-toughness synergy. This study provides a new strategy for the development of highperformance as-cast Ti alloys through NTs-induced simultaneous strengthening and toughening. (c) 2026 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.

This research tackles motion inaccuracies in multiaxis maglev planar motor (MPM) systems, crucial for precision applications such as semiconductor lithography, which suffer from position-dependent disturbances and multiaxis coupling. The objective is to develop a model-data fusion disturbance suppression framework. Our methodology integrates a static decoupling model, derived from electromagnetic and mechanical analysis, to enable independent control of four motion degree of freedom (DOF) x, y, z, Rx . A multi-DOF feedforward compensation using a harmonic disturbance model addresses identified low-frequency, periodic disturbances by exploiting their spatial position dependency, overcoming limitations of conventional observers. Finally, a radial basis function neural network (RBFNN) approximates and mitigates residual nonlinear disturbances. Key findings demonstrate the framework's efficacy: the decoupling model reduces multiaxis crosstalk, and harmonic feedforward attenuates periodic disturbances. The RBFNN-based residual compensation significantly enhances tracking accuracy and has been experimentally verified under different motion conditions. This work contributes a high-performance disturbance suppression solution for precision mechatronic systems.

A robust model predictive current control (MPCC) strategy is proposed for motor drive systems, in which a cascaded architecture is innovatively constructed by integrating a noise-resilient augmented observer (NAO) with an adaptive data-driven iterative harmonic identification (ADIHI) mechanism. First, to address dominant aperiodic disturbances in the ultralocal motor model, an enhanced NAO is developed, where the integral of noisy measured current is deliberately introduced as an augmented state variable. This novel augmented state effectively decouples the adverse interaction between high observer gains and high-frequency current measurement noise, enabling inherent low-pass filtering properties of the integrator operator and significantly improving noise immunity without sacrificing the disturbance estimation accuracy. Second, based on the NAO-estimated disturbances and ultralocal model, a high-pass-filtered harmonic internal model component is extracted and further refined through the proposed ADIHI scheme. By incorporating an adaptive forgetting factor and an iterative identification mechanism, ADIHI achieves accurate online harmonics extraction. Moreover, an adaptive forgetting factor updating strategy driven by the variation rate of harmonic identification error is designed to enhance robustness against operating condition variations. Finally, the overall closed-loop system stability of the proposed MPCC framework is rigorously established using the Nyquist stability criterion. Explicit analytical expressions for control parameters are derived under stability constraints, and systematic stability regions and parameters tuning guidelines are provided. Extensive experimental results on a motor test bench demonstrate the effectiveness and superiority of the proposed current control strategy.

For the winding-segmented permanent magnet linear synchronous motor (WS-PMLSM) driven by a distributed controller, current control is challenged by high sampling noise and significant back electromotive force (EMF) disturbances. To address this, a robust deadbeat predictive current controller (DPCC) based on double extended state observers (ESOs) is proposed. This controller enhances both disturbance and noise suppression performance in the current closed-loop system while maintaining deadbeat tracking for the current reference. For the dq-axis multiple-input multiple-output (MIMO) current closedloop system, frequency-domain shaping of the maximum singular value of the transfer function matrix is employed to design the controller structure and select control parameters. An universal dynamic model of the MIMO observer is derived, simplifying the frequency response analysis of the MIMO current closedloop system. The correctness of the analytical method and the superiority of the proposed approach are validated through frequency sweep and time-domain response experiments conducted on a WS-PMLSM prototype.

Short-circuit phase winding fault is a common type of fault in electrical driving systems, which brings great threat to the safety to the whole system. In this paper, a control strategy is proposed to reduce the torque ripples caused by the short-circuit fault. The torque ripples consist of two portions, namely the torque ripples caused by the phase missing, the other is caused by short-circuit current itself. The strategy is composed of two steps. The first step is to get access to the accurate short-circuit current by the method of calibration. The next step adjusts the amplitude and phase of each phase current first to reduce the first portion of torque ripples, then the corresponding compensation current is calculated by the principle of maintaining the Q-axis and D-axis current and injected into each phase winding to eliminate the second portion of torque ripples. Finally, a simulation-model is established and verifies the effectiveness of the proposed control strategy.

This article presents a hybrid thermal modeling approach combining Computational Fluid Dynamics (CFD) and Lumped Parameter Thermal Network (LPTN) for the thermal analysis of in-slot evaporative cooling systems. Firstly, a Volume of Fluid (VOF) based numerical model is established to characterize the boiling heat transfer under various slot geometry parameters. Subsequently, a heat transfer correlation is derived to decouple the effects of heat flux and geometry parameters, which is then integrated into the LPTN model. The comparative results demonstrate that the proposed hybrid model achieves high-fidelity thermal prediction with significantly reduced computational cost. Furthermore, the parametric analysis identifies an optimal channel design that effectively balances the trade-off between convective heat transfer area and volumetric heat generation.

Conventional motor drives are subjected to extensive disturbances and uncertainties across entire frequency spectrum, which significantly deteriorate current control performance within electric propulsion system. To address this issue, this paper proposes a discrete-time composite control strategy that integrates an improved equivalent-input-disturbance (IEID) approach with a dynamic decoupled adaptive damping (DDAD) regulator, aiming to suppress external disturbances and improve the transient current response. Specifically, a proportional-integral augmented observer (PIAO) is introduced into the IEID framework, where the integral of the measured current is treated as an augmented variable. This modification enhances both the estimation accuracy of internal states and the system’s resilience to the current measurement noise. Furthermore, a modified causal filter, constructed building upon an integral-resonant internal model structure, is incorporated into the IEID estimator to achieve simultaneous and effective attenuation of both disturbances and harmonics. Finally, an improved adaptive damping function that is adjustably updated with load current as well as motor speed and the associated dynamic decoupled control law are systematically designed using poles placement techniques, enabling the superior transient dynamics and the flexible damping characteristics. Comparative experimental results validate the practical applicability of the proposed control method.

The voltage source inverters (VSI) are widely used in motor drivers. As one of the most primary components in the VSI, the DC-link capacitor is vitally important in terms of reliability. Reducing the capacitor current is widely considered an effective method to improve its reliability. For this purpose, the existing pulse width modulation (PWM) technique is improved by introducing the individual switching frequency for each phase. A hybrid frequency PWM method is proposed in this study, taking account of the impedance characteristics of the DC-side circuit in two-level VSI. Simulation results show that, in scenarios using small-capacitance capacitors or low-impedance bus cables, the proposed method can achieve a smaller capacitor current at the same equivalent switching frequency.

The transformation-induced plasticity (TRIP) effect has been widely introduced into advanced metal structural materials to assist dislocation slip in carrying plastic deformation. In this work, the deformation responses of stress-induced alpha ''-martensite (SIM) under different yield strengths and early plastic behaviors were investigated for TRIP titanium alloys. Accordingly, the comprehensive theoretical calculations focusing on phase stability and modulus mismatch were employed for screening TRIP-dominated target composition. The designed Ti-0.56Al8.04Mo-2.18Cr (wt.%) alloy achieved a synergistic enhancement of yield strength-ductility after simple thermomechanical processing. Our results clarified the conventional understanding for deformation behaviors of SIM at the early plastic stage. Concurrently, the mechanism underlying the retention of > 0.52 ductility at approaching 700 MPa yield strength for TRIP-dominated titanium alloys has been systematically elucidated. Moreover, three SIM-SIM interaction modes, that is, shear displacement, SIM splitting, and SIM blocking, and detwinning phenomena in alpha ''-martensite during unloading were also captured.

This paper primarily derives and verifies the mathematical model of an interior fault-tolerant permanent magnet synchronous motor, which is commonly equipped with fractional-slot concentrated windings. The results show that the torque equation can be decomposed into three components. The first two components have been previously identified: one corresponds to the negative-sequence current, and the other arises from the interaction between the third harmonic of the permanent magnet flux and the third harmonic of the spatial current. The third component results from the interaction between the fields generated by currents in different subspaces. Notably, this third component is revealed and verified for the first time in this paper. Besides, an analysis is conducted to clarify the application scope of the motor model, and a brief guide is provided on how to use this model to enhance fault-tolerant control algorithms. However, the previously established mathematical model does not account for this third torque component. To address this gap, a series of simulations and experiments are conducted in this paper to validate the proposed analysis.

The n-coil (n+1)-leg inverter serves as a key hardware solution for independent-coil-based permanent magnet linear synchronous motors (ICPMLSM) due to its simple circuit structure. However, the demand for independent drive of each coil under asymmetric phase quantities makes most conventional modulation strategies inapplicable. Meanwhile, the research on the modulation strategy for output current harmonic suppression based on this inverter is still lacking. This paper proposes a carrier-based modulation strategy for the n-coil (n+1)-leg inverter. By zero-sequence voltage injection to all legs, each coil is decoupled from the auxiliary leg, enabling independent drive. Instead of treating zero-sequence voltage injection as a waveform-shaping technique, it is reformulated as a system-level harmonic minimization problem. A harmonic metric is derived and the optimal zero-sequence voltage is obtained by minimizing the aggregated harmonic content of all energized coils, applicable to arbitrary quantity of energized coils. The DC-link utilization under different quantities of energized coils is analyzed, revealing an inherent trade-off between harmonic suppression and linear modulation range. Furthermore, robustness of the proposed method is also analyzed. Finally, the effectiveness of the proposed method is verified by detailed experiments under different quantities of energized coils.

Classical current control strategies in electric propulsion systems often suffer from degraded performance under periodic and aperiodic disturbances. To overcome these limitations, this paper proposes a novel current control framework that combines an adaptive fractional-order resonant controller (AFRC) with a fixed-time augmented extended state observer (FxTAESO), aiming to enhance disturbance rejection and dynamic robustness. Firstly, the proposed AFRC introduces a self-tuning fractional-order operator, which adaptively adjusts in real-time according to load current, harmonic rejection strength, and desired phase margin. This adaptive mechanism enables precise harmonic compensation while ensuring stability and robustness across the varying operating conditions. Subsequently, the FxTAESO incorporates a current integral term as system augmented variable to decouple the coupling effect between current measurement noise and high observer gains. Additionally, by embedding an improved nonlinear fixed-time convergence law, the observer ensures that the estimation error converges to a bounded neighborhood of the equilibrium point within a predetermined time, independent of initial conditions. Finally, experimental validation on a PMSM drive platform demonstrates that the proposed FxTAESO-AFRC scheme achieves superior steady-state accuracy, faster transient response, and stronger disturbance suppression compared to conventional methods.

Interleaved auxiliary-commutated resonant-pole (ACRP) inverters are used for high-precision DC–AC conversion. However, direct application of steady-state carrier phases at start up may give different units unequal first conduction intervals, causing start-up inrush current. This article analyzes the start-up inrush mechanism and proposes a soft start-up strategy based on carrier phase control. First, the relationship between the first conduction interval and the switch current peak is derived to clarify the origin of the start-up inrush current. Then, the passive current sharing after start-up is described using switching-cycle averaging, and the synchronization interval before carrier phase restoration is determined. In the proposed strategy, the corresponding carriers of the interleaved modules are first aligned so that all units start with the same first conduction interval. The carrier phases are then restored to their steady-state interleaved positions under the switch current limit. Experiments on a 300 V, 250 kHz prototype show that the peak switch current is reduced from approximately 20 A under direct start-up to the 10 A steady state envelope. The complete soft start-up process is finished within 0.2 ms. The measured passive current-sharing time constant agrees with the calculated value within 2.38%, and tests under resistive and resistive–inductive (R–L) loads verify the effectiveness of the proposed strategy.

The inversion of multiple magnetic dipoles plays a critical role in applications such as geological exploration and spacecraft magnetic modeling. The primary challenges include an unknown number of magnetic sources, high sensitivity to noise, and low inversion accuracy. In this article, we propose a novel 3-D inversion method for multiple magnetic dipole models that integrates deep-learning-based prior analysis with a penalty function optimization strategy. A lightweight convolutional attention network, termed magnetic-gradient-tensor-invariant net (MGTI-Net), is developed to extract prior information from the invariants of the magnetic gradient tensor, thereby enabling accurate identification of the dipole count and providing preliminary estimates of their positions. By incorporating a penalty function into an improved least squares estimation framework, the proposed method robustly inverts the spatial positions and magnetic moments of the dipoles. Simulation results demonstrate that MGTI-Net can reliably determine the number of dipoles in a 3-D space and maintain a classification accuracy above 75% even under 50% relative random noise interference. Moreover, the improved least squares estimation can constrain the position and magnetic moment errors within 0.01 m and 0.1 A & centerdot; m(2), respectively, under 15% relative noise, reducing the error by more than one order of magnitude compared with conventional least squares methods. Experimental findings corroborate the simulation analysis, confirming that the new approach can accurately recover magnetic source parameters.

Magnetic target inversion technology has significant applications in biomedicine, unexploded ordnance detection, and vehicle tracking. However, traditional inversion algorithms suffer from inaccurate areas, limiting the inversion accuracy. This article establishes a global error model that simultaneously accounts for the effects of the magnetic target’s position and posture, revealing the distribution of inaccurate areas. Error analysis demonstrates that the inaccurate areas differ across various inversion algorithms. By switching between these inversion algorithms, we propose an improved inversion algorithm. Simulation results show that the improved inversion algorithm reduces the size of the inaccurate area to 0.20%. Experimental results in a magnetic shielding room (MSR) indicate that the new inversion algorithm improves positioning accuracy by more than 59%. This improvement allows magnetic target inversion technology to determine the position and posture of the magnetic target with greater accuracy, significantly boosting its effectiveness and reliability across various applications.

To achieve net-zero carbon emissions, electrified and hybrid propulsion systems in air-transport increasingly demand high torque density motors. High torque density is invariably accompanied by high loss density, where winding copper losses typically constitute the primary source of total motor losses. This directly increases the risk that the winding temperature will exceed the threshold, leading to dielectric failure of the insulation. Thus, enhancing winding heat dissipation becomes a core approach to breaking through the power density improvement bottleneck. Additive manufacturing (AM) enables innovative winding designs. This article compares three AM windings with integrated cooling channels, which enhances heat dissipation by increasing the winding cooling area and optimizing coolant flow paths. A computational fluid dynamics (CFD) model is established to compare the temperature distribution of three winding structures, as well as the flow characteristics and pressure drop of the coolant under different structures. The best-performing O-type AM winding exhibits a steady-state average temperature rise of only 34.38 C-degrees at a current density of 33.5 A/mm(2). Finally, the prototype windings are manufactured and tested to verify the feasibility of the concept, and satisfactory results are achieved.

The DC-link capacitor is one of the most crucial component in motor drive systems. The reliability of capacitors has drawn an increase of attention due to the complex application environment and the compression of their volume for higher power density. For the purpose of health condition monitoring, the online capacitance identification for DC-link capacitors is examined in this paper. A revised identification model that incorporates DC-link inductance is developed using weighted least-squares, taking account of the non-linearly changing source current. To address the error caused by measurement noise, an identification algorithm based on gradient-descent restricted total least-squares is proposed. Through comprehensive improvements to the model and algorithm, relatively stable and accurate capacitance identification under different operating conditions is achieved. Experiments are conducted to verify the efficiency of the proposed method.

To achieve the magnetic cleanliness of spacecraft, it is necessary to precisely model the magnetic characteristics of the spacecraft using on-ground magnetic measurement data collected by magnetic sensors. The accuracy of the modeling largely depends on the accurate position and orientation information of magnetic sensors. Therefore, this paper presents a novel localization and orientation method for sensors based on a magnetic beacon to obtain accurate sensor position and orientation. Firstly, the magnetic field generated by the magnetic beacon is characterized by spherical harmonic functions. Therefore, the method proposed in this paper is not limited to dipolelike magnetic beacons. Subsequently, the magnetic beacon was placed on a non-magnetic turntable and rotated through one full circle. The generated magnetic field was measured by sensors whose position and orientation needed to be determined. The deviation between the Fourier coefficients calculated based on the spherical harmonic model and the that obtained based on the test data is used as the objective, and the Particle Swarm Optimization (PSO) algorithm is adopted to calculate the position and orientation. Through simulation and experimental measurement, the accuracy of the algorithm, the localization and orientation ability at short distances, the uniqueness of the solution, and the anti-noise ability were verified, which shows that under the condition of 1 nT Gaussian noise, the standard deviations of the position and orientation obtained from multiple repeated calculations are 1.502 mm and 0.22 degrees, respectively.

The independent-coil-based permanent magnet linear synchronous motor (ICPMLSM) has great flexibility due to the minimum unit control, and it plays an important role in advancing industrial automation. However, research on its modeling and current control is still limited. This article presents a comprehensive study on both aspects. First, general linear models of inductance and back electromotive force (EMF) are established under different coupling conditions between the mover and the coils. Based on the principle of constant electromagnetic thrust, a current distribution strategy is developed, and a minimum-distance current switching strategy is further derived through the calculation of current zero-crossing points. Considering parameter variations under different coupling states, a model-free predictive current control (MFPCC) strategy is adopted to ensure robust current regulation. Furthermore, a model-free adaptive feedforward (AFF) controller is integrated into the MFPCC, forming an adaptive MFPCC (AMFPCC). This enhanced control scheme enables real-time compensation of both back EMF and resistive voltage through online parameter adaptation. Finally, the proposed control strategies are experimentally validated. The results confirm the effectiveness of the current distribution and switching methods and demonstrate that the AMFPCC achieves near-zero steady-state current error while exhibiting strong robustness.

Taking the drive motor of a hydrogen-oxygen electric pump as a representative example of short-duration ultra-high power density machines, this study investigates lightweight thermal management techniques under extreme power density operating conditions. An evaluation method for the limiting output power is first proposed to determine the theoretical maximum output power of the motor under given constraints. However, the copper loss associated with this limiting operating point exceeds the allowable level of the machine. To address this issue, a novel cooling configuration is introduced, in which cryogenic channels are embedded in the stator slots and supplied with a low-temperature coolant. The proposed structure operates in two modes: immersion cooling and flow cooling. In the former, the vaporization latent heat of a quiescent coolant is utilized to remove heat, while in the latter, forced coolant flow enhances convective heat transfer. To clarify the underlying mechanisms, an energized solenoid is initially adopted as a simplified test object to investigate and compare the heat transfer performance of the two cooling modes, and immersion cooling is further validated experimentally. Subsequently, an 80 kW prototype motor is used as a test platform to conduct both cryogenic flow and immersion cooling experiments, thereby demonstrating the feasibility and effectiveness of the proposed lightweight thermal management approach.