Accurate and rapid prediction of temperature distribution in electrical machine windings is essential for thermal management. This article proposes the asymptotic homogenization method (AHM) as a numerical approach to estimate the equivalent thermal conductivity (ETC) of windings. A dual-scale coordinate system is adopted to analyze conductor-insulator composite, with the heat transfer problem separated into coupled macroscopic homogeneous and microscopic periodic perturbation fields. The global ETC of the winding is subsequently derived from the representative unit cell of a single wire. Crucially, the ETC is computed from the distribution and characteristic scales of physical parameters, so it is applicable to wires with arbitrary cross sections and filling arrangements. Numerical simulations validate the accuracy of the method against randomly distributed winding models. Experiments on the prototype further confirm that the temperature distribution can be precisely predicted by the developed homogenized model, while computational efficiency is significantly improved.

This paper proposes a multi-objective optimization method based on electromagnetic-structural coupling for permanent magnet synchronous motor. The proposed method is aimed at simultaneously meeting the electromagnetic and structural performance requirements of aerospace motors. An analytical model is established for the strength and stiffness of each component in a permanent magnet synchronous motor. The analytical model is combined with the electromagnetic finite element model. A multi-objective genetic algorithm is used for the coupled electromagnetic-structural optimization. This method ensures high torque density, high efficiency, and high mechanical reliability. The optimized motor can withstand three times the mechanical overload, achieving 94.5% efficiency and a torque density of 8.2 N & centerdot;m/kg. Finally, a prototype is manufactured and experiments are conducted to validate both the theoretical analysis and the proposed optimization method.

In this article, a harmonic-oriented slotted rotor is proposed to significantly reduce vibration without sacrificing the torque performance in the fractional-slot concentrated-winding (FSCW) interior permanent magnet synchronous machines (IPMSMs). First, the generation mechanism of nonswitching high frequency band vibration is revealed. Unlike conventional theory, nonswitching high frequency band vibration dominates instead of the low frequency band vibration in the 10-slot/8-pole FSCW IPMSMs. Second, a harmonic-oriented slotted rotor is designed by constructing the compensation function. The required air-gap permeance phase angle is determined based on the permanent magnet flux density distribution. In this way, the specific permanent magnet flux density harmonics can be directly reduced. Finally, the FSCW IPMSM with harmonic-oriented slotted rotor is manufactured and tested. The experimental results verify the effectiveness of the proposed method.

When an open-circuit fault occurs in a dual three-phase permanent magnet synchronous motor (DTP-PMSM), the system is subject to both current and voltage constraints. Analysis of these voltage constraints reveals that voltage residuals that have been previously overlooked significantly contribute to torque ripple. This article proposes a dual-plane voltage compensation strategy. The harmonic-plane compensation is used to eliminate the dominant voltage residual, while the fundamental-plane compensation further eliminates the residual-induced voltage disturbance on the fundamental-plane control. The proposed method suppresses torque ripple under fault conditions and further reduces it during fault-tolerant operation. Experimental results validate their effectiveness.

This paper investigates the impact of sleeve segmentation on eddy-current loss in permanent-magnet (PM) machines with fractional-slot concentrated-windings (FSCW) under different stator MMF harmonics. The concept of equivalent sleeve segmentation is introduced. The eddy-current path induced by the v-order armature reaction magnetic field harmonic in the sleeve is divided into v spatial segments. First, the effect factors of EC losses of FSCW-PM machines, including stator magneto-motive force (MMF) harmonics, armature reaction magnetic field, and EC density, are analyzed in detail. Then, a 12s10p and a 24s22p PM machines are design optimal and their performances are calculated by the finite-element method. The results show that the equivalent segmentation of harmonics significantly affects eddy-current losses. Finally, some experiments on the prototype of the 12s10p FSCW-PM machine are carried out for validation.

To address the limited capability of conventional hydro-pneumatic suspensions in coordinated damping–stiffness regulation, this paper proposes a new semi-active hydro-pneumatic suspension (SAHPS) system based on a dual-valve shock absorber. A damping valve architecture composed of a spring check valve–solenoid proportional valve–spring check valve is arranged between the rod and rodless chambers of the hydraulic cylinder, enabling coordinated adjustment of suspension damping and equivalent stiffness. Furthermore, a genetic algorithm optimization with model predictive control (GA-MPC) is designed to enhance the overall dynamic performance of the suspension while effectively reducing the operating frequency of the solenoid proportional valve. Finally, AMESim–Simulink co-simulations and hardware-in-the-loop (HIL) experiments are conducted under bumpy road excitation and Class C random road conditions. Under Class C random road conditions, compared with passive hydro-pneumatic suspension and semi-active suspension with conventional MPC, the proposed method achieves maximum reductions of 11%, 25%, and 12.9% in the root mean square values of body acceleration, suspension working space, and dynamic tire load, respectively. The discrepancies between experimental and simulation results remain below 7%, confirming the effectiveness of the proposed system and control strategy. This study provides a new technical guidance for low-frequency vibration suppression in vehicle suspension systems.

This paper proposes a hybrid model combining equivalent magnetic network and analytical method for calculating high-frequency eddy current losses in windings. Firstly, the equivalent magnetic network model is developed for a permanent magnet machine, enabling the determination of the magnetic flux density distribution within the stator slots. The magnetic flux density at the center coordinates of each winding conductor is then obtained based on their specific positions. This data is subsequently applied to a 2D high-frequency eddy current loss analytical model to compute the windings eddy current losses. The proposed hybrid model improves computational efficiency while maintaining accuracy compared to the finite element method. Finally, the effectiveness of the proposed model is validated on a 10-slot/8-pole surface-mounted permanent magnet machine. Finite element method and experimental results of the machine have verified the proposed hybrid model.

Traditional open-switch fault diagnosis methods largely rely on real-world fault data for model training, leading to high experimental data acquisition and limited fault coverage. To address this limitation, this paper proposes a domain consistent framework for accurate and robust open-switch fault diagnosis in dual three-phase permanent magnet synchronous motor drives. The method analyses the spatial characteristics of six-phase currents with three orthogonal current trajectories under different fault cases. A data unification processing algorithm is developed to correct amplitude and waveform discrepancies between simulated and experimental trajectories, ensuring domain consistent. This consistency enables the diagnostic model to be trained entirely using simulated data while maintaining its applicability in actual experiments. To exploit fault features, a hybrid model is designed for robust classification. The proposed approach can theoretically identify 78 types of open-switch fault scenarios. Experimental validation demonstrates the superior performance of the proposed method.

Five-phase permanent magnet synchronous motors (PMSMs) with loop-winding topology exhibit good fault-tolerant capability under an open-leg fault condition. However, unbalanced leg currents increase the risk of subsequent inverter failures. This paper proposes an open-leg fault-tolerant control strategy for loop-winding five-phase PMSMs, aiming to optimize leg currents and achieve symmetric inverter operation. First, the phase currents are directly reconstructed in the original coordinate system to address the asymmetric winding connection after an open-leg fault, facilitating the establishment of the relationship between magnetomotive force and leg currents. Then, the optimized phase and leg currents are proposed using a geometric approach under symmetric leg-current constraints. To extend the applicability of the proposed method, a unified fault-tolerant switching table is designed for addressing arbitrary single-leg open-circuit faults. Finally, the influence of the third-order back-EMF on the torque and leg currents is analyzed and compensated, extending the applicability to non-sinusoidal five-phase PMSMs. Compared with the existing method, the proposed method can effectively reduce the maximum leg currents and indirectly enhance the output torque capacity. Experimental results demonstrate the effectiveness and feasibility of the proposed method.

A new vibration suppression method for a fractional-slot distributed winding permanent magnet synchronous machine (FSDW-PMSM) is proposed by considering the influence of the radial force modulation effect on FSDW-PMSMs. First, the vibration source of the FSDW-PMSMs is analyzed, and the principle of radial force modulation is revealed. Afterwards, the radial force distribution characteristics are studied, and the radial force component that contributes to the dominant vibration is identified. The PM flux density harmonics in the air gap are suppressed using the harmonic injection method to reduce vibrations. Additionally, dual three-phase techniques are used to enhance the fundamental armature flux density, thereby improving torque capability. Consequently, the vibration performance of the FSDW-PMSM is improved without sacrificing the torque. Finally, the proposed method is validated through simulations and experiments.

Open-phase fault and current sensor fault are common in multiphase permanent magnet synchronous motor (PMSM) systems. However, the characteristics of the two fault types are too similar to be distinguished, resulting in misdiagnosis and thereby misleading implementation of fault-tolerant control. In this article, a locate-then-identify method is proposed to diagnose both open-phase fault and current sensor fault in the dual three-phase PMSM (DTP-PMSM) system. First, each phase current is decomposed by vector space decomposition transformation into fundamental, harmonic, and zero-sequence components. The ratio of these components enables fault location through the common characteristics of open-phase fault and current sensor fault. Subsequently, the asymmetric high-frequency voltage is injected into the DTP-PMSM system according to the fault location. Then, the fault type is identified based on the distinct responses to asymmetric high-frequency excitation under open-phase and current sensor faults. The proposed locate-then-identify method not only reduces the impact of real-time high-frequency injection on system control performance but also eliminates the need for additional voltage sensors. Finally, the effectiveness of the proposed fault diagnosis method is verified by experiments.

The incipient broken rotor bar (BRB) fault detection in the induction motor remains a significant challenge because the fault-related signature components are extremely weak and are masked by the main frequency component in the motor stator current signal. This paper proposes a novel and low-cost dual-signature fault detection framework that uniquely integrates the envelope modulation, spectral shifting, and rotor slip confirmation, enabling decisive identification of incipient BRB faults. First, principal component inspired projection (PCIP) is applied to a three-phase stator current signal, utilizing an enhanced projection-based envelope method to effectively isolate low-frequency amplitude modulation. The projected analytical signal is then used to form a fault-sensitive envelope spectrum. For improved visibility, the fault-related frequency components are shifted towards the supply frequency, generating detectable sidebands around it. Secondly, the rotor mechanical frequency is extracted simultaneously from the same envelope signal to estimate the slip. This estimation provides an independent physical confirmation of the detected fault while effectively minimizing false alarms. The proposed framework is validated using experimental datasets for various fault severities, multiple load torques, and two different supply frequencies. The results show that this not only reliably detects incipient BRB signatures but also offers a slip-based validation. This method is scalable, non-intrusive, and computationally efficient, making it highly suitable for motor condition monitoring.

This paper investigates power factor analysis and optimization control of the DC-biased hybrid excitation vernier machine. The machine has two hybrid excitation sources, viz. permanent magnet and zero-sequence current in virtual field winding. Different from conventional power factor optimization control derived in dq-axis without considering 0-axis, this paper aims to improve the power factor by fully utilizing additional control flexibility of zero-sequence current. An analytical model of the DCB-HEVM is established in the synchronous rotating reference frame, which captures the torque production and power characteristics. Based on this model, the influence of the three-dimensional dq0-axis current components on power factor is investigated, thereby clarifying the inherent coupling between torque generation and power factor regulation. Then, a power factor optimization control strategy based on coordinated dq0-axis current distribution is proposed. Experimental results show that with the proposed control strategy, the power factor can be effectively improved.

Fractional-slot concentrated-winding (FSCW) permanent magnet (PM) synchronous machines (PMSMs) exhibit numerous low-spatial-order radial force waves (RFWs), which are a dominant source of vibration and noise. This article investigates the influence of slotting structures on flux density harmonics, RFWs, and vibration and proposes a new vibration suppression method tailored for FSCW-PMSMs. First, analytical and numerical studies reveal that the closed-slot structure can effectively mitigate the non-integer-pole-pair vibrations induced by slotting effects, but it increases flux leakage, leading to torque loss. To address the torque deficiency of the closed-slot structure design, an anisotropic wedge-based vibration suppression method was proposed to achieve simultaneous torque retention and vibration attenuation. Next, the effectiveness of the proposed method for the FSCW-PMSMs with different pole-slot combinations is validated via finite element analysis (FEA) on two groups of FSCW-PMSMs, where each group comprises three machines-employing open slot, anisotropic wedge, and closed slot, respectively-while maintaining identical geometries. Finally, experimental verification using three prototyped machines confirms that the proposed method can significantly reduce the vibration acceleration without compromising electromagnetic torque for FSCW-PMSMs.

Random switching frequency space vector pulsewidth modulation (RSF-SVPWM) strategy mitigates high-frequency harmonics and vibrations by randomly varying the switching frequency across a specified frequency range. However, its effectiveness in suppressing high-frequency harmonics and vibrations is constrained. This article introduces an enhanced RSF-SVPWM strategy through improving random number properties. Specifically, the Beta distribution and random number constraints are employed in a cascaded manner. The Beta distribution improves the probability density of the random numbers, whereas the random number constraint reduces the average relative changes between adjacent switching frequencies, leading to more effective suppression of high-frequency harmonics and vibrations. Moreover, the torque ripple and current distortion are not adversely affected by the frequency randomization in RSF-SVPWM. Experimental results validate the effectiveness of the proposed method.

Early detection of broken rotor bar (BRB) faults in induction motors is essential to prevent secondary failures and production losses. Conventional motor current signature analysis (MCSA) methods suffer from spectral leakage, especially under low supply frequency and light-load conditions, where fault-related harmonics overlap with supply harmonics. A robust diagnostic framework that combines orthogonal-axis rectification with the Goertzel algorithm for reliable BRB fault detection under low-load and low supply frequency scenarios is proposed. The Hilbert transform is employed to construct quadrature components, enabling the fundamental frequency to be shifted into a fourth harmonic instead of the second, thereby improving spectral separation of the fault characteristic frequency. The Goertzel algorithm is then applied to extract fault components with high spectral resolution and low computational cost. Simulation and laboratory experiments, conducted on motors with varying fault severities and operating conditions, demonstrate that the proposed method effectively suppresses harmonic interference, enhances weak fault signature visibility. Moreover, the proposed method achieves reliable diagnosis even under no-load and low-frequency operation.

This article aims to investigate the influence of overlapped and separated winding configurations on permanent-magnet (PM) demagnetization under three-phase short-circuit condition. First, the topological differences between various winding configurations and the characteristics of PM demagnetization curves are analyzed in detail. Second, the relationship between inductance and magneto-motive force (MMF) harmonics is revealed based on winding function theory. Then, a three-phase short-circuit fault model is developed to deduce the influence factors of d-axis current. Besides, the demagnetization MMF is derived to reflect the PM demagnetization characteristics. Third, the inductance, the d-axis current under three-phase short-circuit condition, PM demagnetization distribution, as well as pre- and post-demagnetization performance are compared elaborately through finite-element method. The result indicates that the overlapped winding configurations exhibit a superior anti-demagnetization capability current compared to the separated ones. Finally, a 48-slot/8-pole PM machine with separated winding configuration is manufactured. The corresponding experiments are carried out for validation.

The standard inverter topology of five-phase permanent magnet synchronous motor (PMSM) has weaker fault-tolerant capability than other complex drives. Additionally, traditional open-switch fault-tolerant strategies demand precise diagnosis methods involving numerous states of different phases and reconfiguration according to fault phase change. To enhance fault-tolerant algorithm applicability, a universal fault-tolerant space vector pulsewidth modulation (SVPWM) strategy without extra hardware is proposed to handle single open-switch fault for five-phase PMSM. The most significant innovation is to achieving fault-tolerant operation for arbitrary phase open-switch fault without requiring adjustments based on fault phase location. Owing to this, corresponding diagnosis process can be simplified. In diagnosis process, the positive and negative relationship of the third harmonic currents within faulty half cycle is adopted to obtain the overall diagnosis result without requiring precise identification. In fault-tolerant algorithm, postfault basic voltage vectors are first reconstructed based on switching state analysis. Then, to minimize the influence of harmonic subspace and improve SVPWM control precision, virtual voltage vectors are synthesized based on geometric meaning of basic voltage vectors. Furthermore, through establishing vector sets involving five phases and summarizing their intersection regions, universal virtual voltage vectors are determined. Finally, the effectiveness of proposed method is verified by experiments.

Domain adaptation approaches have been applied to motor rolling bearing fault detection. Nevertheless, these approaches are constrained by the assumption of label space consistency between source and target domains. In complex industrial application scenarios, it is more common that the target domain label space is a subset of the source domain label space. To address such partial domain adaptation problems, a multi-scale feature calibration partial transfer network is proposed in this paper. This method extracts discriminative features from fault signals through a multi-scale convolutional feature extraction network to improve the accuracy of transfer classification. A domain shift calibration module is designed to explicitly learn cross-domain differences, achieving fine-grained alignment at the feature level. Furthermore, a domain-class joint distribution alignment mechanism is developed. On one hand, this mechanism enhances the transferability of shared classes and suppresses the negative transfer of outlier classes through weighted class alignment. On the other hand, the feature-level and task-level joint distribution alignment mechanisms work synergistically to minimize cross-domain discrepancy. Experiments on three bearing datasets verify the effectiveness and superiority of the proposed method.

For dual three-phase permanent magnet synchronous motors (PMSMs), the accurate acquisition of phase current information is critical. Incorrect current information caused by sensor failure will degrade motor performance or lead to drive collapse. This work proposes a strategy that leverages multiple-branch current sampling to broaden current sampling paths. This redundancy permits the detection and localization of current sensor faults through combinational logic circuits. Moreover, the redundant current information supports effective remedial strategy against all four types of sensor faults. Even when faults occur repeatedly, the strategy maintains excellent remediation performance. In contrast to conventional observe/model-based methods, the proposed strategy eliminates the need for an accurate parameterized model. Its enhanced simplicity and reliability are well-suited for real-time motor drives with limited computational resources. Experimental results demonstrate the effectiveness of the proposed strategy under repeated sensor faults.