Search Results (1,269)

When the speed of an induction motor (IM) exceeds its rated value, voltage saturation occurs, which degrades its performance. Traditional flux-weakening (FW) control suffers from delays due to cascaded PI regulators and sensitivity to rotor field orientation lag. Addressing these two issues, the proposed ancillary flux-weakening (AFW) method introduces two d-axis current compensation paths. One compensation path is from the reference value of the q-axis current, which simplifies the traditional three-PI cascade FW path into a single PI path in the transient process. The other compensation path is derived from the q-axis current tracking error to mitigate voltage saturation caused by orientation error. Comparative experiments show that during precise direction acceleration, the AFW method increases the current response time by 35% and reduces the peak voltage fluctuation by 38.98%. It also reduces low voltage ripple by 76.4% in inaccurate direction and burst load conditions. The results confirm a significant enhancement of dynamic performance and voltage anti-saturation capability in the FW region. Full article

The transient performance of sensorless control for interior permanent magnet synchronous motors (IPMSMs), based on back-electromotive force (back-EMF) estimation, is a critical factor in ensuring the high reliability of motor drive systems. Although rotor speed and position can be accurately estimated under steady-state conditions, estimation errors tend to increase during transient states such as acceleration, deceleration, and load torque variations. The enhancement of transient stability is closely related to the overshoot in the estimated position and speed errors. In this paper, the maximum overshoot of the estimated position and speed errors during transient operation is analyzed. Furthermore, compensation strategies are proposed to reduce the magnitude of these overshoots. The effectiveness of the proposed sensorless control method is validated through comparative analysis with existing approaches. Full article

Duct fan motors must provide high torque within limited space to maintain airflow while requiring low vibration characteristics to minimize fluid resistance caused by fan oscillation. Axial Flux Permanent Magnet Motor (AFPM) offers higher torque performance than Radial Flux Permanent Magnet Motor (RFPM) due to their large radial and short axial dimensions. In particular, the coreless AFPM structure enables superior low-vibration performance. Conventional AFPM typically employs a core-type stator, which presents manufacturing difficulties. In core-type AFPM, applying a multi-stator configuration linearly increases winding takt time in proportion to the number of stators. Conversely, a Printed Circuit Board (PCB) stator AFPM significantly reduces stator production time, making it favorable for implementing multi-stator topologies. The use of multi-stator structures enables various topological configurations depending on (1) stator placement, (2) magnetization pattern of permanent magnets, and (3) rotor arrangement—each offering specific advantages. This study evaluates and analyzes the performance of different topologies based on efficient arrangements of magnets and stators, aiming to identify the optimal structure for duct fan applications. The validity of the proposed approach and design was verified through three-dimensional finite element analysis (FEA). Full article

Axial flux motors, characterized by compact axial dimensions and high torque density, are well-suited for space-constrained applications such as in-wheel drives and flying vehicles. However, conventional axial flux permanent magnet synchronous motors (AFPMSMs) face challenges such as high-temperature demagnetization, reduced efficiency at high speeds, and elevated manufacturing costs. Electrically excited synchronous motors (EESMs) offer a promising alternative, providing high-temperature reliability and superior high-speed capability while maintaining high torque density. In this paper, a novel composite-cooled axial flux electrically excited synchronous motor (AFEESM) is proposed. From an electromagnetic design perspective, the effects of key parameters such as shaft-to-outer-diameter ratio, inner-to-outer-diameter ratio, slot depth, and yoke thickness on output performance are systematically investigated, and a dedicated design procedure is established. Through multi-objective optimization, the motor’s torque output is increased by 19.6%. Comparative simulations are conducted to evaluate differences in torque density, efficiency, and cost between the proposed AFEESM, a conventional radial flux EESM, and an AFPMSM. To address the cooling requirements of double-sided windings on both the stator and rotor, a dual-channel composite cooling structure is developed, integrating internal–external double-loop water cooling for the stator and axial through-hole air cooling for the rotor, reducing the peak temperature by over 36%. Finally, a prototype is manufactured, and no-load characteristics and load efficiency validate the effectiveness of the electromagnetic design and the structural reliability of the motor. Full article

Line-Start Permanent Magnet Synchronous Motors (LSPMSMs) offer a hybrid solution that combines the high efficiency of permanent magnet motors with the self-starting capability of induction machines. This review examines their key performance characteristics, historical development, and design approaches. Advantages such as high efficiency, improved power factor, and operational stability are discussed alongside challenges like limited critical inertia and synchronization issues. Design enhancements through rotor topology optimization and cage resistance adjustment are also explored. Finally, market trends and economic considerations are evaluated, highlighting the strong potential of LSPMSMs in energy-efficient motor applications. Full article

Robust speed estimation in induction motors (IM) is essential for control systems (especially in sensorless drive applications) and condition monitoring. Traditional model-based techniques for inverter-fed IM provide a high accuracy but rely heavily on precise motor parameter identification, requiring multiple sensors to monitor the necessary variables. In contrast, model-independent methods that use rotor slot harmonics (RSH) in the stator current spectrum offer a better adaptability to various motor types and conditions. However, many of these techniques are dependent on full-band processing, which reduces noise immunity and increases computational cost. This paper introduces a novel subband signal processing approach for rotor speed estimation focused on RSH tracking under both steady and non-steady states. By limiting spectral analysis to relevant content, the method significantly reduces computational demand. The technique employs an advanced time-frequency analysis for high-resolution frequency identification, even in noisy settings. Simulations and experiments show that the proposed approach outperforms conventional RSH-based estimators, offering a robust and cost-effective solution for integrated speed monitoring in practical applications. Full article

Induction motors are the dominant choice in industrial applications due to their robustness, structural simplicity, and high reliability. However, extended operation under extreme conditions, such as high temperatures, overload, and contamination, accelerates the degradation of internal components and increases the likelihood of faults. These faults are challenging to detect, as they typically develop gradually without clear external indicators. To address this issue, the present study proposes a cost-effective fault diagnosis system utilizing low-cost MEMS acoustic sensors in conjunction with a lightweight multilayer neural network (MNN). The same MNN architecture is employed to systematically compare three types of input feature representations: raw time-domain waveforms, FFT-based statistical features, and PCA-compressed FFT features. A total of 5040 samples were used to train, validate, and test the model for classifying three conditions: normal, rotor fault, and bearing fault. The time-domain approach achieved 90.6% accuracy, misclassifying 102 samples. In comparison, FFT-based statistical features yielded 99.8% accuracy with only two misclassifications. The FFT + PCA method produced similar performance while reducing dimensionality, making it more suitable for resource-constrained environments. These results demonstrate that acoustic-based fault diagnosis provides a practical and economical solution for industrial applications. Full article

Interior permanent magnet (IPM) synchronous motors have gained widespread adoption in electric vehicles (EVs) owing to their durable rotor configurations, expansive operational speed range, and superior efficiency. Nonetheless, typical IPM motor designs frequently exhibit high torque ripple and constrained torque density. To address these issues, a torque enhancement method is introduced by applying both filleting and notching techniques to the stator core. These techniques help reshape the magnetic field directly at the stator, allowing for more precise control of torque production and torque ripple reduction while keeping the rotor structure unchanged. Design variables of the stator in a 12-slot/8-pole fractional-slot V-shaped IPM motor are optimized using a multi-objective genetic algorithm based on a sensitivity constraint for unidirectional operation. The electromagnetic performance of the motor is analyzed through 2D finite element simulations for both no-load and loaded scenarios. The proposed motor increases average torque by 2.45% and significantly reduces torque ripple by 47.73% compared to the conventional motor. These reflect a significant advancement in torque capability. Furthermore, the efficiency of the proposed motor reaches 93.8%. The findings suggest the potential of the proposed filleting and notching techniques for torque capability improvement in EV applications. Full article

In this paper, a lightweight permanent magnet in-wheel (LW-PMIW) motor is proposed. This research focuses on using a multi-modulation design to enhance the amplitude of the fundamental wave while suppressing high-order harmonics, thereby enabling the motor to achieve high output torque, a light weight, and a high efficiency. Firstly, a combined trade-off factor related to motor mass, losses, and torque is defined specifically to provide guidance for the design. Secondly, a dual-rotor structure is adopted, and a harmonic injection (HI) design is applied to the permanent magnets (PMs). By designing a targeted harmonic injection ratio coefficient, the non-working harmonics of the PM magnetomotive force (MMF) can be weakened. Then, two iron modulating blocks are introduced to asynchronously modulate the PM MMF, which can further enhance the fundamental amplitude and improve the distribution of the airgap magnetic field. Finally, to verify the effectiveness of the multi-modulation design, the electromagnetic performance of the motor is evaluated and analyzed. The analytical and simulation results show that the torque of the proposed motor can reach 35.4 Nm, which is an increase of 19.6% while the torque ripple remains unchanged compared with the initial motor. Meanwhile, the output power increased by 0.37 kW. Hence, the rationality and effectiveness of the motor design are verified. Full article

Large synchronous motors are typically used to drive various load equipment, such as reciprocating compressors. Due to the continuous oscillation of the load, the pulsating torque acting on the main shaft of the synchronous motor will continuously vary with the load changes. This leads to forced oscillations during the dynamic stable operation of the unit, subsequently causing severe problems such as overheating, noise, and failures. Moreover, the rotor length of large synchronous motors is generally greater than the rotor diameter, giving the rotor certain flexible characteristics. During a motor’s operation, it is necessary to cross the first-order critical speed, making resonance highly likely to occur. Therefore, the analysis of dynamic characteristics of large synchronous motors is particularly important. This study investigates the dynamic characteristics of a 7800 kW-18P large synchronous motor rotor system through comprehensive theoretical and experimental analyses. The research encompasses three key aspects: (1) modal analysis comparing fan-equipped and fan-free configurations, (2) harmonic response evaluation, and (3) critical speed determination under concentrated mass conditions. Experimental validation was performed via impact hammer testing, with measured natural frequencies showing a strong correlation with simulated results for the magnetic pole core assembly. The findings not only confirm the operational speed validity but also establish a reliable foundation for the subsequent structural optimization of high-power synchronous machines. Full article

This study proposes a novel computational method, employing the integral dynamics of multibody systems to simulate the transverse vibrations of the rotor in a cantilever-type centrifugal pump. This method was applied to the kinematic assembly of the rotor and its supports, with the latter modeled as springs possessing stiffness and damping properties equivalent to those of real bearings supporting the shaft in an actual design. To investigate transverse vibrations within the system, three key observation points were defined—at the locations of the left and right bearings, as well as at the rotor’s center of mass—to allow for a thorough dynamic analysis. Additionally, the influence of motor rotational speed and the impeller’s eccentricity on the transverse vibrations of the supports and the shaft was examined. The results have revealed that transverse vibrations significantly affect the system’s dynamics at lower rotational speeds, leading to the classification of the shaft as flexible. As the rotational speed increases, the system exhibits enhanced dynamic stability. Furthermore, it was found that for impellers with a diameter less than 300 mm, the unbalanced forces are negligible and can be disregarded in pump design. To reduce vibration levels, an elastic damping ring was selected and incorporated into the system. This novel method provides an effective tool for analyzing the transverse vibrations of centrifugal pump rotors and for optimizing vibration mitigation strategies. Full article

To eliminate the dependence of the induction motor (IM) flux-oriented control system on position sensors, IM sensorless control based on a full-order state observer is studied in this paper. First, according to the IM rotor flux linkage models of current and voltage, the speed of the full-order state observer for IM and the solution for the feedback matrix are designed. Then, to simplify the expression of the feedback matrix and improve the stability of the observer for high-speed operation, a novel solving method of the feedback matrix by left-shifting the poles of the observer is proposed, and the terms containing rotor speed are simplified. On this basis, a speed estimation method based on the current error and Lyapunov theory is proposed. For low-speed operation, the feedback matrix parameter design method is proposed based on the stability conditions of d–q axis current error model. Finally, the feasibility and effectiveness of the proposed full-order state observer are verified by simulation and experiment. Since the improved full-order state observer can provide accurate speed feedback and rotor flux position for flux-oriented vector control systems, the IM drive system exhibits good steady-state and dynamic performance. Full article

As a core component of both the ship propulsion system and mission-critical equipment, shipboard motors are undergoing a technological transition from traditional fault diagnosis to multi-physical-field collaborative modeling and integrated intelligent maintenance systems. This paper provides a systematic review of recent advances in shipboard motor fault monitoring, with a focus on key technical challenges under complex service environments, and offers several innovative insights and analyses in the following aspects. First, regarding the fault evolution under electromagnetic–thermal–mechanical coupling, this study summarizes the typical fault mechanisms, such as bearing electrical erosion, rotor eccentricity, permanent magnet demagnetization, and insulation aging, and analyzes their modeling approaches and multi-physics coupling evolution paths. Second, in response to the problem of multi-source signal fusion, the applicability and limitations of feature extraction methods—including current analysis, vibration demodulation, infrared thermography, and Dempster–Shafer (D-S) evidence theory—are evaluated, providing a basis for designing subsequent signal fusion strategies. With respect to intelligent diagnostic models, this paper compares model-driven and data-driven approaches in terms of their suitability for different scenarios, highlighting their complementarity and integration potential in the complex operating conditions of shipboard motors. Finally, considering practical deployment needs, the key aspects of monitoring platform implementation under shipborne edge computing environments are discussed. The study also identifies current research gaps and proposes future directions, such as digital twin-driven intelligent maintenance, fleet-level PHM collaborative management, and standardized health data transmission. In summary, this paper offers a comprehensive analysis in the areas of fault mechanism modeling, feature extraction method evaluation, and system deployment frameworks, aiming to provide a theoretical reference and engineering insights for the advancement of shipboard motor health management technologies. Full article

The integration of axial flux motors into canned motor pumps offers a promising approach to overcome the efficiency and size limitations of traditional designs, particularly in critical sectors like aerospace. However, the hydrodynamics in magnetic gap between the stator and rotor are poorly understood. This study investigates the effect of magnetic gap on performance and internal flow. Six magnetic gap schemes are developed, ranging from 0.2 to 1.2 mm. Numerical simulations are conducted, and simulation results showed good agreement with experimental data. The magnetic gap exhibits a non-linear effect on performance. The peak head coefficient occurs at a 0.4 mm gap and maximum efficiency at 1.0 mm. At a 0.2 mm gap, strong viscous shear forces increase disk friction loss and create high-vorticity flow. As the gap widens, flow transitions from viscosity-dominated to inertia-dominated, leading to a more ordered flow structure. The blade passing frequency is the dominant frequency. For a gap of 0.8 mm, the pressure fluctuation intensity is lowest. By analyzing performance, head coefficient, velocity, vorticity, entropy production, and pressure fluctuations, a gap of 0.8 mm is identified as the optimal design. This study provides critical guidance for optimizing the design of axial flux canned motor pumps. Full article

This paper introduces a speed-sensorless dual-field-oriented control (DFOC) strategy for induction motors (IMs). DFOC combines the advantages or rotor- and stator-field orientation to significantly reduce the parameter sensitivity of the control regarding the generation of the converter control variable. A simplified structure is also proposed, using only two regulators for the flux and speed control, eliminating the two current regulators. Related to sensorless control, the classical adaptation mechanism within an MRAS (model reference adaptive system) observer is replaced with artificial intelligence (AI)-based approaches. Specifically, artificial neural networks (ANNs) and recurrent neural networks (RNNs) are employed for rotor speed estimation. They offer significant advantages in managing complex and nonlinear systems, providing enhanced flexibility and adaptability compared to traditional MRAS methods. The effectiveness of the proposed sensorless control scheme is validated through both simulation and real-time implementation. The paper focuses on the ANN and RNN architectures, as deep learning models, in terms of the reliability and accuracy of rotor speed estimation under various operating conditions. Full article