Search Results (292)

The efficiency of electric motors is highly dependent on their operating temperature, with lower temperatures contributing to enhanced performance, reliability, and extended service life. This study presents a comprehensive review of state-of-the-art cooling technologies and evaluates their impact on the thermal behavior of a commercial motor–generator system in high-demand applications. A baseline model of a permanent magnet synchronous motor (PMSM) was developed using MotorCAD 2023${}^{\circledR }$ software, which was supported by reverse engineering techniques to accurately replicate the motor’s physical and thermal characteristics. Subsequently, multiple cooling strategies were simulated under consistent operating conditions to assess their effectiveness. These strategies include conventional axial water jackets as well as advanced oil-based methods such as shaft cooling and direct oil spray to the windings. The integration of these systems in hybrid configurations was also explored to maximize thermal efficiency. Simulation results reveal that hybrid cooling significantly reduces the temperature of critical components such as stator windings and permanent magnets. This reduction in thermal stress improves current efficiency, power output, and torque capacity, enabling reliable motor operation across a broader range of speeds and under sustained high-load conditions. The findings highlight the effectiveness of hybrid cooling systems in optimizing both thermal management and operational performance of electric machines. Full article

Background and Objective: Temperature management is key for reliable operation of permanent magnet synchronous motors (PMSMs). The lumped-parameter thermal network (LPTN) is fast and interpretable but struggles with nonlinear behavior under high power density. We propose OLTEM, a physics-informed deep model that combines LPTN with a thermal neural network (TNN) to improve prediction accuracy while keeping physical meaning. Methods: OLTEM embeds LPTN into a recurrent state-space formulation and learns three parameter sets: thermal conductance, inverse thermal capacitance, and power loss. Two additions are introduced: (i) a state-conditioned squeeze-and-excitation (SC-SE) attention that adapts feature weights using the current temperature state, and (ii) an enhanced power-loss sub-network that uses a deep MLP with SC-SE and non-negativity constraints. The model is trained and evaluated on the public Electric Motor Temperature dataset (Paderborn University/Kaggle). Performance is measured by mean squared error (MSE) and maximum absolute error across permanent-magnet, stator-yoke, stator-tooth, and stator-winding temperatures. Results: OLTEM tracks fast thermal transients and yields lower MSE than both the baseline TNN and a CNN–RNN model for all four components. On a held-out generalization set, MSE remains below 4.0 °C² and the maximum absolute error is about 4.3–8.2 °C. Ablation shows that removing either SC-SE or the enhanced power-loss module degrades accuracy, confirming their complementary roles. Conclusions: By combining physics with learned attention and loss modeling, OLTEM improves PMSM temperature prediction while preserving interpretability. This approach can support motor thermal design and control; future work will study transfer to other machines and further reduce short-term errors during abrupt operating changes. Full article

Inter-turn short-circuit (ITSC) faults in permanent magnet synchronous machines (PMSMs) present a significant reliability challenge in electric vehicle (EV) drivetrains, particularly under non-stationary operating conditions characterized by inverter-driven transients, variable loads, and magnetic saturation. Existing diagnostic approaches, including motor current signature analysis (MCSA) and wavelet-based methods, are primarily designed for steady-state conditions and rely on manual feature selection, limiting their applicability in real-time embedded systems. Furthermore, the lack of publicly available, high-fidelity datasets capturing the transient dynamics and nonlinear flux-linkage behaviors of PMSMs under fault conditions poses an additional barrier to developing data-driven diagnostic solutions. To address these challenges, this study introduces a simulation framework that generates a comprehensive dataset using finite element method (FEM) models, incorporating magnetic saturation effects and inverter-driven transients across diverse EV operating scenarios. Time-frequency features extracted via Discrete Wavelet Transform (DWT) from stator current signals are used to train a Transformer model for automated ITSC fault detection. The Transformer model, leveraging self-attention mechanisms, captures both local transient patterns and long-range dependencies within the time-frequency feature space. This architecture operates without sequential processing, in contrast to recurrent models such as LSTM or RNN models, enabling efficient inference with a relatively low parameter count, which is advantageous for embedded applications. The proposed model achieves 97% validation accuracy on simulated data, demonstrating its potential for real-time PMSM fault detection. Additionally, the provided dataset and methodology contribute to the facilitation of reproducible research in ITSC diagnostics under realistic EV operating conditions. Full article

This study presents an analysis of the electromagnetic noise and vibration in a surface-mounted permanent magnet synchronous machine (SPMSM), focusing on their excitation sources. To investigate this, the excitation sources were identified through an analytical approach, and their effects on electromagnetic noise and vibration were evaluated using a finite element method (FEM)-based analysis approach. Additionally, an equivalent curved-beam model based on three-dimensional shell theory was applied to determine the deflection forces on the stator yoke, accounting for the tooth-modulation effect. The stator’s natural frequencies were derived through the characteristic equation in free vibration analysis. Modal analysis was performed to validate the analytically derived natural frequencies and to investigate stator deformation under the tooth-modulation effect across various vibration modes. Furthermore, noise, vibration, and harshness (NVH) analysis via FEM reveals that major harmonic components align closely with the natural frequencies, identifying them as primary sources of elevated vibrations. A comparative study between 8-pole–9-slot and 8-pole–12-slot SPMSMs highlights the impact of force variations on the stator teeth in relation to vibration and noise characteristics, with FEM verification. The proposed method provides a valuable tool for early-stage motor design, enabling the rapid identification of resonance operating points that may induce severe vibrations. This facilitates proactive mitigation strategies to enhance motor performance and reliability. Full article

This study presents a design and optimization methodology to enhance the power density and efficiency of wound field synchronous machines (WFSMs) by selectively applying grain-oriented electrical steel (GOES). Unlike conventional non-grain-oriented electrical steel (NOES), GOES exhibits significantly lower core loss along its rolling direction, making it suitable for regions with predominantly alternating magnetic fields. Based on magnetic field analysis, four machine configurations were investigated, differing in the placement of GOES within stator and rotor teeth. Finite element analysis (FEA) was employed to compare electromagnetic performance across the configurations. Subsequently, a multi-objective optimization was conducted using Latin Hypercube Sampling, meta-modeling, and a genetic algorithm to maximize power density and efficiency while minimizing torque ripple. The optimized WFSM achieved a 13.97% increase in power density and a 1.0% improvement in efficiency compared to the baseline NOES model. These results demonstrate the feasibility of applying GOES in rotating machines to reduce core loss and improve overall performance, offering a viable alternative to rare-earth permanent magnet machines in xEV applications. Full article

In order to achieve the optimal stator–rotor combinations of conventional flux-switching permanent magnet (FSPM) machines, this paper proposes and analyzes a general principle with prime phase numbers. Based on the coil complementarity concept, the proposed methodology specifically addresses the phase symmetry of back electromotive force (back-EMF) and electromagnetic torque optimization, with comprehensive analysis conducted for two-phase, three-phase, and five-phase configurations. Firstly, the coil-EMF vectors and the concept of coil pairs of conventional FSPM machines are introduced. Then, based on the coil-EMF vectors, an analytical model determining the stator pole and rotor teeth combinations is proposed. Further, the combinations for conventional FSPM machines with prime phase numbers are synthesized and summarized on the basis of the results obtained by the proposed model. To validate the model and combination principles, the FSPM machines satisfying the principles have been verified to exhibit a symmetrical phase back-EMF waveform by finite element analysis (FEA) and experiments on prototypes. In addition, the winding factors of the conventional FSPM machines with different stator pole and rotor teeth combinations are calculated. Full article

To address the high vibration and noise in fractional-slot concentrated-winding permanent magnet synchronous machines for electric vehicles, this study focuses on a 30-pole, 36-slot fractional-slot concentrated-winding permanent magnet synchronous machine. These issues are mainly caused by the modulation of high-order radial electromagnetic forces into low-order radial electromagnetic forces, known as the teeth modulation effect. The characteristics of radial electromagnetic forces are analyzed using the Maxwell stress tensor method, and the modulation process is examined. A novel unequal-teeth stator structure is proposed to reduce vibration and noise. Finite element simulations are performed to investigate how this structure affects the amplitude of modulated low-order radial electromagnetic forces. The optimal ratio of the unequal-teeth design is identified to effectively suppress the modulation effect. Simulation results indicate that an appropriately chosen unequal-teeth proportion leads to significant improvements in the machine’s vibration and noise performance across various operating conditions, providing a preliminary validation of the feasibility and effectiveness of the proposed unequal-teeth design methodology. Full article

In practical applications, the fully enclosed structure is always required by self-starting permanent magnet synchronous motors for safety. However, internal heat dissipation can be obstructed as a result, which affects operational reliability. To resolve the issue, this study takes a 3 kW self-starting permanent magnet synchronous motor as the research object. Based on fluid dynamics and fluid solid coupling heat transfer theory, the model is reasonably simplified according to the characteristics of the structure of motor cooling, and basic assumptions and boundary conditions are given to establish a three-dimensional, whole machine solution domain model. The finite element method is used to numerically analyze and calculate under rated conditions. The fluid flow characteristics, heat transfer characteristics, motion trajectories of the cooling medium on the surface of the external casing, fan, and internal stator and rotor domains, and winding ends are analyzed. Therefore, the internal rheological characteristics and temperature rise distribution law of the self-starting permanent magnet synchronous motor can be revealed. Based on the aforementioned research, a novel method to design the wind spur structure on the surface of the rotor end is proposed. By comparing the simulation results of the fluid field and temperature field of the motor under wind spur structures with different lengths and equidistant distributions in the circumferential direction of the rotor end, the influence of the convective heat characteristics can be systematically studied. Lastly, the accuracy of the calculation results and the rationality of the solution method are verified through experiments of temperature rise, and the flow temperature distribution characteristics of the motor can be optimized by the wind spur structure, which can be used in practical applications. Full article

A novel brushless power feedback permanent magnet adjustable speed drive (BLPF-PMASD) is developed for the energy-saving of a large power electrical machine drive system in this paper. It can transfer the slip power between the input and output shafts to a stator and then transmit it back to the power grid, achieving higher drive efficiency and stability. First, the topology feature, operation principle, and power feedback mechanism of the proposed drive are clearly illustrated. Second, a multi-objective optimization design method suitable for all working conditions is proposed to provide an effective design means for this type of adjustable speed drive with power feedback. Finally, the electromagnetic performance of the optimized drive is analyzed by using the finite element method (FEM) to demonstrate the effectiveness and superiority of the proposed drive. Full article

This paper introduces a hybrid analytical model (HAM) for the evaluation of permanent-magnet (PM) eddy-current loss in dual-stator single-rotor axial flux permanent-magnet machine (AFPMM), accounting for stator saturation. The proposed model integrates the magnetic equivalent circuit (MEC) with an analytical model based on scalar magnetic potential, enabling simultaneous consideration of different rotor positions and stator slotting effects. The three-dimensional finite element method (3D-FEM) validates the no-load and armature reaction magnetic field calculated by HAM, as well as the PM eddy-current loss under both no-load and load conditions. Compared to 3D-FEM, the proposed model reduces the calculation time by more than 98% with an error of no more than 18%, demonstrating a significant advantage in terms of computational time. Based on the proposed model, the effects of air-gap length and slot opening width on PM eddy-current loss are analyzed; the results indicate that reducing the slot opening width can effectively mitigate PM eddy-current loss for AFPMM. Full article

Owing to the distinct advantages of stator–permanent magnet (PM) motors over other PM machines, their prominence in high-power-density applications is surging dramatically, capturing growing interest across diverse applications. This article proposes an innovative design procedure for two primary stator–PM motor types, flux switching and biased flux, yielding 30 novel motor designs. The procedure involves splitting teeth, incorporating a flux reversal effect, and embedding flux barriers into the conventional structure. The analytical reasons behind the novel motors’ architecture are mathematically expressed and verified using finite element analysis (FEA). Through an effective optimisation based on a multi-objective genetic algorithm, various feasible stator/rotor pole combinations are explored, with over 36,000 samples evaluated using FEA coupled with the algorithm. The electromagnetic characteristics of promising motors are analysed, revealing that adding the flux reversal effect and flux barriers, which reduce PM volume while decreasing leakage flux and enhancing air gap flux, improves torque production by up to 68%. Beyond torque enhancement, other electromagnetic parameters, including torque ripple, core loss, and the power factor, are also improved. The proposed motors enhance the PM torque density significantly by about 115% compared to conventional motors and reduce the motor costs. A generalised decision-making process and thermal analysis are applied to the top-performing motors. Additionally, the prototyping measures and considerations are thoroughly discussed. Finally, a comprehensive conclusion is reached. Full article

In this study, a sensorless vector control method was proposed for a doubly fed induction machine (DFIM), where the stator is directly connected to the grid. The DFIM is a three-phase symmetric system without saliency, and when the stator side is directly connected to the grid, the magnitude and frequency of the stator flux are almost fixed and determined by the grid voltage. Due to its three-phase symmetric configuration, this structure can be modeled in a manner similar to that of a symmetric permanent-magnet synchronous motor (PMSM). It enables the application of back-EMF-based sensorless control methods commonly used for symmetric PMSMs. In PMSMs, sensorless estimators typically estimate the back-EMF using only stator voltage and current measurements. By extending this modeling concept to DFIMs, a similar estimator can be designed that utilizes only rotor-side voltage and current for sensorless back-EMF estimation. This paper proposes a back-EMF estimator using only rotor-side voltages and currents, which were implemented on a stator flux reference frame. The proposed algorithm also estimates the stator-side variables, including the magnitudes of stator voltage, current, and stator power factor. These variables can be used to detect grid faults. The feasibility of the proposed method was validated via experiments using a 2.4 kW DFIM. It was confirmed that the sensorless operation functioned properly even during speed acceleration/deceleration and step load conditions. Additionally, the system maintained stable operation and achieved an accurate estimation of stator voltage and current, even under a 30% voltage sag in the stator grid voltage. Full article

This paper proposes a novel nine-phase ferrite-assisted synchronous reluctance machine (FA-SynRM) featuring skewed stator slots to address challenges related to harmonic distortion, torque ripple, and material sustainability which are prevalent in conventional permanent magnet-assisted synchronous reluctance motors (PMa-SynRMs). Existing PMa-SynRMs often suffer from increased torque ripples and harmonic distortion, while reliance on rare-earth materials raises cost and sustainability concerns. To address these issues, the proposed design incorporates low-cost ferrite magnets embedded within the rotor flux barriers to achieve a flux-concentrated effect and enhanced torque production. The nine-phase winding configuration is utilized to improve fault tolerance, reduce harmonic distortion, and enable smoother torque output compared with conventional three-phase counterparts. In addition, the skewed stator slot design further minimizes harmonic components, reducing overall distortion. The proposed machine is validated through finite element analysis (FEA), and experimental verification is obtained by measuring the inductance characteristics and back-EMF of the nine-phase winding, confirming the feasibility of the electromagnetic design. The results demonstrate significant reductions in harmonic distortion and torque ripples, verifying the potential of this design. Full article

The dual three-phase permanent magnet synchronous motor (DT-PMSM) has the advantages of high fault tolerance, flexible control, small torque ripple, and meeting the requirements of low voltage and high power. However, in the traditional model of predictive torque control (MPTC) of DT-PMSM, the calculation is cumbersome due to the numerous voltage vectors. Therefore, a fast-switching table based on torque prediction DT-PMSM control is established. In addition, in the DT-PMSM conventional MPTC strategy, the cost function consists of the electromagnetic torque error and the stator flux error. Due to the lack of an explicit theory to guide the design of the weight coefficients, the weight coefficients can only be set through a large number of simulations and experiments in applications, and the tuning process is very cumbersome. Therefore, the support vector machine regression (SVR) method was used to improve the tedious calculation and tuning process of MPTC of DT-PMSM. The experimental results show that MPTC based on a fast-switching table achieves good steady-state and dynamic control performance by using weighting factors. Full article

This paper proposes a hybrid brushless wound-rotor synchronous machine (HB-WRSM) with an outer rotor topology that can operate as a permanent magnet synchronous machine (PMSM), as well as an HB-WRSM. In the first part, the existing brushless wound-rotor synchronous machine (BL-WRSM) is modified into a hybrid model by introducing permanent magnets (PMs) in the rotor pole faces to improve the magnetic field strength and other performance variables of the machine. In the second part, a centrifugal switch is introduced, which can change the machine operation from HB-WRSM to PMSM. The proposed machine uses an inner stator, outer rotor model with 36 stator slots and 48 poles, making the stator winding a concentrated winding. The HB-WRSM is utilized for dual-speed applications such as washing machines that run at low speed (46 rpm) and high speed (1370 rpm). For high speed, to have a better efficiency and less torque ripple, the machine is switched to PMSM mode using a centrifugal switch. The results are compared with the existing BL-WRSM. A 2D model is simulated using ANSYS Electromagnetics Suite to validate the machine model and performance. Full article