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Volume 53,Issue 4,2026 Table of Contents
2026, 53(4):318-327.
DOI: 10.12177/emca.2026.151
Abstract:
[Objective] This paper proposes a harmonic elimination slot structure for the rotor bars of a 5.5 kW inverter-fed squirrel-cage induction motor, aiming to improve the current density distribution in the rotor bars and minimize local hot spots near the slot openings. [Methods] The analysis was initially conducted based on magnetomotive force and magnetic permeability to examine the air-gap magnetic field components and induced harmonics current in the rotor bars of the induction motor. The penetration depths of different harmonics current were calculated according to the skin effect. Subsequently, a mathematical model was established for the current-carrying area of individual bars as a function of harmonic elimination slot geometry and parameters, derived from the rotor slot opening geometric model. An optimization design process for the harmonic elimination slots was proposed by combining this mathematical model with limited simulation data. Finally, the optimal parameters for the rotor harmonic elimination slots of the specified induction motor were determined through simulation verification. [Results] Through simulation analysis, it was found that under no-load conditions, the rotor harmonic elimination slots reduced harmonic copper losses by 40.9%; under full-load conditions, a reduction of 5.5% was achieved. Additionally, the current-carrying area of the bars decreased by only 0.94%, indicating that the harmonic elimination slots did not significantly affect other electromagnetic performance in both operating conditions. [Conclusion] The proposed rotor harmonic elimination slots in this paper can significantly reduce rotor harmonic copper losses, leading to a more uniform current distribution in the bars. This effectively mitigates local thermal stress and temperature rise in high-load motors, making it suitable for motor operating conditions with frequent start-stop cycles or power supply containing harmonics.
[Objective] This paper proposes a harmonic elimination slot structure for the rotor bars of a 5.5 kW inverter-fed squirrel-cage induction motor, aiming to improve the current density distribution in the rotor bars and minimize local hot spots near the slot openings. [Methods] The analysis was initially conducted based on magnetomotive force and magnetic permeability to examine the air-gap magnetic field components and induced harmonics current in the rotor bars of the induction motor. The penetration depths of different harmonics current were calculated according to the skin effect. Subsequently, a mathematical model was established for the current-carrying area of individual bars as a function of harmonic elimination slot geometry and parameters, derived from the rotor slot opening geometric model. An optimization design process for the harmonic elimination slots was proposed by combining this mathematical model with limited simulation data. Finally, the optimal parameters for the rotor harmonic elimination slots of the specified induction motor were determined through simulation verification. [Results] Through simulation analysis, it was found that under no-load conditions, the rotor harmonic elimination slots reduced harmonic copper losses by 40.9%; under full-load conditions, a reduction of 5.5% was achieved. Additionally, the current-carrying area of the bars decreased by only 0.94%, indicating that the harmonic elimination slots did not significantly affect other electromagnetic performance in both operating conditions. [Conclusion] The proposed rotor harmonic elimination slots in this paper can significantly reduce rotor harmonic copper losses, leading to a more uniform current distribution in the bars. This effectively mitigates local thermal stress and temperature rise in high-load motors, making it suitable for motor operating conditions with frequent start-stop cycles or power supply containing harmonics.
2026, 53(4):328-339.
DOI: 10.12177/emca.2026.147
Abstract:
[Objective] To address issues in traditional low-voltage power cable fault diagnosis, such as reliance on a single signal, insufficient feature extraction, and weak anti-interference capability, an intelligent diagnostic strategy is proposed that can achieve high robustness and high-precision identification under complex operating conditions. [Methods] An intelligent diagnostic method integrating variational mode decomposition-Hilbert transform (VMD-HT) and multi-source one-dimensional convolutional neural network (MS-1DCNN) was proposed. A time-frequency analysis framework was constructed using VMD and HT to adaptively decompose signals of different modes and quantify feature parameters. Meanwhile, the MS-1DCNN structure was designed to achieve unified modeling and diagnosis of multiple types of cable faults. [Results] The experimental results demonstrated that the proposed MS-1DCNN diagnostic model outperformed conventional methods in terms of fault feature separability, classification accuracy, and stability under complex noise conditions. Superior robustness to hyperparameter variations was also verified. [Conclusion] The proposed MS-1DCNN model significantly enhances the reliability of fault identification in low-voltage cables, making it suitable for online monitoring and early warning scenarios in actual power grids. It provides a scalable technical solution for ensuring the operational safety of low-voltage distribution systems. Key words: low-voltage power cable; fault diagnosis; variational mode decomposition; Hilbert transform; multi-source one-dimensional convolutional neural network
[Objective] To address issues in traditional low-voltage power cable fault diagnosis, such as reliance on a single signal, insufficient feature extraction, and weak anti-interference capability, an intelligent diagnostic strategy is proposed that can achieve high robustness and high-precision identification under complex operating conditions. [Methods] An intelligent diagnostic method integrating variational mode decomposition-Hilbert transform (VMD-HT) and multi-source one-dimensional convolutional neural network (MS-1DCNN) was proposed. A time-frequency analysis framework was constructed using VMD and HT to adaptively decompose signals of different modes and quantify feature parameters. Meanwhile, the MS-1DCNN structure was designed to achieve unified modeling and diagnosis of multiple types of cable faults. [Results] The experimental results demonstrated that the proposed MS-1DCNN diagnostic model outperformed conventional methods in terms of fault feature separability, classification accuracy, and stability under complex noise conditions. Superior robustness to hyperparameter variations was also verified. [Conclusion] The proposed MS-1DCNN model significantly enhances the reliability of fault identification in low-voltage cables, making it suitable for online monitoring and early warning scenarios in actual power grids. It provides a scalable technical solution for ensuring the operational safety of low-voltage distribution systems. Key words: low-voltage power cable; fault diagnosis; variational mode decomposition; Hilbert transform; multi-source one-dimensional convolutional neural network
2026, 53(4):340-350.
DOI: 10.12177/emca.2026.148
Abstract:
[Objective] To improve the reliability of the symmetrical six-phase permanent magnet synchronous motor (PMSM) drive system, this paper constructs a dynamic model based on a nine-switch converter and proposes an innovative open-circuit fault diagnosis method for the inverter. [Methods] Considering the dead-time effect of pulse width modulation, the logical mapping between the motor winding terminal-to-ground voltage and the switch state was defined. The dynamic correspondence between the phase voltage and the switch signal was established, and a unified logical model of the hybrid system was derived. Based on voltage hybrid logic operations, the voltage differences between standard and fault states were compared, and open-circuit faults were accurately located. [Results] The simulation results demonstrated that when an open-circuit fault occurred in the symmetrical six-phase PMSM inverter, the faulty switch could be accurately located through dynamic logic transformation and voltage difference analysis. [Conclusion] The proposed diagnostic method can effectively identify faults in a single switch or simultaneous open-circuit faults in two switches of the same bridge arm, demonstrating high accuracy and universality.
[Objective] To improve the reliability of the symmetrical six-phase permanent magnet synchronous motor (PMSM) drive system, this paper constructs a dynamic model based on a nine-switch converter and proposes an innovative open-circuit fault diagnosis method for the inverter. [Methods] Considering the dead-time effect of pulse width modulation, the logical mapping between the motor winding terminal-to-ground voltage and the switch state was defined. The dynamic correspondence between the phase voltage and the switch signal was established, and a unified logical model of the hybrid system was derived. Based on voltage hybrid logic operations, the voltage differences between standard and fault states were compared, and open-circuit faults were accurately located. [Results] The simulation results demonstrated that when an open-circuit fault occurred in the symmetrical six-phase PMSM inverter, the faulty switch could be accurately located through dynamic logic transformation and voltage difference analysis. [Conclusion] The proposed diagnostic method can effectively identify faults in a single switch or simultaneous open-circuit faults in two switches of the same bridge arm, demonstrating high accuracy and universality.
2026, 53(4):351-361.
DOI: 10.12177/emca.2026.149
Abstract:
[Objective] Aiming at the problems of small insulator defect size, susceptibility to complex background interference during detection, and large parameter volume of the baseline model, this paper proposes a lightweight insulator defect detection algorithm based on an improved CPLC-YOLOv8. [Methods] Firstly, the lightweight RepNCSPELAN4-CAA module was designed to replace the C2f module in YOLOv8’s backbone network, reducing parameter quantity while enhancing feature representation capability. Secondly, a small-defect detection layer P2 was added to strengthen the fusion of shallow and deep features, minimizing the loss of small-target information. Subsequently, a lightweight detection head was developed, where 1×1 convolution was employed for channel dimension adjustment and detail-enhanced convolution was utilized to replace conventional 3×3 convolution, achieving parameter sharing and feature enhancement. Finally, the convolutional block attention mechanism was introduced to suppress background interference through dual channel-spatial attention mechanisms, enhancing key feature representation and improving model robustness and detection accuracy. [Results] Experimental results on the custom insulator defect dataset demonstrated that the proposed CPLC-YOLOv8 achieved a mAP@0.5 of 0.928, representing a 2 percentage point improvement over the original YOLOv8. The model parameters were reduced to only 1.72 MB (42.8% reduction compared to YOLOv8), with a compressed model size of 4.12 MB (31.3% compression). Comparative evaluations with classic network models confirmed that CPLC-YOLOv8 exhibited significant advantages in detection accuracy, parameter efficiency, and model compactness, particularly demonstrating superior robustness and generalization capability in small object detection tasks. [Conclusion] The proposed algorithm achieves lightweight model design while maintaining high detection accuracy, making it suitable for deployment on resource-constrained edge devices with promising engineering application prospects. Future work will further explore the integration of multi-scale feature fusion and lightweight techniques to continuously enhance the algorithm’s adaptability and stability in practical power inspection scenarios.
[Objective] Aiming at the problems of small insulator defect size, susceptibility to complex background interference during detection, and large parameter volume of the baseline model, this paper proposes a lightweight insulator defect detection algorithm based on an improved CPLC-YOLOv8. [Methods] Firstly, the lightweight RepNCSPELAN4-CAA module was designed to replace the C2f module in YOLOv8’s backbone network, reducing parameter quantity while enhancing feature representation capability. Secondly, a small-defect detection layer P2 was added to strengthen the fusion of shallow and deep features, minimizing the loss of small-target information. Subsequently, a lightweight detection head was developed, where 1×1 convolution was employed for channel dimension adjustment and detail-enhanced convolution was utilized to replace conventional 3×3 convolution, achieving parameter sharing and feature enhancement. Finally, the convolutional block attention mechanism was introduced to suppress background interference through dual channel-spatial attention mechanisms, enhancing key feature representation and improving model robustness and detection accuracy. [Results] Experimental results on the custom insulator defect dataset demonstrated that the proposed CPLC-YOLOv8 achieved a mAP@0.5 of 0.928, representing a 2 percentage point improvement over the original YOLOv8. The model parameters were reduced to only 1.72 MB (42.8% reduction compared to YOLOv8), with a compressed model size of 4.12 MB (31.3% compression). Comparative evaluations with classic network models confirmed that CPLC-YOLOv8 exhibited significant advantages in detection accuracy, parameter efficiency, and model compactness, particularly demonstrating superior robustness and generalization capability in small object detection tasks. [Conclusion] The proposed algorithm achieves lightweight model design while maintaining high detection accuracy, making it suitable for deployment on resource-constrained edge devices with promising engineering application prospects. Future work will further explore the integration of multi-scale feature fusion and lightweight techniques to continuously enhance the algorithm’s adaptability and stability in practical power inspection scenarios.
2026, 53(4):362-371.
DOI: 10.12177/emca.2026.153
Abstract:
[Objective] Aiming at the nonlinear distortion of d-q axis inductance caused by magnetic saturation effects in the operation of synchronous reluctance motor (SynRM) drive systems, this paper proposes an online inductance parameter identification strategy based on robust recursive least square (RRLS). [Methods] Firstly, the predicted voltage difference was calculated to construct a historical prediction residual sequence, and rolling optimization was performed during motor operation to effectively reduce steady-state estimation errors caused by random data. Secondly, the predicted standard deviation was used as a robust scale to construct a robust loss function, which enhanced the algorithm’s ability to resist load disturbances without significantly increasing the computational burden. Then, an approximate equilibrium condition was combined with an adaptive mechanism with a variable forgetting factor for recursive estimation, and accurate parameter values were obtained through multiple iterations. Finally, a SynRM control and parameter identification system was built in Matlab/Simulink, and the RRLS algorithm was compared with the traditional variable forgetting factor recursive least square (VFFRLS) under different operating conditions. [Results] The simulation results showed that under no-load and load disturbance conditions, the proposed RRLS algorithm had lower identification errors. The steady-state error of the d-axis inductance was less than 0.5%, and the steady-state error of the q-axis inductance was less than 4%. During the dynamic process, the d-axis overshoot was reduced from 25 mH by the VFFRLS algorithm to 12 mH by the proposed RRLS algorithm, and the q-axis overshoot was reduced from 33 mH to 13 mH. [Conclusion] Compared with the traditional VFFRLS algorithm, the RRLS algorithm proposed in this paper achieves high steady-state identification accuracy, reduces overshoot during dynamic processes, and demonstrates excellent online identification performance under load disturbances, with high system robustness.
[Objective] Aiming at the nonlinear distortion of d-q axis inductance caused by magnetic saturation effects in the operation of synchronous reluctance motor (SynRM) drive systems, this paper proposes an online inductance parameter identification strategy based on robust recursive least square (RRLS). [Methods] Firstly, the predicted voltage difference was calculated to construct a historical prediction residual sequence, and rolling optimization was performed during motor operation to effectively reduce steady-state estimation errors caused by random data. Secondly, the predicted standard deviation was used as a robust scale to construct a robust loss function, which enhanced the algorithm’s ability to resist load disturbances without significantly increasing the computational burden. Then, an approximate equilibrium condition was combined with an adaptive mechanism with a variable forgetting factor for recursive estimation, and accurate parameter values were obtained through multiple iterations. Finally, a SynRM control and parameter identification system was built in Matlab/Simulink, and the RRLS algorithm was compared with the traditional variable forgetting factor recursive least square (VFFRLS) under different operating conditions. [Results] The simulation results showed that under no-load and load disturbance conditions, the proposed RRLS algorithm had lower identification errors. The steady-state error of the d-axis inductance was less than 0.5%, and the steady-state error of the q-axis inductance was less than 4%. During the dynamic process, the d-axis overshoot was reduced from 25 mH by the VFFRLS algorithm to 12 mH by the proposed RRLS algorithm, and the q-axis overshoot was reduced from 33 mH to 13 mH. [Conclusion] Compared with the traditional VFFRLS algorithm, the RRLS algorithm proposed in this paper achieves high steady-state identification accuracy, reduces overshoot during dynamic processes, and demonstrates excellent online identification performance under load disturbances, with high system robustness.
2026, 53(4):372-381.
DOI: 10.12177/emca.2026.143
Abstract:
[Objective] An improved method based on an optimized control set is proposed to address the issues of harmonic currents and torque ripple in the model predictive control (MPC) system of an open-end winding six-phase permanent magnet synchronous motor under single upper-arm faults. [Methods] Based on the vector space decoupling theory, the voltage vectors under single upper-arm faults and their distribution characteristics in both fundamental and harmonic planes were derived and analyzed. To ensure high voltage utilization, virtual vector synthesis was implemented. Addressing the challenge of selecting appropriate basic voltage vectors using conventional convex hull methods, an optimized control set-based model predictive fault-tolerant control (MPFTC) method was proposed in this study. Through post-fault vector characteristic analysis, an optimized control set was selected from the G5 vector group, and its impact on harmonic currents and torque ripple performance was evaluated. Comparative simulations between conventional MPC and the proposed optimized control set-based MPFTC method were conducted under fault conditions. [Results] The simulation results demonstrated that the proposed MPFTC method effectively reduced the total harmonic distortion of the current from 50.54% to 5.96% under fault conditions, with the third-order harmonic component suppressed below 5%. Additionally, the electromagnetic torque exhibited only a transient drop of 1 N·m and recovered within 10 ms, successfully mitigating the untreated 50 Hz oscillation with an amplitude of ±50 N·m. [Conclusion] The proposed MPFTC method demonstrates significant effectiveness in harmonic suppression and torque ripple control, verifying its strong fault tolerance and engineering application value.
[Objective] An improved method based on an optimized control set is proposed to address the issues of harmonic currents and torque ripple in the model predictive control (MPC) system of an open-end winding six-phase permanent magnet synchronous motor under single upper-arm faults. [Methods] Based on the vector space decoupling theory, the voltage vectors under single upper-arm faults and their distribution characteristics in both fundamental and harmonic planes were derived and analyzed. To ensure high voltage utilization, virtual vector synthesis was implemented. Addressing the challenge of selecting appropriate basic voltage vectors using conventional convex hull methods, an optimized control set-based model predictive fault-tolerant control (MPFTC) method was proposed in this study. Through post-fault vector characteristic analysis, an optimized control set was selected from the G5 vector group, and its impact on harmonic currents and torque ripple performance was evaluated. Comparative simulations between conventional MPC and the proposed optimized control set-based MPFTC method were conducted under fault conditions. [Results] The simulation results demonstrated that the proposed MPFTC method effectively reduced the total harmonic distortion of the current from 50.54% to 5.96% under fault conditions, with the third-order harmonic component suppressed below 5%. Additionally, the electromagnetic torque exhibited only a transient drop of 1 N·m and recovered within 10 ms, successfully mitigating the untreated 50 Hz oscillation with an amplitude of ±50 N·m. [Conclusion] The proposed MPFTC method demonstrates significant effectiveness in harmonic suppression and torque ripple control, verifying its strong fault tolerance and engineering application value.
2026, 53(4):382-390.
DOI: 10.12177/emca.2026.152
Abstract:
[Objective] Electromagnetic vibration characteristics are a core performance indicator of interior permanent magnet synchronous motor (IPMSM) for electric vehicles, directly determining their operational stability and playing a key role in noise control. Current research primarily focuses on the electromagnetic vibration features of IPMSM under normal operating conditions, while insufficient attention has been paid to the significant impact of stator and rotor deformations in practical scenarios. [Methods] This study focused on the air gap deformation caused by stator deformation and rotor mechanical stress deformation. The air gap permeance function after deformation was derived, and the expression of radial electromagnetic force for IPMSM under non-uniform air gap conditions was subsequently derived. Finite element simulations were conducted for validation. Finally, the difference in equivalent radiated power level on the motor housing surface before and after air gap deformation was calculated to clarify the variation patterns of vibration and noise. [Results] The simulation results demonstrated that: force waves of (n±m)p±ks orders (ks=1,2,3…8) were introduced by stator inner circular deformation through magnetic permeance modulation, depending on different deformation wave numbers. (n±m±2k)p-order force waves were generated by rotor mechanical deformation via the same modulation mechanism, and the amplitudes of inherent force waves were amplified. The low-order force waves modulated by stator deformation were found to easily couple with low-order structural modes at low rotational speeds, leading to non-negligible vibration noise. The inherent electromagnetic force wave amplitude was increased by rotor mechanical deformation at high speeds, leading to aggravated vibration. [Conclusion] This study reveals the correlation mechanism between stator/rotor deformation and electromagnetic vibration in IPMSM, providing a theoretical basis for the optimization of flux barriers and low-order modal decoupling under high-speed operating conditions.
[Objective] Electromagnetic vibration characteristics are a core performance indicator of interior permanent magnet synchronous motor (IPMSM) for electric vehicles, directly determining their operational stability and playing a key role in noise control. Current research primarily focuses on the electromagnetic vibration features of IPMSM under normal operating conditions, while insufficient attention has been paid to the significant impact of stator and rotor deformations in practical scenarios. [Methods] This study focused on the air gap deformation caused by stator deformation and rotor mechanical stress deformation. The air gap permeance function after deformation was derived, and the expression of radial electromagnetic force for IPMSM under non-uniform air gap conditions was subsequently derived. Finite element simulations were conducted for validation. Finally, the difference in equivalent radiated power level on the motor housing surface before and after air gap deformation was calculated to clarify the variation patterns of vibration and noise. [Results] The simulation results demonstrated that: force waves of (n±m)p±ks orders (ks=1,2,3…8) were introduced by stator inner circular deformation through magnetic permeance modulation, depending on different deformation wave numbers. (n±m±2k)p-order force waves were generated by rotor mechanical deformation via the same modulation mechanism, and the amplitudes of inherent force waves were amplified. The low-order force waves modulated by stator deformation were found to easily couple with low-order structural modes at low rotational speeds, leading to non-negligible vibration noise. The inherent electromagnetic force wave amplitude was increased by rotor mechanical deformation at high speeds, leading to aggravated vibration. [Conclusion] This study reveals the correlation mechanism between stator/rotor deformation and electromagnetic vibration in IPMSM, providing a theoretical basis for the optimization of flux barriers and low-order modal decoupling under high-speed operating conditions.
2026, 53(4):391-402.
DOI: 10.12177/emca.2026.144
Abstract:
[Objective] To address the issues of low control precision, slow convergence, and strong chattering in permanent magnet synchronous motor (PMSM) under rapid acceleration/deceleration and load changes, this paper proposes a fractional-order dynamic boundary layer super-twisting sliding mode active disturbance rejection control (FO-DBL-STSM-ADRC) strategy. [Methods] Firstly, the ADRC was integrated with the STSMC algorithm to enhance adaptability under complex operating conditions. Next, a novel DBL sliding mode surface was designed, which dynamically adjusted the boundary layer structure to improve the system’s dynamic response speed and load disturbance rejection capability. Then, fractional-order calculus was introduced to effectively suppress the inherent high-frequency chattering of traditional sliding mode control, significantly enhancing the system’s ability to inhibit steady-state errors and chattering. Finally, the superiority and robustness of the proposed FO-DBL-STSM-ADRC strategy were verified through simulation and experiment under various complex operating conditions. [Results] The simulation and experiment results showed that, compared to the other three strategies, the proposed FO-DBL-STSM-ADRC strategy demonstrated significant advantages in terms of response speed, steady-state control precision, load disturbance rejection capability, and overall system robustness. [Conclusion] The proposed FO-DBL-STSM-ADRC strategy not only provides an effective solution for the high-performance operation of PMSM, but also offers technical support for demanding engineering applications such as electric vehicle drives and rail transit door control systems.
[Objective] To address the issues of low control precision, slow convergence, and strong chattering in permanent magnet synchronous motor (PMSM) under rapid acceleration/deceleration and load changes, this paper proposes a fractional-order dynamic boundary layer super-twisting sliding mode active disturbance rejection control (FO-DBL-STSM-ADRC) strategy. [Methods] Firstly, the ADRC was integrated with the STSMC algorithm to enhance adaptability under complex operating conditions. Next, a novel DBL sliding mode surface was designed, which dynamically adjusted the boundary layer structure to improve the system’s dynamic response speed and load disturbance rejection capability. Then, fractional-order calculus was introduced to effectively suppress the inherent high-frequency chattering of traditional sliding mode control, significantly enhancing the system’s ability to inhibit steady-state errors and chattering. Finally, the superiority and robustness of the proposed FO-DBL-STSM-ADRC strategy were verified through simulation and experiment under various complex operating conditions. [Results] The simulation and experiment results showed that, compared to the other three strategies, the proposed FO-DBL-STSM-ADRC strategy demonstrated significant advantages in terms of response speed, steady-state control precision, load disturbance rejection capability, and overall system robustness. [Conclusion] The proposed FO-DBL-STSM-ADRC strategy not only provides an effective solution for the high-performance operation of PMSM, but also offers technical support for demanding engineering applications such as electric vehicle drives and rail transit door control systems.
2026, 53(4):403-408.
DOI: 10.12177/emca.2026.141
Abstract:
[Objective] The IE5 energy efficiency class is currently the highest global standard for low-voltage three-phase asynchronous motors, corresponding to the 1st energy efficiency level in the national standard GB/T 18613—2020. In response to the lack of unified design for IE5 energy efficiency series motors in China, the Shanghai Electrical Apparatus Research Institute has organized the development of the YE5 series (IP55) three-phase asynchronous motor to promote the advancement of 1st energy efficiency motors. The IE5 energy efficiency is the highest global standard, equivalent to the 1st energy efficiency level in GB/T 18613—2020. [Methods] A working group was formed by uniting leading manufacturers and upstream/downstream enterprises. Based on the joint design of IE2 efficiency motors, energy-saving technologies such as unequal-slot design, stamped air-gap process, and low-pressure aluminum die-casting were comprehensively applied, significantly reducing additional motor losses and thereby improving motor efficiency. [Results] The complete product series of low-voltage three-phase asynchronous motors was developed through breakthroughs and applications of key technologies. Prototype testing of 30 units across 16 specifications demonstrated that all motor efficiencies met the IE5 efficiency limits specified in GB/T 18613—2020, confirming the design’s validity. [Conclusion] This project achieves the first unified industry design for a series of 1st energy efficiency low-voltage three-phase asynchronous motors in China, filling a product gap and providing crucial practical support for the energy efficiency upgrade of the motor industry.
[Objective] The IE5 energy efficiency class is currently the highest global standard for low-voltage three-phase asynchronous motors, corresponding to the 1st energy efficiency level in the national standard GB/T 18613—2020. In response to the lack of unified design for IE5 energy efficiency series motors in China, the Shanghai Electrical Apparatus Research Institute has organized the development of the YE5 series (IP55) three-phase asynchronous motor to promote the advancement of 1st energy efficiency motors. The IE5 energy efficiency is the highest global standard, equivalent to the 1st energy efficiency level in GB/T 18613—2020. [Methods] A working group was formed by uniting leading manufacturers and upstream/downstream enterprises. Based on the joint design of IE2 efficiency motors, energy-saving technologies such as unequal-slot design, stamped air-gap process, and low-pressure aluminum die-casting were comprehensively applied, significantly reducing additional motor losses and thereby improving motor efficiency. [Results] The complete product series of low-voltage three-phase asynchronous motors was developed through breakthroughs and applications of key technologies. Prototype testing of 30 units across 16 specifications demonstrated that all motor efficiencies met the IE5 efficiency limits specified in GB/T 18613—2020, confirming the design’s validity. [Conclusion] This project achieves the first unified industry design for a series of 1st energy efficiency low-voltage three-phase asynchronous motors in China, filling a product gap and providing crucial practical support for the energy efficiency upgrade of the motor industry.
2026, 53(4):409-419.
DOI: 10.12177/emca.2026.145
Abstract:
[Objective] This paper proposes and designs an axial-flux discrete-modular counter-rotating dual-rotor synchronous generator (DM-AF-CRDRSG), aiming to achieve wide-band potential modulation and stable power generation under multi-pole-pair magnetic field coupling. [Methods] Firstly, the stator of the motor was designed with a rectangular iron core, 6-slot three-phase fractional-slot concentrated winding. The dual-rotor excitation (2/4 poles) was selectively coupled with the dominant component of the stator magnetomotive force. Then, a prototype test platform was built, and no-load and load tests were conducted, with the results compared to simulations. Next, 11 magnetically equivalent two-dimensional finite element models were constructed using Ansys Maxwell software, with tooth-slot ratios ranging from 1 to 3 in equal steps, and the voltage waveforms characteristics under different tooth-slot ratios were studied. Finally, the results of the Maxwell 2D models were superimposed and converted to the prototype model, and the induced voltage waveforms and harmonic spectrum characteristics of the simulation and experiment were compared and analyzed to verify the feasibility of the motor topology. [Results] The induced voltage waveforms from both the simulation and experiment exhibited good sinusoidal characteristics and were found to be basically consistent. Although the harmonic content in the simulation results was higher and the amplitude was slightly larger, the consistency between the two still verified the correctness and effectiveness of the DM-AF-CRDRSG structural design. [Conclusion] The DM-AF-CRDRSG designed in this paper exhibits excellent spatial potential modulation capability and stable power generation performance under wide-band magnetomotive force excitation.
[Objective] This paper proposes and designs an axial-flux discrete-modular counter-rotating dual-rotor synchronous generator (DM-AF-CRDRSG), aiming to achieve wide-band potential modulation and stable power generation under multi-pole-pair magnetic field coupling. [Methods] Firstly, the stator of the motor was designed with a rectangular iron core, 6-slot three-phase fractional-slot concentrated winding. The dual-rotor excitation (2/4 poles) was selectively coupled with the dominant component of the stator magnetomotive force. Then, a prototype test platform was built, and no-load and load tests were conducted, with the results compared to simulations. Next, 11 magnetically equivalent two-dimensional finite element models were constructed using Ansys Maxwell software, with tooth-slot ratios ranging from 1 to 3 in equal steps, and the voltage waveforms characteristics under different tooth-slot ratios were studied. Finally, the results of the Maxwell 2D models were superimposed and converted to the prototype model, and the induced voltage waveforms and harmonic spectrum characteristics of the simulation and experiment were compared and analyzed to verify the feasibility of the motor topology. [Results] The induced voltage waveforms from both the simulation and experiment exhibited good sinusoidal characteristics and were found to be basically consistent. Although the harmonic content in the simulation results was higher and the amplitude was slightly larger, the consistency between the two still verified the correctness and effectiveness of the DM-AF-CRDRSG structural design. [Conclusion] The DM-AF-CRDRSG designed in this paper exhibits excellent spatial potential modulation capability and stable power generation performance under wide-band magnetomotive force excitation.
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沪ICP备16038578号-3
Electric Machines & Control Application ® 2026
Supported by:Beijing E-Tiller Technology Development Co., Ltd.
沪ICP备16038578号-3
Electric Machines & Control Application ® 2026
Supported by:Beijing E-Tiller Technology Development Co., Ltd.
