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Volume 52,Issue 8,2025 Table of Contents
2025, 52(8):823-834.
DOI: doi:10.12177/emca.2025.070
Abstract:
[Objective] To address the renewable energy curtailment caused by the mismatch between stochastic renewable generation and time-varying load characteristics in distributed smart grids, this paper proposes a source-load power ultra-short-term forecasting model integrating convolutional neural network (CNN), bidirectional gated recurrent unit (BiGRU), and multi-head attention (MHA) mechanisms. [Methods] Firstly, a CNN was emplayed to extract spatiotemporal features of renewable power. Subsequently, a BiGRU was utilized to capture bidirectional temporal dependencies in load sequences. Thirdly, MHA was introduced to dynamically assign weights to critical time-step information, and a Newton-Raphson based optimizer (NRBO) was utilized for the automatic hyperparameter tuning to enhance model generalization capability. Finally, this paper presented the NRBO-optimized CNN-BiGRU-MHA modeling framework, achieving accurate ultra-short-term forecasting of source-load power. [Results] Case studies demonstrated that compared to CNN-BiGRU and BiGRU models, the proposed CNN-BiGRU-MHA model reduced the relative error by 51.5% and 74.1%. The proposed NRBO-CNN-BiGRU-MHA model outperformed other commonly used algorithm models in prediction accuracy, with its predicted peak values closely matching the actual values in both magnitude and trend. The model excelled in handling smooth features and exhibited strong adaptability and robustness under both peak and off-peak power load conditions.[Conclusion] The model proposed in this paper demonstrates more stable prediction performance under different weather conditions, verifying the effectiveness of its spatio-temporal feature mining. It provides a new idea for power forecasting in scenarios with high-proportion new energy integration and has practical value for promoting the consumption of renewable energy.
[Objective] To address the renewable energy curtailment caused by the mismatch between stochastic renewable generation and time-varying load characteristics in distributed smart grids, this paper proposes a source-load power ultra-short-term forecasting model integrating convolutional neural network (CNN), bidirectional gated recurrent unit (BiGRU), and multi-head attention (MHA) mechanisms. [Methods] Firstly, a CNN was emplayed to extract spatiotemporal features of renewable power. Subsequently, a BiGRU was utilized to capture bidirectional temporal dependencies in load sequences. Thirdly, MHA was introduced to dynamically assign weights to critical time-step information, and a Newton-Raphson based optimizer (NRBO) was utilized for the automatic hyperparameter tuning to enhance model generalization capability. Finally, this paper presented the NRBO-optimized CNN-BiGRU-MHA modeling framework, achieving accurate ultra-short-term forecasting of source-load power. [Results] Case studies demonstrated that compared to CNN-BiGRU and BiGRU models, the proposed CNN-BiGRU-MHA model reduced the relative error by 51.5% and 74.1%. The proposed NRBO-CNN-BiGRU-MHA model outperformed other commonly used algorithm models in prediction accuracy, with its predicted peak values closely matching the actual values in both magnitude and trend. The model excelled in handling smooth features and exhibited strong adaptability and robustness under both peak and off-peak power load conditions.[Conclusion] The model proposed in this paper demonstrates more stable prediction performance under different weather conditions, verifying the effectiveness of its spatio-temporal feature mining. It provides a new idea for power forecasting in scenarios with high-proportion new energy integration and has practical value for promoting the consumption of renewable energy.
MA Bin
,
XU Qiongjing
,
ZHANG Ruowei
,
DUAN Lingli
,
ZHANG Yao
,
ZHANG Tinghui
,
WANG Yuting
,
ZHU Ying
2025, 52(8):835-843.
DOI: doi:10.12177/emca.2025.071
Abstract:
[Objective] In recent years, secondary segmented flux-switching permanent magnet linear motor (FSPMLM) has demonstrated significant application potential in urban rail transit traction systems, owing to their simple structure, high efficiency, high power density, and low manufacturing cost. To verify the effectiveness of the traction control strategy for this type of motor under real-world power supply conditions, this paper conducts a comprehensive study involving system modeling, simulation, and experimental performance evaluation. [Methods] Firstly, a power supply model that incorporated dynamic voltage fluctuations was developed to accurately simulate the operating environment of urban rail DC traction systems. This model reflectd the typical voltage variations encountered during actual operation. Next, based on the results of finite element analysis, the d-q axis mathematical model of the FSPMLM was established. A magnetic field-oriented control strategy was then designed to achieve precise closed-loop speed control. Finally, the entire system was modeled and validated using Matlab/Simulink simulation tools. Additionally, a low-power experimental platform was constructed, based on a physical prototype, to obtain real measurement data and validate the simulation outcomes by comparing key performance indicators. [Results] Both the simulation and experimental results showed consistent findings: the motor system achieved high control accuracy and rapid dynamic response under conditions of sudden speed variation. It also maintained low thrust fluctuation, strong system stability, and excellent dynamic and steady-state performance. These results confirmed the reliability and responsiveness of the proposed control strategy. [Conclusion] This study confirms that the secondary segmented FSPMLM, when equipped with a vector control strategy, can achieve efficient and stable speed regulation under the voltage conditions typical of urban subway power supply systems. The approach offers a cost-effective, technically sound solution with strong engineering practicality and wide application potential in modern electrified traction systems for urban rail transit.
[Objective] In recent years, secondary segmented flux-switching permanent magnet linear motor (FSPMLM) has demonstrated significant application potential in urban rail transit traction systems, owing to their simple structure, high efficiency, high power density, and low manufacturing cost. To verify the effectiveness of the traction control strategy for this type of motor under real-world power supply conditions, this paper conducts a comprehensive study involving system modeling, simulation, and experimental performance evaluation. [Methods] Firstly, a power supply model that incorporated dynamic voltage fluctuations was developed to accurately simulate the operating environment of urban rail DC traction systems. This model reflectd the typical voltage variations encountered during actual operation. Next, based on the results of finite element analysis, the d-q axis mathematical model of the FSPMLM was established. A magnetic field-oriented control strategy was then designed to achieve precise closed-loop speed control. Finally, the entire system was modeled and validated using Matlab/Simulink simulation tools. Additionally, a low-power experimental platform was constructed, based on a physical prototype, to obtain real measurement data and validate the simulation outcomes by comparing key performance indicators. [Results] Both the simulation and experimental results showed consistent findings: the motor system achieved high control accuracy and rapid dynamic response under conditions of sudden speed variation. It also maintained low thrust fluctuation, strong system stability, and excellent dynamic and steady-state performance. These results confirmed the reliability and responsiveness of the proposed control strategy. [Conclusion] This study confirms that the secondary segmented FSPMLM, when equipped with a vector control strategy, can achieve efficient and stable speed regulation under the voltage conditions typical of urban subway power supply systems. The approach offers a cost-effective, technically sound solution with strong engineering practicality and wide application potential in modern electrified traction systems for urban rail transit.
3 Research on Fault Detection Method of Flexible DC Distribution Network Based on TransGAN Algorithm
2025, 52(8):844-856.
DOI: doi:10.12177/emca.2025.078
Abstract:
[Objective] Aiming at the problem that the existing methods for detecting faults in flexible DC distribution networks have low accuracy and high cost of acquiring fault signals, this paper proposes a fault accurate detection method based on the Transformer algorithm and the generative adversarial network (GAN) fusion model. [Methods] Firstly, the effective modal components of the preprocessed DC distribution network fault voltage and current signals were extracted by adaptive variational mode decomposition method, and the effective feature vectors were extracted by Transformer algorithm. Then, the GAN model generator was replaced by Transformer algorithm, and the TransGAN deep learning model was established based on it. Finally, a simulation model was established based on Matlab/Simulink to verify the effectiveness and accuracy of the proposed method. [Results] Experimental results showed that this method has significant advantages in improving fault detection accuracy and reducing false alarm rate. Compared with the existing detection methods, it has higher fault recognition accuracy and stronger generalization ability. [Conclusion] The proposed method achieving higher detection accuracy, the required data set size is smaller than other methods, which reduces the data acquisition cost and computational complexity, and improves the practical application value and engineering feasibility of the model.
[Objective] Aiming at the problem that the existing methods for detecting faults in flexible DC distribution networks have low accuracy and high cost of acquiring fault signals, this paper proposes a fault accurate detection method based on the Transformer algorithm and the generative adversarial network (GAN) fusion model. [Methods] Firstly, the effective modal components of the preprocessed DC distribution network fault voltage and current signals were extracted by adaptive variational mode decomposition method, and the effective feature vectors were extracted by Transformer algorithm. Then, the GAN model generator was replaced by Transformer algorithm, and the TransGAN deep learning model was established based on it. Finally, a simulation model was established based on Matlab/Simulink to verify the effectiveness and accuracy of the proposed method. [Results] Experimental results showed that this method has significant advantages in improving fault detection accuracy and reducing false alarm rate. Compared with the existing detection methods, it has higher fault recognition accuracy and stronger generalization ability. [Conclusion] The proposed method achieving higher detection accuracy, the required data set size is smaller than other methods, which reduces the data acquisition cost and computational complexity, and improves the practical application value and engineering feasibility of the model.
2025, 52(8):857-868.
DOI: doi:10.12177/emca.2025.068
Abstract:
[Objective] The 46 phase brushless exciter used in the 1 750 MW nuclear power unit, which has the largest single unit capacity in the world, is significantly different from the common odd numbered camera types. Currently, research on ultra large capacity and even-phase brushless exciters is still relatively lagging behind, and there is an urgent need to analyze the operating mechanism of the 46 phase exciter under various working conditions, including normal and fault conditions, in order to provide a basis for subsequent fault protection. Thus, this paper proposes an analysis method for the parallel equivalent model of armature winding based on even-phase toroidal brushless excitation machine. [Methods] Firstly, the actual structure of the armature winding of the 46 phase brushless excitation machine was analyzed in detail, and then the theoretical waveforms of diode current, armature current, and excitation current were obtained. Then, based on the armature reaction magnetic potential, the harmonic characteristics of the stator excitation current during normal operation, single-diode open circuit, single-phase open circuit, and two-phase open circuit were obtained. Finally, the performance of the proposed analytical method was validated by establishing a finite element simulation model consistent with the actual physical machine. [Results] The correctness of the armature winding parallel equivalent model and the harmonic characteristics of stator excitation current under various operating conditions were verified based on the real machine experiments and finite element simulation results of the 46 phase actual unit. [Conclusion] This paper investigates the operational characteristics of even-phase annular brushless excitation systems and the fault signatures associated with various diode open-circuit failures. The study provides a reference for further research on fault diagnosis in high-capacity nuclear power plants multi-phase brushless excitation systems.
[Objective] The 46 phase brushless exciter used in the 1 750 MW nuclear power unit, which has the largest single unit capacity in the world, is significantly different from the common odd numbered camera types. Currently, research on ultra large capacity and even-phase brushless exciters is still relatively lagging behind, and there is an urgent need to analyze the operating mechanism of the 46 phase exciter under various working conditions, including normal and fault conditions, in order to provide a basis for subsequent fault protection. Thus, this paper proposes an analysis method for the parallel equivalent model of armature winding based on even-phase toroidal brushless excitation machine. [Methods] Firstly, the actual structure of the armature winding of the 46 phase brushless excitation machine was analyzed in detail, and then the theoretical waveforms of diode current, armature current, and excitation current were obtained. Then, based on the armature reaction magnetic potential, the harmonic characteristics of the stator excitation current during normal operation, single-diode open circuit, single-phase open circuit, and two-phase open circuit were obtained. Finally, the performance of the proposed analytical method was validated by establishing a finite element simulation model consistent with the actual physical machine. [Results] The correctness of the armature winding parallel equivalent model and the harmonic characteristics of stator excitation current under various operating conditions were verified based on the real machine experiments and finite element simulation results of the 46 phase actual unit. [Conclusion] This paper investigates the operational characteristics of even-phase annular brushless excitation systems and the fault signatures associated with various diode open-circuit failures. The study provides a reference for further research on fault diagnosis in high-capacity nuclear power plants multi-phase brushless excitation systems.
2025, 52(8):869-878.
DOI: doi:10.12177/emca.2025.066
Abstract:
[Objective] To address the issue of significantly increased AC winding losses in planar transformers caused by the flat winding structure exacerbating proximity and skin effects, this study proposes a topology optimization method for windings based on variable-width design, aiming to improve current distribution uniformity and reduce losses. [Methods] A multi-physics coupling model of winding AC effects was established, and eletromagnetic field theory was employed to analyze current density distribution patterns. A gradient variable-width parametric model was developed for circular windings to validate the regulatory mechanism of width variation on loss reduction. Building on circular winding optimization, nonlinear variable-width design criteria for rectangular windings were formulated, and two differentiated width adjustment schemes were developed. The electromagnetic performance of these schemes was evaluated using 3D finite element simulations. [Results] Experimental data demonstrated that the optimized rectangular variable-width windings achieved a 7.789% reduction in AC Ohmic losses while maintaining equivalent conductive area. Additionally, the maximum magnetic flux density in the winding region decreased by 3.766%, and current density distribution uniformity improved by 21.6%. The leakage inductance of the optimized variable-width winding was, on average, 49.1% higher than that of the equal-width winding. This indicated that the variable-width design indirectly increases the leakage inductance by altering the winding width and the number of turns per unit length. [Conclusion] The optimization design of variable-width circular windings is applied to rectangular windings. By actively controlling the electromagnetic field boundary conditions of the conductor cross-section, the phenomenon of eddy current accumulation under high-frequency conditions is effectively suppressed. This work prorides a quantifiable design paradigm for multi-objective collaborative optimization of planar transformer windings.
[Objective] To address the issue of significantly increased AC winding losses in planar transformers caused by the flat winding structure exacerbating proximity and skin effects, this study proposes a topology optimization method for windings based on variable-width design, aiming to improve current distribution uniformity and reduce losses. [Methods] A multi-physics coupling model of winding AC effects was established, and eletromagnetic field theory was employed to analyze current density distribution patterns. A gradient variable-width parametric model was developed for circular windings to validate the regulatory mechanism of width variation on loss reduction. Building on circular winding optimization, nonlinear variable-width design criteria for rectangular windings were formulated, and two differentiated width adjustment schemes were developed. The electromagnetic performance of these schemes was evaluated using 3D finite element simulations. [Results] Experimental data demonstrated that the optimized rectangular variable-width windings achieved a 7.789% reduction in AC Ohmic losses while maintaining equivalent conductive area. Additionally, the maximum magnetic flux density in the winding region decreased by 3.766%, and current density distribution uniformity improved by 21.6%. The leakage inductance of the optimized variable-width winding was, on average, 49.1% higher than that of the equal-width winding. This indicated that the variable-width design indirectly increases the leakage inductance by altering the winding width and the number of turns per unit length. [Conclusion] The optimization design of variable-width circular windings is applied to rectangular windings. By actively controlling the electromagnetic field boundary conditions of the conductor cross-section, the phenomenon of eddy current accumulation under high-frequency conditions is effectively suppressed. This work prorides a quantifiable design paradigm for multi-objective collaborative optimization of planar transformer windings.
2025, 52(8):879-887.
DOI: doi:10.12177/emca.2025.076
Abstract:
[Objective] The permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) has been widely adopted in industrial applications due to its excellent speed regulation performance and cost advantages. However, its further development is constrained by insufficient torque density. To enhance electromagnetic torque, the asymmetric rotor PMa-SynRM has become a research hotspot. Nevertheless, existing studies have failed to establish a quantitative relationship between the permanent magnet torque to reluctance torque proportion coefficient and electromagnetic torque enhancement capability, while also lacking systematic analysis of pole offset angle. Consequently, rapid evaluation of motor torque performance through torque proportion coefficient and pole offset angle remains challenging. To address this, this paper systematically investigates the impact of the torque proportion coefficient and pole shift angle on electromagnetic torque. [Methods] Based on these findings, this paper proposed an asymmetric rotor PMa-SynRM and evaluated its electromagnetic performance using the finite element method. [Results] The study revealed that as the torque proportion coefficient increases, the electromagnetic torque improvement initially rised and then declined, peaking when the ratio of permanent magnet torque to reluctance torque was 2. Furthermore, as the offset angle increases, the torque enhancement capability gradually strengthened. The results demonstrated that the proposed motor achieves a 7.82% increase in electromagnetic torque and a 57.73% reduction in torque ripple. [Conclusion] This study provides critical theoretical foundation for optimizing the torque performance of asymmetric rotor PMa-SynRMs.
[Objective] The permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) has been widely adopted in industrial applications due to its excellent speed regulation performance and cost advantages. However, its further development is constrained by insufficient torque density. To enhance electromagnetic torque, the asymmetric rotor PMa-SynRM has become a research hotspot. Nevertheless, existing studies have failed to establish a quantitative relationship between the permanent magnet torque to reluctance torque proportion coefficient and electromagnetic torque enhancement capability, while also lacking systematic analysis of pole offset angle. Consequently, rapid evaluation of motor torque performance through torque proportion coefficient and pole offset angle remains challenging. To address this, this paper systematically investigates the impact of the torque proportion coefficient and pole shift angle on electromagnetic torque. [Methods] Based on these findings, this paper proposed an asymmetric rotor PMa-SynRM and evaluated its electromagnetic performance using the finite element method. [Results] The study revealed that as the torque proportion coefficient increases, the electromagnetic torque improvement initially rised and then declined, peaking when the ratio of permanent magnet torque to reluctance torque was 2. Furthermore, as the offset angle increases, the torque enhancement capability gradually strengthened. The results demonstrated that the proposed motor achieves a 7.82% increase in electromagnetic torque and a 57.73% reduction in torque ripple. [Conclusion] This study provides critical theoretical foundation for optimizing the torque performance of asymmetric rotor PMa-SynRMs.
2025, 52(8):888-897.
DOI: doi:10.12177/emca.2025.075
Abstract:
[Objective] An optimisation model of a flexible microgrid is proposed to study the resilience of the system under extreme conditions while considering user satisfaction and pursuing economic operation. And the impact of flexible loads on user satisfaction is considered to improve user satisfaction while optimising economic dispatch. [Methods] This model integrated user satisfaction with microgrid economic operation and resilience enhancement, proposing a hybrid pelican optimization algorithm that simultaneously addresses pre-disaster prevention and post-disaster recovery strategies. A hybrid pelican algorithm was proposed, which contains multiple strategies of inertia weights, Lévy flights, attenuation factors and t-distribution. Mixing multiple strategies gradually improved the solution accuracy of the pelican algorithm. [Results] In simulation tests of low-probability high-impact scenarios, the proposed algorithm demonstrated significant performance advantages over butterfly optimization algorithm, particle swarm optimization algorithm, grey wolf optimization algorithm, artificial bee colony optimization algorithm, and the original algorithm, achieving system operational cost reductions of 26.7%, 27.0%, 26.1%, 21.8%, and 6.7% respectively, significant perpormance advantages. [Conclusion] The model can improve user satisfaction to a certain extent and proves that the proposed algorithm is more superior in solving the optimal economic operation and resilience problems of microgrids.
[Objective] An optimisation model of a flexible microgrid is proposed to study the resilience of the system under extreme conditions while considering user satisfaction and pursuing economic operation. And the impact of flexible loads on user satisfaction is considered to improve user satisfaction while optimising economic dispatch. [Methods] This model integrated user satisfaction with microgrid economic operation and resilience enhancement, proposing a hybrid pelican optimization algorithm that simultaneously addresses pre-disaster prevention and post-disaster recovery strategies. A hybrid pelican algorithm was proposed, which contains multiple strategies of inertia weights, Lévy flights, attenuation factors and t-distribution. Mixing multiple strategies gradually improved the solution accuracy of the pelican algorithm. [Results] In simulation tests of low-probability high-impact scenarios, the proposed algorithm demonstrated significant performance advantages over butterfly optimization algorithm, particle swarm optimization algorithm, grey wolf optimization algorithm, artificial bee colony optimization algorithm, and the original algorithm, achieving system operational cost reductions of 26.7%, 27.0%, 26.1%, 21.8%, and 6.7% respectively, significant perpormance advantages. [Conclusion] The model can improve user satisfaction to a certain extent and proves that the proposed algorithm is more superior in solving the optimal economic operation and resilience problems of microgrids.
2025, 52(8):898-905.
DOI: doi:10.12177/emca.2025.074
Abstract:
[Objective] Aiming at the problem that the relatively high temperature rise caused by high power density affects the power of the motor, this paper takes the high-power-density electric tail rotor motor drive system as the research object and systematically carries out the optimization work on the performance of the motor’s thermal characteristics and heat dissipation structure. The purpose is to improve the heat dissipation efficiency of the motor by modifying the topological structure of the motor’s heat dissipation, and ultimately increase the power density of the motor. [Methods] This study presented a systematic integrated optimization design for system-level heat-dissipation fin coupling. Through computational fluid dynamics simulations of the airflow field surrounding the motor system, the spatial arrangement of heat-dissipation fins-key components of the system was optimized to enhance thermal management performance. Subsequently, nine different heat dissipation topological structures were designed and their efficiency was verified through simulation, resulting in the optimal fin topology. Finally, the accuracy of the research was confirmed by simulating the fluid and temperature fields using the finite element method. [Results] Simulation results demonstrated that when the heat-dissipating metal fins of the motor and the controller housing were arranged alternately at a 50-degree angle, turbulent flow was generated in the airflow field surrounding the housing, effectively enhancing the heat-dissipation performance. The multi-layer square-hole heat-dissipation topology not only offers favorable manufacturability and processability but also achieves high heat-dissipation efficiency. Compared with conventional heat-dissipation fin structures, this innovative design boosted heat-dissipation efficiency by 9.3%. [Conclusion] The systematic thermal management solution proposed in this paper can significantly improve the motor cooling efficiency, accumulating practical experience for the subsequent thermal structure design of aviation motors.
[Objective] Aiming at the problem that the relatively high temperature rise caused by high power density affects the power of the motor, this paper takes the high-power-density electric tail rotor motor drive system as the research object and systematically carries out the optimization work on the performance of the motor’s thermal characteristics and heat dissipation structure. The purpose is to improve the heat dissipation efficiency of the motor by modifying the topological structure of the motor’s heat dissipation, and ultimately increase the power density of the motor. [Methods] This study presented a systematic integrated optimization design for system-level heat-dissipation fin coupling. Through computational fluid dynamics simulations of the airflow field surrounding the motor system, the spatial arrangement of heat-dissipation fins-key components of the system was optimized to enhance thermal management performance. Subsequently, nine different heat dissipation topological structures were designed and their efficiency was verified through simulation, resulting in the optimal fin topology. Finally, the accuracy of the research was confirmed by simulating the fluid and temperature fields using the finite element method. [Results] Simulation results demonstrated that when the heat-dissipating metal fins of the motor and the controller housing were arranged alternately at a 50-degree angle, turbulent flow was generated in the airflow field surrounding the housing, effectively enhancing the heat-dissipation performance. The multi-layer square-hole heat-dissipation topology not only offers favorable manufacturability and processability but also achieves high heat-dissipation efficiency. Compared with conventional heat-dissipation fin structures, this innovative design boosted heat-dissipation efficiency by 9.3%. [Conclusion] The systematic thermal management solution proposed in this paper can significantly improve the motor cooling efficiency, accumulating practical experience for the subsequent thermal structure design of aviation motors.
2025, 52(8):906-916.
DOI: doi:10.12177/emca.2025.067
Abstract:
[Objective] Flexible manipulators are prone to residual vibrations due to their low-stiffness characteristics, resulting in degraded end-effector positioning accuracy. Additionally, dynamic fluctuations caused by load disturbances and load-side positional hysteresis induced by flexible shaft deformation further constrain high-precision control. Although conventional input shaping techniques can suppress vibrations, their open-loop nature fails to simultaneously address these multi-source disturbances. To address these challenges, this paper proposes a zero vibration and derivative-dynamic torque feedback compensation-load position feedback compensation (ZVD-DTFC-LPFC) composite control strategy. [Methods] Based on a dual-inertia system model, an open-loop and closed-loop collaborative architecture was constructed. The open-loop side employs zero vibration and derivative (ZVD) input shaping to suppress residual vibration. The closed-loop side designed dynamic torque feedback compensation (DTFC), which used a reduced-order state observer to estimate the shaft torque in real time, forming a four-loop cascade control of position-speed-torque-current to resist load disturbances. Additionally, a load position feedback compensation (LPFC) algorithm was designed to dynamically calculate the load position deviation and superimpose it onto the motor encoder signal to eliminate steady-state lag. [Results] Simulation results showed that the residual vibration suppression rate of ZVD-DTFC-LPFC under no-load conditions was 98%; the average dynamic response time under 25%, 50%, and 100% load changes was 0.11 s, which was 54% shorter than that of ZVD; the steady-state position lag angle under load was less than 0.005 rad, which was reduced by 97% compared to before compensation. [Conclusion] The ZVD-DTFC-LPFC strategy synergizes open-loop vibration suppression with closed-loop disturbance rejection, achieving multi-objective optimization of vibration, disturbance, and hysteresis. This framework provides a robust paradigm for precision control of flexible manipulators.
[Objective] Flexible manipulators are prone to residual vibrations due to their low-stiffness characteristics, resulting in degraded end-effector positioning accuracy. Additionally, dynamic fluctuations caused by load disturbances and load-side positional hysteresis induced by flexible shaft deformation further constrain high-precision control. Although conventional input shaping techniques can suppress vibrations, their open-loop nature fails to simultaneously address these multi-source disturbances. To address these challenges, this paper proposes a zero vibration and derivative-dynamic torque feedback compensation-load position feedback compensation (ZVD-DTFC-LPFC) composite control strategy. [Methods] Based on a dual-inertia system model, an open-loop and closed-loop collaborative architecture was constructed. The open-loop side employs zero vibration and derivative (ZVD) input shaping to suppress residual vibration. The closed-loop side designed dynamic torque feedback compensation (DTFC), which used a reduced-order state observer to estimate the shaft torque in real time, forming a four-loop cascade control of position-speed-torque-current to resist load disturbances. Additionally, a load position feedback compensation (LPFC) algorithm was designed to dynamically calculate the load position deviation and superimpose it onto the motor encoder signal to eliminate steady-state lag. [Results] Simulation results showed that the residual vibration suppression rate of ZVD-DTFC-LPFC under no-load conditions was 98%; the average dynamic response time under 25%, 50%, and 100% load changes was 0.11 s, which was 54% shorter than that of ZVD; the steady-state position lag angle under load was less than 0.005 rad, which was reduced by 97% compared to before compensation. [Conclusion] The ZVD-DTFC-LPFC strategy synergizes open-loop vibration suppression with closed-loop disturbance rejection, achieving multi-objective optimization of vibration, disturbance, and hysteresis. This framework provides a robust paradigm for precision control of flexible manipulators.
2025, 52(8):917-923.
DOI: doi:10.12177/emca.2025.072
Abstract:
[Objective] Permanent magnet canned motor (PMCM) are widely used in petroleum, chemical, and nuclear industries due to their unique advantages. However, during operation, PMCM exhibit significant can losses, resulting in relatively low overall efficiency. This limitation substantially restricts their broader adoption and application, hindering technological progress and equipment upgrades in related industries. To address these challenges, this paper proposes an innovative sinusoidal air-gap magnetic flux density design method. [Methods] Through in-depth research and theoretical analysis, this study conducted a comprehensive optimization design of the permanent magnet parameters for a 1.5 kW PMCM using the proposed method, determining the optimal magnet dimensions. Additionally, finite element analysis was systematically employed to compare and analyze the performance of the PMCM before and after optimization. [Results] The research results demonstrated that the proposed design method can effectively reduce harmonic content in the air-gap magnetic flux density, significantly improving motor performance. After optimization, the motor losses were reduced by 30.44%, efficiency was increased by 8.87%, and the maximum operating temperature was lowered by 8.36%. [Conclusion] This research provides theoretical support for the widespread application of PMCM, facilitating the development of efficient and reliable motor equipment, thereby creating significant economic and social benefits.
[Objective] Permanent magnet canned motor (PMCM) are widely used in petroleum, chemical, and nuclear industries due to their unique advantages. However, during operation, PMCM exhibit significant can losses, resulting in relatively low overall efficiency. This limitation substantially restricts their broader adoption and application, hindering technological progress and equipment upgrades in related industries. To address these challenges, this paper proposes an innovative sinusoidal air-gap magnetic flux density design method. [Methods] Through in-depth research and theoretical analysis, this study conducted a comprehensive optimization design of the permanent magnet parameters for a 1.5 kW PMCM using the proposed method, determining the optimal magnet dimensions. Additionally, finite element analysis was systematically employed to compare and analyze the performance of the PMCM before and after optimization. [Results] The research results demonstrated that the proposed design method can effectively reduce harmonic content in the air-gap magnetic flux density, significantly improving motor performance. After optimization, the motor losses were reduced by 30.44%, efficiency was increased by 8.87%, and the maximum operating temperature was lowered by 8.36%. [Conclusion] This research provides theoretical support for the widespread application of PMCM, facilitating the development of efficient and reliable motor equipment, thereby creating significant economic and social benefits.
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Electric Machines & Control Application ® 2025
Supported by:Beijing E-Tiller Technology Development Co., Ltd.
沪ICP备16038578号-3
Electric Machines & Control Application ® 2025
Supported by:Beijing E-Tiller Technology Development Co., Ltd.
