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Volume 52,Issue 1,2025 Table of Contents
2025, 52(1):1-11.
DOI: 10.12177/emca.2024.153
Abstract:
[Objective] In response to the rotor vibration issues of doubly-fed linear motor (DFLM) under AC excitation, this paper proposes an adaptive compensation control method based on the filtered-x least mean-square (FxLMS) algorithm, aimed at enhancing both the dynamic performance and the operational stability of DFLM. [Method] Firstly, the electromagnetic vibration mechanism of DFLM under AC excitation was analyzed in depth. By establishing the two-point force model of a five-phase twenty-slot DFLM under AC excitation, the generation mechanism of the pitching moment induced by AC excitation was investigated. Secondly, based on the mechanism analysis, the FxLMS algorithm was introduced as the core control method, which relied on closed-loop feedback control to adaptively inject harmonic currents, thus effectively suppressing the periodic vibration. Finally, in order to further improve the control effect, a feedforward compensation control method based on the electric angle of the mover excitation current was proposed, in combination with the above generation mechanism of electromagnetic torque, improving the dynamic response capability of the system. [Results] To validate the effectiveness of the proposed method, simulation analysis and experimental verification were conducted. A dynamic model of the DFLM was established on the Matlab/Simulink platform, and the vibration response of the mover before and after the introduction of adaptive compensation control was compared and analyzed. The simulation results indicated that the adaptive compensation control method based on the FxLMS algorithm achieved substantial suppression of vertical mover vibrations. And the introduction of feed-forward control improved the dynamic performance of the control system and reduced the regulation pressure of the feedback control. To further verify the practical performance of the algorithm, an experimental platform was set up and tests were conducted under different operating conditions. Experimental results showed that the adaptive compensation control method based on the FxLMS algorithm significantly reduced the vertical mover vibrations induced by AC excitation. [Conclusion] The adaptive compensation control method based on FxLMS algorithm utilizes the adaptive characteristics of the FxLMS algorithm, combined with the feedforward compensation strategy. This approach effectively solves the vibration problem generated during the AC excitation process of DFLM without changing the original closed-loop control structure, significantly improved the operation stability and control accuracy of DFLM. It provides a novel solution for the high-performance control of DFLM.
[Objective] In response to the rotor vibration issues of doubly-fed linear motor (DFLM) under AC excitation, this paper proposes an adaptive compensation control method based on the filtered-x least mean-square (FxLMS) algorithm, aimed at enhancing both the dynamic performance and the operational stability of DFLM. [Method] Firstly, the electromagnetic vibration mechanism of DFLM under AC excitation was analyzed in depth. By establishing the two-point force model of a five-phase twenty-slot DFLM under AC excitation, the generation mechanism of the pitching moment induced by AC excitation was investigated. Secondly, based on the mechanism analysis, the FxLMS algorithm was introduced as the core control method, which relied on closed-loop feedback control to adaptively inject harmonic currents, thus effectively suppressing the periodic vibration. Finally, in order to further improve the control effect, a feedforward compensation control method based on the electric angle of the mover excitation current was proposed, in combination with the above generation mechanism of electromagnetic torque, improving the dynamic response capability of the system. [Results] To validate the effectiveness of the proposed method, simulation analysis and experimental verification were conducted. A dynamic model of the DFLM was established on the Matlab/Simulink platform, and the vibration response of the mover before and after the introduction of adaptive compensation control was compared and analyzed. The simulation results indicated that the adaptive compensation control method based on the FxLMS algorithm achieved substantial suppression of vertical mover vibrations. And the introduction of feed-forward control improved the dynamic performance of the control system and reduced the regulation pressure of the feedback control. To further verify the practical performance of the algorithm, an experimental platform was set up and tests were conducted under different operating conditions. Experimental results showed that the adaptive compensation control method based on the FxLMS algorithm significantly reduced the vertical mover vibrations induced by AC excitation. [Conclusion] The adaptive compensation control method based on FxLMS algorithm utilizes the adaptive characteristics of the FxLMS algorithm, combined with the feedforward compensation strategy. This approach effectively solves the vibration problem generated during the AC excitation process of DFLM without changing the original closed-loop control structure, significantly improved the operation stability and control accuracy of DFLM. It provides a novel solution for the high-performance control of DFLM.
2025, 52(1):12-21.
DOI: 10.12177/emca.2024.155
Abstract:
[Objective] Permanent magnet synchronous motor (PMSM) is widely used in wind power generation and electric vehicles due to its high power factor, simple structure and good dynamic performance. However, PMSM may experience phase loss faults during operation due to reasons such as drive failure or loose stator winding connections. When operating with phase loss, the PMSM generates noise and vibration, leading to a reduction in output power. Prolonged phase loss operation can also damage electrical equipment, making accurate fault diagnosis crucial for ensuring the normal operation of the equipment. [Methods] This paper proposed a fault diagnosis strategy based on an improved empirical wavelet transform (IEWT) and categorical boosting (CatBoost) algorithm, and applied it to the phase loss fault diagnosis of six-phase PMSM. First, the basic principle of the IEWT algorithm was introduced. The IEWT algorithm performed spectral segmentation on the Welch power spectrum, effectively suppressing modal aliasing compared
[Objective] Permanent magnet synchronous motor (PMSM) is widely used in wind power generation and electric vehicles due to its high power factor, simple structure and good dynamic performance. However, PMSM may experience phase loss faults during operation due to reasons such as drive failure or loose stator winding connections. When operating with phase loss, the PMSM generates noise and vibration, leading to a reduction in output power. Prolonged phase loss operation can also damage electrical equipment, making accurate fault diagnosis crucial for ensuring the normal operation of the equipment. [Methods] This paper proposed a fault diagnosis strategy based on an improved empirical wavelet transform (IEWT) and categorical boosting (CatBoost) algorithm, and applied it to the phase loss fault diagnosis of six-phase PMSM. First, the basic principle of the IEWT algorithm was introduced. The IEWT algorithm performed spectral segmentation on the Welch power spectrum, effectively suppressing modal aliasing compared
2025, 52(1):22-35.
DOI: 10.12177/emca.2024.147
Abstract:
[Objective] For armature winding inter-turn short circuit fault diagnosis in aerospace generators, this paper proposes a diagnostic method based on convolutional neural network (CNN) with squeeze-excitation (SE) attention mechanism and bidirectional long short-term memory (BiLSTM). It aims to enhance the effectiveness and robustness of armature winding fault diagnosis. [Methods] Firstly, an equivalent analytical model for armature winding inter-turn short circuit fault diagnosis in a doubly salient electromagnetic generator (DSEG) was established, and the vibration signal on the surface of the generator casing was adopted as a characteristic signal of the fault. Theoretical derivations of the expressions for the air gap magnetic flux density and electromagnetic force, which influenced vibration characteristics, were carried out. Secondly, the impact of electromagnetic force on vibration characteristics under various short circuits was analyzed using finite element simulation in Workbench software. Finally, vibration signals were collected and used as actual experimental data to extract relevant fault features. These extracted features were put into the CNN-SE-BiLSTM for efficient fault diagnosis. Among this, the CNN and BiLSTM networks effectively extracted local features and features in time series from vibration signals, while the SE attention mechanism optimized the feature weight distribution by selectively amplifying relevant diagnostic features, significantly enhancing the model’s fault diagnosis capability. [Results] The experimental results showed that the proposed CNN-SE-BiLSTM-based method achieved a diagnostic accuracy of over 99% for inter-turn short circuit faults in armature windings under various working conditions. Moreover, it still exhibited strong diagnostic performance in noisy environments. Compared to traditional diagnostic methods, the proposed method not only demonstrated strong anti-interference ability, high fault recognition accuracy, and fast diagnostic speed under various rotational speeds and load conditions, validating its applicability in aerospace generators with complex operating conditions. [Conclusion] The CNN-SE-BiLSTM diagnostic approach effectively improves the fault diagnosis efficiency and accuracy of DSEG systems. By combining CNN for spatial feature extraction, SE attention mechanism for selective feature weighting, and BiLSTM for capturing comprehensive temporal information, this method provides a streamlined and highly effective solution for inter-turn short-circuit fault diagnosis.
[Objective] For armature winding inter-turn short circuit fault diagnosis in aerospace generators, this paper proposes a diagnostic method based on convolutional neural network (CNN) with squeeze-excitation (SE) attention mechanism and bidirectional long short-term memory (BiLSTM). It aims to enhance the effectiveness and robustness of armature winding fault diagnosis. [Methods] Firstly, an equivalent analytical model for armature winding inter-turn short circuit fault diagnosis in a doubly salient electromagnetic generator (DSEG) was established, and the vibration signal on the surface of the generator casing was adopted as a characteristic signal of the fault. Theoretical derivations of the expressions for the air gap magnetic flux density and electromagnetic force, which influenced vibration characteristics, were carried out. Secondly, the impact of electromagnetic force on vibration characteristics under various short circuits was analyzed using finite element simulation in Workbench software. Finally, vibration signals were collected and used as actual experimental data to extract relevant fault features. These extracted features were put into the CNN-SE-BiLSTM for efficient fault diagnosis. Among this, the CNN and BiLSTM networks effectively extracted local features and features in time series from vibration signals, while the SE attention mechanism optimized the feature weight distribution by selectively amplifying relevant diagnostic features, significantly enhancing the model’s fault diagnosis capability. [Results] The experimental results showed that the proposed CNN-SE-BiLSTM-based method achieved a diagnostic accuracy of over 99% for inter-turn short circuit faults in armature windings under various working conditions. Moreover, it still exhibited strong diagnostic performance in noisy environments. Compared to traditional diagnostic methods, the proposed method not only demonstrated strong anti-interference ability, high fault recognition accuracy, and fast diagnostic speed under various rotational speeds and load conditions, validating its applicability in aerospace generators with complex operating conditions. [Conclusion] The CNN-SE-BiLSTM diagnostic approach effectively improves the fault diagnosis efficiency and accuracy of DSEG systems. By combining CNN for spatial feature extraction, SE attention mechanism for selective feature weighting, and BiLSTM for capturing comprehensive temporal information, this method provides a streamlined and highly effective solution for inter-turn short-circuit fault diagnosis.
2025, 52(1):36-51.
DOI: 10.12177/emca.2024.150
Abstract:
[Objective] With the increasing depletion of non-renewable resources and the worsening environmental pollution, new energy vehicles have become an important development direction in the automotive industry. Drive motors are the key components that determine the performance of new energy vehicles. [Methods] This paper provides an overview of the current status of drive motor technology for new energy vehicles, introduces the new hybrid excitation technology and its application in drive motors for new energy vehicles, and offers a prospect for the future development of this technology. [Results] First, four existing types of drive motors for new energy vehicles-DC motor, AC asynchronous motor, switched reluctance motor and permanent magnet synchronous motor-were introduced. Based on an analysis of the advantages and disadvantages of the existing drive motors, the hybrid excitation motor, which offers higher performance and compatibility with new energy vehicles, was introduced. Second, the driving principle of the hybrid excitation motor was explained. This motor features both permanent magnet excitation and electromagnetic excitation as two magnetic flux sources, which jointly control and regulate the motor’s air-gap magnetic field. It has advantages such as diverse structural forms, high power density, and a wide speed range, making it highly valuable in fields like wide-range magnetic field regulation for drive motors of new energy vehicles. Third, from the perspective of permanent magnet placement, the two different structures of hybrid excitation motors-rotor permanent magnet type and stator permanent magnet type were discussed in detail. Based on this, the control strategies for hybrid excitation technology were summarized, and its application in new energy vehicles was briefly described. Finally, the future development trends of drive motors for new energy vehicles were analyzed and prospected. [Conclusion] Based on the analysis of the advantages and disadvantages of the four commonly used motors for new energy vehicles and the current status of hybrid excitation technology, it is concluded that hybrid excitation technology has strong application prospects in the field of drive motors for new energy vehicles.
[Objective] With the increasing depletion of non-renewable resources and the worsening environmental pollution, new energy vehicles have become an important development direction in the automotive industry. Drive motors are the key components that determine the performance of new energy vehicles. [Methods] This paper provides an overview of the current status of drive motor technology for new energy vehicles, introduces the new hybrid excitation technology and its application in drive motors for new energy vehicles, and offers a prospect for the future development of this technology. [Results] First, four existing types of drive motors for new energy vehicles-DC motor, AC asynchronous motor, switched reluctance motor and permanent magnet synchronous motor-were introduced. Based on an analysis of the advantages and disadvantages of the existing drive motors, the hybrid excitation motor, which offers higher performance and compatibility with new energy vehicles, was introduced. Second, the driving principle of the hybrid excitation motor was explained. This motor features both permanent magnet excitation and electromagnetic excitation as two magnetic flux sources, which jointly control and regulate the motor’s air-gap magnetic field. It has advantages such as diverse structural forms, high power density, and a wide speed range, making it highly valuable in fields like wide-range magnetic field regulation for drive motors of new energy vehicles. Third, from the perspective of permanent magnet placement, the two different structures of hybrid excitation motors-rotor permanent magnet type and stator permanent magnet type were discussed in detail. Based on this, the control strategies for hybrid excitation technology were summarized, and its application in new energy vehicles was briefly described. Finally, the future development trends of drive motors for new energy vehicles were analyzed and prospected. [Conclusion] Based on the analysis of the advantages and disadvantages of the four commonly used motors for new energy vehicles and the current status of hybrid excitation technology, it is concluded that hybrid excitation technology has strong application prospects in the field of drive motors for new energy vehicles.
2025, 52(1):52-63.
DOI: 10.12177/emca.2024.143
Abstract:
[Objective] The output of renewable energy is characterized by randomness and volatility, which can negatively impact the stable operation of power grids when directly integrated. To improve the grid connection characteristics of renewable energy generation systems, a hybrid energy storage system (HESS) has been introduced. To fully utilize the energy density and power density advantages of the HESS in DC microgrids, this paper proposes a fuzzy logic-based second-order high-pass filter control strategy with variable time constants. [Methods] Firstly, a photovoltaic hybrid energy storage DC microgrid model was constructed. Secondly, the power allocation strategy for the microgrid was designed based on power balance relationships, along with corresponding control strategies for each unit. The photovoltaic generation unit used fuzzy control to rapidly track the maximum power point, improving the energy utilization efficiency of the photovoltaic system. The grid-connected inverter adopted a double closed-loop con
[Objective] The output of renewable energy is characterized by randomness and volatility, which can negatively impact the stable operation of power grids when directly integrated. To improve the grid connection characteristics of renewable energy generation systems, a hybrid energy storage system (HESS) has been introduced. To fully utilize the energy density and power density advantages of the HESS in DC microgrids, this paper proposes a fuzzy logic-based second-order high-pass filter control strategy with variable time constants. [Methods] Firstly, a photovoltaic hybrid energy storage DC microgrid model was constructed. Secondly, the power allocation strategy for the microgrid was designed based on power balance relationships, along with corresponding control strategies for each unit. The photovoltaic generation unit used fuzzy control to rapidly track the maximum power point, improving the energy utilization efficiency of the photovoltaic system. The grid-connected inverter adopted a double closed-loop con
2025, 52(1):64-73.
DOI: 10.12177/emca.2024.146
Abstract:
[Objective] To address the problem that the current detection method in open-circuit fault diagnosis for permanent magnet synchronous motor (PMSM) system needs to set the fault diagnosis threshold empirically when using the normalized current average value to detect and locate the open-circuit fault, this paper proposes an adaptive diagnostic threshold method based on the current vector analysis. [Method] The open-circuit fault of insulated gate bipolar transistor (IGBT) was diagnosed by Park normalized current average. The fault detection variables were obtained from the average values of normalized three-phase stator currents. An adaptive diagnostic threshold was then established using the absolute average value of these currents, which determined the fault diagnosis criterion and enabled fault detection and localization. The Crested Porcupine optimization (CPO) algorithm and the least squares support vector machine (LSSVM) were introduced. The LSSVM served as the basic fault classification model, with fault detection variables used as its fault feature vectors. The CPO algorithm was utilized to optimize the LSSVM classification model. A simulation model of IGBT open-circuit fault diagnosis was built using Matlab/Simulink, and the optimized fault classification model was used to classify and predict the four types of faults studied in this paper. [Results] The simulation results showed that the adaptive diagnostic threshold established using the absolute average values of three-phase stator currents normalized by Park vector modulus after the IGBT open-circuit fault occurred would change adaptively with the location of the fault IGBT in different types of open-circuit faults. The fault classification accuracy of the LSSVM classification model optimized by the CPO algorithm reached 99.21%. [Conclusion] The method proposed in this paper can not only address the shortcomings of the current detection method, but also achieve high fault classification accuracy. It offers significant advantages in IGBT open-circuit fault classification and provides the best fault diagnosis performance.
[Objective] To address the problem that the current detection method in open-circuit fault diagnosis for permanent magnet synchronous motor (PMSM) system needs to set the fault diagnosis threshold empirically when using the normalized current average value to detect and locate the open-circuit fault, this paper proposes an adaptive diagnostic threshold method based on the current vector analysis. [Method] The open-circuit fault of insulated gate bipolar transistor (IGBT) was diagnosed by Park normalized current average. The fault detection variables were obtained from the average values of normalized three-phase stator currents. An adaptive diagnostic threshold was then established using the absolute average value of these currents, which determined the fault diagnosis criterion and enabled fault detection and localization. The Crested Porcupine optimization (CPO) algorithm and the least squares support vector machine (LSSVM) were introduced. The LSSVM served as the basic fault classification model, with fault detection variables used as its fault feature vectors. The CPO algorithm was utilized to optimize the LSSVM classification model. A simulation model of IGBT open-circuit fault diagnosis was built using Matlab/Simulink, and the optimized fault classification model was used to classify and predict the four types of faults studied in this paper. [Results] The simulation results showed that the adaptive diagnostic threshold established using the absolute average values of three-phase stator currents normalized by Park vector modulus after the IGBT open-circuit fault occurred would change adaptively with the location of the fault IGBT in different types of open-circuit faults. The fault classification accuracy of the LSSVM classification model optimized by the CPO algorithm reached 99.21%. [Conclusion] The method proposed in this paper can not only address the shortcomings of the current detection method, but also achieve high fault classification accuracy. It offers significant advantages in IGBT open-circuit fault classification and provides the best fault diagnosis performance.
2025, 52(1):74-83.
DOI: 10.12177/emca.2024.151
Abstract:
[Objective] Permanent magnet shielded motors are widely used in fields that require high sealing and stability. These motors are typically powered by inverters, but the time harmonic currents generated by the inverter can lead to a deterioration in motor performance. Therefore, an in-depth study of the impact of time harmonic current on motor performance is essential for optimizing motor design and ensuring stable operation when powered by inverters. [Methods] A finite element method was employed to model a permanent magnet shielded motor with a rated power of 1.5 kW and a rated speed of 9 000 r/min. This study compared and analyzed the eddy current losses in the permanent magnets, shielded sleeve losses, torque characteristics, efficiency, and power factor of the motor under excitation from 5th and 7th order time harmonic currents with different amplitudes. Different materials for the shielded sleeve were also considered. [Results] Simulation results showed that the injection of harmonic excitation significa
[Objective] Permanent magnet shielded motors are widely used in fields that require high sealing and stability. These motors are typically powered by inverters, but the time harmonic currents generated by the inverter can lead to a deterioration in motor performance. Therefore, an in-depth study of the impact of time harmonic current on motor performance is essential for optimizing motor design and ensuring stable operation when powered by inverters. [Methods] A finite element method was employed to model a permanent magnet shielded motor with a rated power of 1.5 kW and a rated speed of 9 000 r/min. This study compared and analyzed the eddy current losses in the permanent magnets, shielded sleeve losses, torque characteristics, efficiency, and power factor of the motor under excitation from 5th and 7th order time harmonic currents with different amplitudes. Different materials for the shielded sleeve were also considered. [Results] Simulation results showed that the injection of harmonic excitation significa
2025, 52(1):84-93.
DOI: 10.12177/emca.2024.149
Abstract:
[Objective] The flux switching magnetic suspension linear motor (FSMSLM) has a limited heat dissipation space and concentrated heat sources, which can lead to significant temperature rise and adversely affect its operation. To address this, the losses in various motor components are calculated, and a temperature field simulation is performed to design a targeted cooling system that ensures efficient heat dissipation. [Methods] Firstly, the structure and operating principle of the FSMSLM were introduced, followed by the calculation of losses and heat generation rates for each motor component. A mathematical model of the temperature field was established, and the thermal conductivity coefficients of the motor components were obtained using empirical formula. The convective heat transfer coefficients for the relevant surfaces were derived by combining simulation results of the external flow field with the empirical formulas. Finally, finite element simulations were carried out to determine the overall temperatur
[Objective] The flux switching magnetic suspension linear motor (FSMSLM) has a limited heat dissipation space and concentrated heat sources, which can lead to significant temperature rise and adversely affect its operation. To address this, the losses in various motor components are calculated, and a temperature field simulation is performed to design a targeted cooling system that ensures efficient heat dissipation. [Methods] Firstly, the structure and operating principle of the FSMSLM were introduced, followed by the calculation of losses and heat generation rates for each motor component. A mathematical model of the temperature field was established, and the thermal conductivity coefficients of the motor components were obtained using empirical formula. The convective heat transfer coefficients for the relevant surfaces were derived by combining simulation results of the external flow field with the empirical formulas. Finally, finite element simulations were carried out to determine the overall temperatur
2025, 52(1):94-105.
DOI: 10.12177/emca.2024.145
Abstract:
[Objective] To improve the anti-disturbance capability of the speed control system for permanent magnet synchronous motor (PMSM), this paper proposes a predictive speed control (PSC) strategy with fixed switching frequency and disturbance compensation. The speed loop adopts PSC with disturbance compensation, while the current loop adopts proportional integral (PI) control. [Methods] Firstly, the q-axis reference current for realizing the target speed was derived from the mechanical motion equation of the PMSM. To enhance the accuracy of q-axis current tracking, a second-order Taylor expansion of the mechanical motion equation was proposed, which proved to be more precise than first-order forward Eulerian discretization. Secondly, traditional sliding mode observers rely on large switching gains to ensure the observation errors converge to zero within a finite period of time. However, these large switching gains often lead to severe jitter phenomena. Therefore, an improved sliding mode disturbance observer (SMD
[Objective] To improve the anti-disturbance capability of the speed control system for permanent magnet synchronous motor (PMSM), this paper proposes a predictive speed control (PSC) strategy with fixed switching frequency and disturbance compensation. The speed loop adopts PSC with disturbance compensation, while the current loop adopts proportional integral (PI) control. [Methods] Firstly, the q-axis reference current for realizing the target speed was derived from the mechanical motion equation of the PMSM. To enhance the accuracy of q-axis current tracking, a second-order Taylor expansion of the mechanical motion equation was proposed, which proved to be more precise than first-order forward Eulerian discretization. Secondly, traditional sliding mode observers rely on large switching gains to ensure the observation errors converge to zero within a finite period of time. However, these large switching gains often lead to severe jitter phenomena. Therefore, an improved sliding mode disturbance observer (SMD
2025, 52(1):106-114.
DOI: 10.12177/emca.2024.154
Abstract:
[Objective] The flux switching linear motor (FSLM) magnetic levitation system is a nonlinear, strongly coupled, parameter time-varying system. Due to the lack of an intermediate transmission device in the FSLM, combined with external disturbances and the inherent end effects of the linear motor, controlling the magnetic levitation system becomes more challenging. To improve the control performance of the magnetic levitation system, an interval type-2 fuzzy super-twisting sliding mode control (IT-2FSTSMC) strategy is proposed. [Methods] Firstly, the mathematical model of the magnetic levitation system was established according to the structural characteristics and operating principle of FSLM. A nonlinear coordinate transformation was applied to derive an affine nonlinear mathematical model of the FSLM magnetic levitation system. Secondly, a new integral sliding mode surface was designed, which could adaptively regulate the convergence rate of the state variables, thereby improving the system’s response perform
[Objective] The flux switching linear motor (FSLM) magnetic levitation system is a nonlinear, strongly coupled, parameter time-varying system. Due to the lack of an intermediate transmission device in the FSLM, combined with external disturbances and the inherent end effects of the linear motor, controlling the magnetic levitation system becomes more challenging. To improve the control performance of the magnetic levitation system, an interval type-2 fuzzy super-twisting sliding mode control (IT-2FSTSMC) strategy is proposed. [Methods] Firstly, the mathematical model of the magnetic levitation system was established according to the structural characteristics and operating principle of FSLM. A nonlinear coordinate transformation was applied to derive an affine nonlinear mathematical model of the FSLM magnetic levitation system. Secondly, a new integral sliding mode surface was designed, which could adaptively regulate the convergence rate of the state variables, thereby improving the system’s response perform
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沪ICP备16038578号-3
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.
