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Volume 50,Issue 10,2023 Table of Contents
2023, 50(10):1-8.
DOI: 10.12177/emca.2023.122
Abstract:
Synchronous condensers have gradually become the optimal choice for reactive power compensation equipment in DC ultra-high voltage（UHVDC）transmission systems due to their excellent reactive power response capability. During the use of the new synchronous condenser, various faults will inevitably occur, such as winding inter-turn short circuit fault, rotor eccentricity fault and bearing fault. But there is still little references on fault diagnosis technology for synchronous condensers. Therefore, the causes, fault characteristics and diagnosis methods of stator winding inter-turn short circuit fault, rotor winding inter-turn short circuit fault, rotor eccentricity fault, waterway blockage fault and bearing fault of synchronous condenser are summarized, and the characteristics of various fault diagnosis methods are analyzed. The challenges and development trends in the field of fault diagnosis for synchronous condensers are pointed out.
Synchronous condensers have gradually become the optimal choice for reactive power compensation equipment in DC ultra-high voltage（UHVDC）transmission systems due to their excellent reactive power response capability. During the use of the new synchronous condenser, various faults will inevitably occur, such as winding inter-turn short circuit fault, rotor eccentricity fault and bearing fault. But there is still little references on fault diagnosis technology for synchronous condensers. Therefore, the causes, fault characteristics and diagnosis methods of stator winding inter-turn short circuit fault, rotor winding inter-turn short circuit fault, rotor eccentricity fault, waterway blockage fault and bearing fault of synchronous condenser are summarized, and the characteristics of various fault diagnosis methods are analyzed. The challenges and development trends in the field of fault diagnosis for synchronous condensers are pointed out.
2023, 50(10):9-16.
DOI: 10.12177/emca.2023.029
Abstract:
The traditional model predictive control（MPC）of permanent magnet synchronous motors（PMSM）only acts on one voltage vector in a control cycle, so a higher sampling frequency is needed to obtain better control performance. Aiming at the problem, a model predictive control algorithm based on extended vector set is proposed, which can realize the dynamic adjustment of motor control performance and switching loss without changing the sampling frequency. Because there are many voltage vectors in the extended vector set, in order to reduce the calculation, an optimization strategy of voltage vectors based on adjacent vectors is proposed, and the number of candidate voltage vectors in the control set is limited to 11. The simulation and experimental results show that the proposed PMSM model predictive control algorithm based on the extended vector set has the same dynamic performance to the traditional finite set model predictive control algorithm, and the control performance and switching loss can be adjusted by adjusting the number of voltage vectors in the extended vector set without changing the sampling frequency.
The traditional model predictive control（MPC）of permanent magnet synchronous motors（PMSM）only acts on one voltage vector in a control cycle, so a higher sampling frequency is needed to obtain better control performance. Aiming at the problem, a model predictive control algorithm based on extended vector set is proposed, which can realize the dynamic adjustment of motor control performance and switching loss without changing the sampling frequency. Because there are many voltage vectors in the extended vector set, in order to reduce the calculation, an optimization strategy of voltage vectors based on adjacent vectors is proposed, and the number of candidate voltage vectors in the control set is limited to 11. The simulation and experimental results show that the proposed PMSM model predictive control algorithm based on the extended vector set has the same dynamic performance to the traditional finite set model predictive control algorithm, and the control performance and switching loss can be adjusted by adjusting the number of voltage vectors in the extended vector set without changing the sampling frequency.
3 DC Bias Suppression of Transformer in Dual Active Bridge Converter Based on Sigma-Delta AD Sampling
2023, 50(10):17-23.
DOI: 10.12177/emca.2023.111
Abstract:
Dual active bridge (DAB) converters has been widely used because of its high efficiency, high power density and bidirectional energy flow. DAB converters are prone to cause magnetic imbalance due to factors such as circuit parameters and asymmetric driving signals, which would affect the normal and stable operation of the circuit. Therefore, a DC bias detection and control strategy for transformer windings is proposed. This strategy uses the sampling resistance and Δ-Σ modulation, which can convert the current into a 1-bit high-speed data stream, and a sampling resistor is placed at the H-bridge DC end. From this, the average value in the positive and negative half cycles of winding current can be obtained, and the DC component of winding current can be obtained by subtracting it. At the same time, a DC suppression method for DAB is designed, which adjusts the DC component of the H-bridge output voltage by designing a controller to tune the duty cycle of any bridge arm. Finally, the effectiveness of DC bias current detection and control strategies has been verified through Matlab simulation.
Dual active bridge (DAB) converters has been widely used because of its high efficiency, high power density and bidirectional energy flow. DAB converters are prone to cause magnetic imbalance due to factors such as circuit parameters and asymmetric driving signals, which would affect the normal and stable operation of the circuit. Therefore, a DC bias detection and control strategy for transformer windings is proposed. This strategy uses the sampling resistance and Δ-Σ modulation, which can convert the current into a 1-bit high-speed data stream, and a sampling resistor is placed at the H-bridge DC end. From this, the average value in the positive and negative half cycles of winding current can be obtained, and the DC component of winding current can be obtained by subtracting it. At the same time, a DC suppression method for DAB is designed, which adjusts the DC component of the H-bridge output voltage by designing a controller to tune the duty cycle of any bridge arm. Finally, the effectiveness of DC bias current detection and control strategies has been verified through Matlab simulation.
2023, 50(10):24-30.
DOI: 10.12177/emca.2023.118
Abstract:
A speed sliding mode control method based on load torque observer is proposed to solve the problem of poor speed regulation performance of brushless DC motor (BLDC) due to frequent load changes. The sliding mode variable structure control method is used in the speed loop, and the speed sliding mode controller is designed based on the improved exponential reaching law. At the same time, in order to reduce the impact of load torque disturbance on the motor operation state, a load torque observer is designed based on the Luenberger observer, which estimates the actual load torque and feed-forward the output of the observer to the speed sliding mode controller to counteract the impact of load torque disturbance. In order to verify the effectiveness of the proposed scheme, a simulation model is built and analyzed in MATLAB/Simulink simulation environment. The simulation results show that the brushless DC motor system based on load torque observer and speed sliding mode controller has excellent performance. Compared with traditional PI control, the proposed scheme has strong anti-interference ability, short recovery time, and fast speed response. The effectiveness of the proposed scheme is proved.
A speed sliding mode control method based on load torque observer is proposed to solve the problem of poor speed regulation performance of brushless DC motor (BLDC) due to frequent load changes. The sliding mode variable structure control method is used in the speed loop, and the speed sliding mode controller is designed based on the improved exponential reaching law. At the same time, in order to reduce the impact of load torque disturbance on the motor operation state, a load torque observer is designed based on the Luenberger observer, which estimates the actual load torque and feed-forward the output of the observer to the speed sliding mode controller to counteract the impact of load torque disturbance. In order to verify the effectiveness of the proposed scheme, a simulation model is built and analyzed in MATLAB/Simulink simulation environment. The simulation results show that the brushless DC motor system based on load torque observer and speed sliding mode controller has excellent performance. Compared with traditional PI control, the proposed scheme has strong anti-interference ability, short recovery time, and fast speed response. The effectiveness of the proposed scheme is proved.
2023, 50(10):31-38.
DOI: 10.12177/emca.2023.125
Abstract:
For the access of distributed power sources and the effective management of electric energy, energy routers with highly flexible power control and information interaction functions were applied to low-voltage distribution networks to achieve integrated operation of source-network-load-storage, thereby improving load regulation capabilities and new energy consumption levels, and ensuring the stable operation of the power system. Therefore, A household energy router for low-voltage distribution network application was designed, and its topology and power coordination control strategy were studied based on the characteristics of each port application object to provide a reliable energy management strategy for power production and consumption. Finally, a simulation model based on MATLAB/Simulink was established to verify its power coordination control strategy. The simulation results show that the proposed multi-port energy router power coordination control strategy can achieve power reciprocity and system power balance control between different ports under various operating modes, and has high flexibility, stability and reliability in energy management.
For the access of distributed power sources and the effective management of electric energy, energy routers with highly flexible power control and information interaction functions were applied to low-voltage distribution networks to achieve integrated operation of source-network-load-storage, thereby improving load regulation capabilities and new energy consumption levels, and ensuring the stable operation of the power system. Therefore, A household energy router for low-voltage distribution network application was designed, and its topology and power coordination control strategy were studied based on the characteristics of each port application object to provide a reliable energy management strategy for power production and consumption. Finally, a simulation model based on MATLAB/Simulink was established to verify its power coordination control strategy. The simulation results show that the proposed multi-port energy router power coordination control strategy can achieve power reciprocity and system power balance control between different ports under various operating modes, and has high flexibility, stability and reliability in energy management.
2023, 50(10):39-45.
DOI: 10.12177/emca.2023.119
Abstract:
Single-phase voltage drop in the grid will cause the unbalanced output current and the large impulse current of doubly-fed induction generator (DFIG). The traditional virtual synchronous generator (VSG) control strategy is modeled on the basis of ideal voltage, which cannot cope with the coupling of negative and positive sequence component of voltage. It will directly affect the stability of current loop and pulse width modulation signal output. Aiming at this problem, a virtual synchronous control strategy based on single-phase Park transformation in decoupled dual synchronous coordinate system (DDSRF-VSG-Spark) is proposed. Firstly, the positive and negative sequence component are decoupled by decoupling the double synchronous reference frame. Then the single-phase Park transformation technology is used to realize the stable output of pulse width modulation signal and current. Finally, through simulation comparison, it is verified that DDSRF-VSG-Spark can ensure the stable operation of the system during single-phase grid voltage drop.
Single-phase voltage drop in the grid will cause the unbalanced output current and the large impulse current of doubly-fed induction generator (DFIG). The traditional virtual synchronous generator (VSG) control strategy is modeled on the basis of ideal voltage, which cannot cope with the coupling of negative and positive sequence component of voltage. It will directly affect the stability of current loop and pulse width modulation signal output. Aiming at this problem, a virtual synchronous control strategy based on single-phase Park transformation in decoupled dual synchronous coordinate system (DDSRF-VSG-Spark) is proposed. Firstly, the positive and negative sequence component are decoupled by decoupling the double synchronous reference frame. Then the single-phase Park transformation technology is used to realize the stable output of pulse width modulation signal and current. Finally, through simulation comparison, it is verified that DDSRF-VSG-Spark can ensure the stable operation of the system during single-phase grid voltage drop.
2023, 50(10):46-53.
DOI: 10.12177/emca.2023.115
Abstract:
In order to improve the tracking performance of the speed regulation servo system, a self-disturbance rejection control strategy of the speed regulation servo system based on the LuGre model is proposed. Using the LuGre friction model to identify the frictional disturbance, and feed-forward compensation, adding the first-order self-disturbance rejection controller to the speed loop and the current loop respectively, the remaining disturbance is estimated and compensated in real time. ADRC makes up for the non-absolute perfection of the friction model, and the LuGre model also relieves the computational pressure of ADRC, complements each other and improves performance. The simulation results show that the proposed control strategy has fast response speed, short adjustment time and low overshoot, which improves the control speed and accuracy of the system.
In order to improve the tracking performance of the speed regulation servo system, a self-disturbance rejection control strategy of the speed regulation servo system based on the LuGre model is proposed. Using the LuGre friction model to identify the frictional disturbance, and feed-forward compensation, adding the first-order self-disturbance rejection controller to the speed loop and the current loop respectively, the remaining disturbance is estimated and compensated in real time. ADRC makes up for the non-absolute perfection of the friction model, and the LuGre model also relieves the computational pressure of ADRC, complements each other and improves performance. The simulation results show that the proposed control strategy has fast response speed, short adjustment time and low overshoot, which improves the control speed and accuracy of the system.
2023, 50(10):54-61.
DOI: 10.12177/emca.2023.117
Abstract:
The temperature rise problem of magnetic suspension linear motor with transverse magnetic field, electric excitation and flux switching is studied, and the cooling system is designed to ensure the normal operation of the motor. The structure and operation principle of the motor are analyzed, and the three-dimensional steady-state temperature field mathematical model are established, and the boundary condition equation are derived. Considering the heat exchange of each part of the motor, the thermal conductivity of each material and the convective heat transfer coefficient of different parts of the motor are determined. The copper loss and iron loss of the motor are calculated by finite element method, and the corresponding heat of formation is obtained. The three-dimensional finite element method is used to calculate the temperature field under different working conditions of the motor, and the temperature field distribution of the motor core, armature and excitation winding is obtained. Finally, the cooling system is designed, and the temperature distribution under natural air cooling and forced water cooling conditions is compared, which proves the feasibility and rationality of the cooling system.
The temperature rise problem of magnetic suspension linear motor with transverse magnetic field, electric excitation and flux switching is studied, and the cooling system is designed to ensure the normal operation of the motor. The structure and operation principle of the motor are analyzed, and the three-dimensional steady-state temperature field mathematical model are established, and the boundary condition equation are derived. Considering the heat exchange of each part of the motor, the thermal conductivity of each material and the convective heat transfer coefficient of different parts of the motor are determined. The copper loss and iron loss of the motor are calculated by finite element method, and the corresponding heat of formation is obtained. The three-dimensional finite element method is used to calculate the temperature field under different working conditions of the motor, and the temperature field distribution of the motor core, armature and excitation winding is obtained. Finally, the cooling system is designed, and the temperature distribution under natural air cooling and forced water cooling conditions is compared, which proves the feasibility and rationality of the cooling system.
2023, 50(10):62-69.
DOI: 10.12177/emca.2023.121
Abstract:
In order to further improve the speed control performance of active disturbance rejection controller (ADRC) for permanent magnet synchronous motor (PMSM), and simplify the complexity of controller parameter setting, a compound ADRC control strategy is proposed. Firstly, the sliding mode ADRC with fuzzy parameter tuning is used in the velocity loop, and the tuning methods of the main parameters is analyzed. Secondly, a sliding mode torque observer is designed to estimate the real-time load torque. Finally, the current loop is designed, and the finite set model predictive control (FCS-MPC) is used to optimize 8 kinds of switching sequences of three-phase two-level voltage source inverter and suppress torque pulsation. The simulation results show that the composite control strategy can effectively improve the control performance of the permanent magnet synchronous motor ADRC, enhance the anti-disturbance ability and robustness of the system, and the control performance is better than the traditional ADRC control and PI control.
In order to further improve the speed control performance of active disturbance rejection controller (ADRC) for permanent magnet synchronous motor (PMSM), and simplify the complexity of controller parameter setting, a compound ADRC control strategy is proposed. Firstly, the sliding mode ADRC with fuzzy parameter tuning is used in the velocity loop, and the tuning methods of the main parameters is analyzed. Secondly, a sliding mode torque observer is designed to estimate the real-time load torque. Finally, the current loop is designed, and the finite set model predictive control (FCS-MPC) is used to optimize 8 kinds of switching sequences of three-phase two-level voltage source inverter and suppress torque pulsation. The simulation results show that the composite control strategy can effectively improve the control performance of the permanent magnet synchronous motor ADRC, enhance the anti-disturbance ability and robustness of the system, and the control performance is better than the traditional ADRC control and PI control.
2023, 50(10):70-75.
DOI: 10.12177/emca.2023.114
Abstract:
In order to improve the accuracy and stability of sensorless control system of surface-mounted permanent magnet synchronous motor (SPMSM), a fast super twisting sliding mode model reference adaptive system observer (FSTA-SM-MRASO) with linear correction is proposed to solve the problem of insufficient robustness of traditional PI control. The proposed observer combines the fast super twisting algorithm (FSTA) with the model reference adaptive system (MRAS) observer to construct the sensorless vector control system of SPMSM based on FSTA-SM-MRASO. The effectiveness of the proposed strategy is verified by simulation on the MATLAB/Simulink platform.
In order to improve the accuracy and stability of sensorless control system of surface-mounted permanent magnet synchronous motor (SPMSM), a fast super twisting sliding mode model reference adaptive system observer (FSTA-SM-MRASO) with linear correction is proposed to solve the problem of insufficient robustness of traditional PI control. The proposed observer combines the fast super twisting algorithm (FSTA) with the model reference adaptive system (MRAS) observer to construct the sensorless vector control system of SPMSM based on FSTA-SM-MRASO. The effectiveness of the proposed strategy is verified by simulation on the MATLAB/Simulink platform.
2023, 50(10):76-80.
DOI: 10.12177/emca.2023.030
Abstract:
In order to monitor and identify transformer winding looseness fault more effectively, a chaotic feature analysis method for transformer winding looseness fault is proposed. Firstly, according to the chaotic dynamic characteristics of vibration signals, mutual information method and G-P algorithm are used to determine the delay time and embedding dimension respectively to reconstruct the phase space of transformer vibration signals; Secondly, the chaotic characteristic of transformer vibration signal is proved by judging whether the maximum Lyapunov exponent is positive. On this basis, the influence of different degrees of winding looseness fault on the change of phase space trajectory is analyzed; Finally, correlation dimension, Kolmogorov entropy and maximum Lyapunov exponent are used as a set of chaotic features to quantify the chaotic characteristics of vibration signals before and after the happening of transformer winding looseness fault. The results show that the maximum Lyapunov exponents of transformer vibration signals are all greater than 0, which proves that they have chaotic characteristics, and the obtained chaotic characteristics can effectively reflect the looseness fault of transformer windings. The research results provide a theoretical basis for monitoring the loosing state of transformer windings.
In order to monitor and identify transformer winding looseness fault more effectively, a chaotic feature analysis method for transformer winding looseness fault is proposed. Firstly, according to the chaotic dynamic characteristics of vibration signals, mutual information method and G-P algorithm are used to determine the delay time and embedding dimension respectively to reconstruct the phase space of transformer vibration signals; Secondly, the chaotic characteristic of transformer vibration signal is proved by judging whether the maximum Lyapunov exponent is positive. On this basis, the influence of different degrees of winding looseness fault on the change of phase space trajectory is analyzed; Finally, correlation dimension, Kolmogorov entropy and maximum Lyapunov exponent are used as a set of chaotic features to quantify the chaotic characteristics of vibration signals before and after the happening of transformer winding looseness fault. The results show that the maximum Lyapunov exponents of transformer vibration signals are all greater than 0, which proves that they have chaotic characteristics, and the obtained chaotic characteristics can effectively reflect the looseness fault of transformer windings. The research results provide a theoretical basis for monitoring the loosing state of transformer windings.
2023, 50(10):81-90.
DOI: 10.12177/emca.2023.113
Abstract:
A transformer winding core mechanical fault diagnosis method based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) multi-scale fuzzy entropy (MFE) and multi-verse optimizer algorithm optimized kernel based extreme learning machine (MVO-KELM) is proposed for the problem of insufficient accuracy of transformer winding core mechanical fault diagnosis. Firstly, to avoid the generation of spurious modal components, the original transformer vibration signal is decomposed using a modified ICEEMDAN. Secondly, the modal component with the highest correlation is selected using the Pearson correlation coefficient method and its MFE value is calculated. Then, the MFE values are used as feature quantities to construct feature datasets, and the kernel parameters and regularization coefficients of KELM are optimized using MVO. Finally, the feature dataset is input into the constructed MVO-KELM model for classification and identification to achieve the goal of high accuracy diagnosis. The experimental results prove that the proposed approach possesses excellent diagnostic accuracy and stability, and can accurately diagnose transformer winding core loosening faults of different degrees with a diagnostic accuracy of more than 99%, which may supply the necessary guidance for the development of transformer field maintenance strategy.
A transformer winding core mechanical fault diagnosis method based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) multi-scale fuzzy entropy (MFE) and multi-verse optimizer algorithm optimized kernel based extreme learning machine (MVO-KELM) is proposed for the problem of insufficient accuracy of transformer winding core mechanical fault diagnosis. Firstly, to avoid the generation of spurious modal components, the original transformer vibration signal is decomposed using a modified ICEEMDAN. Secondly, the modal component with the highest correlation is selected using the Pearson correlation coefficient method and its MFE value is calculated. Then, the MFE values are used as feature quantities to construct feature datasets, and the kernel parameters and regularization coefficients of KELM are optimized using MVO. Finally, the feature dataset is input into the constructed MVO-KELM model for classification and identification to achieve the goal of high accuracy diagnosis. The experimental results prove that the proposed approach possesses excellent diagnostic accuracy and stability, and can accurately diagnose transformer winding core loosening faults of different degrees with a diagnostic accuracy of more than 99%, which may supply the necessary guidance for the development of transformer field maintenance strategy.
2023, 50(10):91-99.
DOI: 10.12177/emca.2023.123
Abstract:
The traditional method of motor current signal characteristic analysis (MCSA) is commonly used in the fault diagnosis of rotor broken bar and eccentricity of asynchronous motor based on signal analysis. Because of low sampling frequency, strong base bourbon effect and other factors will lead to the drowning of characteristic frequency components, difficult to quantify the fault degree and other problems. Therefore, a fault diagnosis method of asynchronous motor based on adaptive particle swarm optimization sequential support vector machine (APSO-SSVM) is proposed. Firstly, empirical wavelet transform (EWT) is used to filter the original signal; then, the feature extraction of the filtered signal is carried out and input into the SSVM diagnosis model; finally, the APSO algorithm is used to determine the optimal hyperparameters of the SVM model in each order, so as to achieve accurate fault diagnosis of the number of broken rotor bars.
The traditional method of motor current signal characteristic analysis (MCSA) is commonly used in the fault diagnosis of rotor broken bar and eccentricity of asynchronous motor based on signal analysis. Because of low sampling frequency, strong base bourbon effect and other factors will lead to the drowning of characteristic frequency components, difficult to quantify the fault degree and other problems. Therefore, a fault diagnosis method of asynchronous motor based on adaptive particle swarm optimization sequential support vector machine (APSO-SSVM) is proposed. Firstly, empirical wavelet transform (EWT) is used to filter the original signal; then, the feature extraction of the filtered signal is carried out and input into the SSVM diagnosis model; finally, the APSO algorithm is used to determine the optimal hyperparameters of the SVM model in each order, so as to achieve accurate fault diagnosis of the number of broken rotor bars.
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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.
