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Volume 50,Issue 9,2023 Table of Contents
2023, 50(9):1-7.
DOI: 10.12177/emca.2023.098
Abstract:
With the continuous development of modern multielectric aircraft technology, higher requirements are put forward for the aviation power supply system. According to the requirements of high reliability, high power density and large power supply capacity of aviation starter generator, a high speed doubly salient axial electromagnetic motor (DSAEM) is proposed. The basic structure and working principle of the motor are described, the mathematical model of the motor is established and rerified by finite element simulation. The magnetic field, inductance, noload characteristics and load characteristics of the motor were analyzed in detail. The results show that DSAEM has a completely symmetrical threephase magnetic linkage which can output a more stable voltage. The motor winding has high space utilization rate, high power density and high efficiency, and can meet the basic requirements of aviation power supply.
With the continuous development of modern multielectric aircraft technology, higher requirements are put forward for the aviation power supply system. According to the requirements of high reliability, high power density and large power supply capacity of aviation starter generator, a high speed doubly salient axial electromagnetic motor (DSAEM) is proposed. The basic structure and working principle of the motor are described, the mathematical model of the motor is established and rerified by finite element simulation. The magnetic field, inductance, noload characteristics and load characteristics of the motor were analyzed in detail. The results show that DSAEM has a completely symmetrical threephase magnetic linkage which can output a more stable voltage. The motor winding has high space utilization rate, high power density and high efficiency, and can meet the basic requirements of aviation power supply.
2023, 50(9):8-13.
DOI: 10.12177/emca.2023.101
Abstract:
Aiming at the problems of weak heat dissipation, low torque density and high winding temperature of permanent magnet outer rotor electric drum motor for belt transportation, a water cooling system based on 710 kW electric drum is designed. In the system, a three-dimensional field solution model by fluid-structure coupling method is established, and the solution calculation is performed. The influence of water channel configuration, water flow, outer diameter of water jacket, wall thickness, number of water channel and height on temperature rise is analyzed. By simulation analysis and temperature rise test, it is rerified that the designed water cooling system is beneficial to improve the heat dissipation capacity of the electric roller, which provides a reference for further improving the torque density of the electric roller.
Aiming at the problems of weak heat dissipation, low torque density and high winding temperature of permanent magnet outer rotor electric drum motor for belt transportation, a water cooling system based on 710 kW electric drum is designed. In the system, a three-dimensional field solution model by fluid-structure coupling method is established, and the solution calculation is performed. The influence of water channel configuration, water flow, outer diameter of water jacket, wall thickness, number of water channel and height on temperature rise is analyzed. By simulation analysis and temperature rise test, it is rerified that the designed water cooling system is beneficial to improve the heat dissipation capacity of the electric roller, which provides a reference for further improving the torque density of the electric roller.
2023, 50(9):14-19.
DOI: 10.12177/emca.2023.109
Abstract:
Traditional high-speed maglev trains adopots a bilateral parallel power supply mode, which requires three converters for each of the upstream and downstream lines. Although this power supply method can reduce losses on the feeder cables and increase the reliability of the power supply system, the output current generated is limited by the converter capacity itself, resulting in limited tractive effort and speed capability. In order to solve the above problems, a high-speed maglev bilateral series power supply method was proposed to improve traction and speed. Without changing the output capacity and insulation of the conventional converter, the motor head and tail were connected to the bilateral converter separately, and the phase angle of the output voltage was changed to achieve the traction and speed capacity enhancement of maglev trains. Finally, the traction power supply system was established in Simulink, and it was verified that the voltage of the bilateral series power supply is smaller than that of the bilateral parallel power supply at the maximum speed, which is more conducive to the speed increase.
Traditional high-speed maglev trains adopots a bilateral parallel power supply mode, which requires three converters for each of the upstream and downstream lines. Although this power supply method can reduce losses on the feeder cables and increase the reliability of the power supply system, the output current generated is limited by the converter capacity itself, resulting in limited tractive effort and speed capability. In order to solve the above problems, a high-speed maglev bilateral series power supply method was proposed to improve traction and speed. Without changing the output capacity and insulation of the conventional converter, the motor head and tail were connected to the bilateral converter separately, and the phase angle of the output voltage was changed to achieve the traction and speed capacity enhancement of maglev trains. Finally, the traction power supply system was established in Simulink, and it was verified that the voltage of the bilateral series power supply is smaller than that of the bilateral parallel power supply at the maximum speed, which is more conducive to the speed increase.
2023, 50(9):20-27.
DOI: 10.12177/emca.2023.110
Abstract:
Fitting model function with load inertia, viscous damping coefficient, load gravity torque and load initial position angle as parameters to be identified is established through the motor kinematics equation. The four parameters are fitted by the nonlinear regression method based on the model function, and the noninertia load torque is obtained. Adding the load torque to the current loop in the classical motor PI control method as the feed forward compensation to realize the compensation of time-varying load torque. The simulation results show that this method can enable the control system to respond quickly to input speed commands, and avoid the appearance of large speed error.
Fitting model function with load inertia, viscous damping coefficient, load gravity torque and load initial position angle as parameters to be identified is established through the motor kinematics equation. The four parameters are fitted by the nonlinear regression method based on the model function, and the noninertia load torque is obtained. Adding the load torque to the current loop in the classical motor PI control method as the feed forward compensation to realize the compensation of time-varying load torque. The simulation results show that this method can enable the control system to respond quickly to input speed commands, and avoid the appearance of large speed error.
2023, 50(9):28-34.
DOI: 10.12177/emca.2023.105
Abstract:
In order to improve the dynamic response speed and robustness of permanent magnet linear synchronous motor (PMLSM) control system, a fixed-time integral sliding mode control (DFISMC) method based on disturbance estimation compensation was proposed. Firstly, based on the integral sliding mode surface, a sliding mode control algorithm with fixed-time was introduced to ensure that the system can reach the equilibrium point within a fixed-time. Secondly, a control rate gain function f(s) was designed to adjust dynamically with the state of the system, which further accelerates the convergence rate. Finally, an adaptive superspiral disturbance observer was designed to estimate the internal and external mismatched disturbances, and the observed values were introduced into the control rate by feedforward compensation, which enhances the antiinterference ability of the system. The simulation results show that the DFISMC method not only guarantees the global robustness of the system, but also improves the tracking accuracy and response speed of the system.
In order to improve the dynamic response speed and robustness of permanent magnet linear synchronous motor (PMLSM) control system, a fixed-time integral sliding mode control (DFISMC) method based on disturbance estimation compensation was proposed. Firstly, based on the integral sliding mode surface, a sliding mode control algorithm with fixed-time was introduced to ensure that the system can reach the equilibrium point within a fixed-time. Secondly, a control rate gain function f(s) was designed to adjust dynamically with the state of the system, which further accelerates the convergence rate. Finally, an adaptive superspiral disturbance observer was designed to estimate the internal and external mismatched disturbances, and the observed values were introduced into the control rate by feedforward compensation, which enhances the antiinterference ability of the system. The simulation results show that the DFISMC method not only guarantees the global robustness of the system, but also improves the tracking accuracy and response speed of the system.
2023, 50(9):35-41.
DOI: 10.12177/emca.2023.107
Abstract:
Aiming at the synchronous control problem of dual-motor servo systems, a discrete tracking and synchronous control scheme is designed based on command filtered. By establishing discrete dynamic equations for a dual-motor system, the computational difficulty in backstepping design process of command filtered is reduced, and virtual control signals can also be processed simultaneously. Define compensation signals in the controller design to eliminate errors and improve tracking performance. The results shows that neural networks can handle nonlinear disturbances caused by shaft torque or backlash during motor operation efficiently. Finally, the stability of the control method was analyzed by Lyapunov, the results shows that the dual-motor servo system had good tracking and synchronous performance under the action of the controller.
Aiming at the synchronous control problem of dual-motor servo systems, a discrete tracking and synchronous control scheme is designed based on command filtered. By establishing discrete dynamic equations for a dual-motor system, the computational difficulty in backstepping design process of command filtered is reduced, and virtual control signals can also be processed simultaneously. Define compensation signals in the controller design to eliminate errors and improve tracking performance. The results shows that neural networks can handle nonlinear disturbances caused by shaft torque or backlash during motor operation efficiently. Finally, the stability of the control method was analyzed by Lyapunov, the results shows that the dual-motor servo system had good tracking and synchronous performance under the action of the controller.
7 Diagnosis Method of Turns of Permanent Magnet Synchronous Motor for Inter-Turn Short-Circuit Fault
2023, 50(9):42-48.
DOI: 10.12177/emca.2023.099
Abstract:
For the problem that the number of faulty turns is difficult to diagnose when an inter-turn short-circuit fault occurs in a permanent magnet synchronous motor (PMSM), an accurate diagnosis method for the number of faulty turns of a faulty motor offline in an offline state was proposed. Firstly, the conditions that the motor model under the inter-turn short-circuit fault of the winding and under the normal state were analyzed, the excitation source was connected to the simulation circuit, the amplitude and phase of the faulted phase current were extracted, and the fault diagnosis indicator was established by combining the excitation source value、circuit parameters and current. The simulation results illustrate that the method could accurately calculate the number of winding turns in the range from the fault-free state to the full-winding fault state. The method can be directly implemented, without installing complex equipment and additional sensors on the target motor, and has utility value in the maintenance of permanent magnet synchronous motors.
For the problem that the number of faulty turns is difficult to diagnose when an inter-turn short-circuit fault occurs in a permanent magnet synchronous motor (PMSM), an accurate diagnosis method for the number of faulty turns of a faulty motor offline in an offline state was proposed. Firstly, the conditions that the motor model under the inter-turn short-circuit fault of the winding and under the normal state were analyzed, the excitation source was connected to the simulation circuit, the amplitude and phase of the faulted phase current were extracted, and the fault diagnosis indicator was established by combining the excitation source value、circuit parameters and current. The simulation results illustrate that the method could accurately calculate the number of winding turns in the range from the fault-free state to the full-winding fault state. The method can be directly implemented, without installing complex equipment and additional sensors on the target motor, and has utility value in the maintenance of permanent magnet synchronous motors.
2023, 50(9):49-56.
DOI: 10.12177/emca.2023.106
Abstract:
A transformer internal mechanical fault diagnosis method based on time-varying filtered empirical modal decomposition (TVFEMD) and sparrow search algorithm optimized least squares support vector machine (SSA-LSSVM) is proposed to identify the internal latent mechanical faults of transformers accurately and effectively. Firstly, the vibration signals from transformers with iron cores in different loose states are collected. Secondly, the vibration signals are decomposed by the empirical mode decomposition (EMD) which was improved by time-varying filtered to obtain multiple intrinsic mode function (IMF); i.e. modal components (IMFs). Thirdly, the correlation coefficient method was used to calculate the correlation between the IMFs component and the original vibration signal, and the sample entropy of the IMF component with the highest correlation is calculated to construct the feature vector set. Finally, with the highest diagnostic accuracy as the objective function, SSA is used to optimize the regularization parameters and kernel function parameters of LSSVM, the SSA-LSSVM diagnostic model is built. The vector set is diagnosed and identified by using the diagnosis model, and the diagnosis of latent mechanical faults inside the transformer core is realized. The experimental results show that the proposed method can effectively identify the latent mechanical faults inside the transformers, and the identification accuracy reaches more than 98%, which is more than 5% higher than the identification accuracy of the comparison algorithm, achieving the diagnosis effect of high identification accuracy.
A transformer internal mechanical fault diagnosis method based on time-varying filtered empirical modal decomposition (TVFEMD) and sparrow search algorithm optimized least squares support vector machine (SSA-LSSVM) is proposed to identify the internal latent mechanical faults of transformers accurately and effectively. Firstly, the vibration signals from transformers with iron cores in different loose states are collected. Secondly, the vibration signals are decomposed by the empirical mode decomposition (EMD) which was improved by time-varying filtered to obtain multiple intrinsic mode function (IMF); i.e. modal components (IMFs). Thirdly, the correlation coefficient method was used to calculate the correlation between the IMFs component and the original vibration signal, and the sample entropy of the IMF component with the highest correlation is calculated to construct the feature vector set. Finally, with the highest diagnostic accuracy as the objective function, SSA is used to optimize the regularization parameters and kernel function parameters of LSSVM, the SSA-LSSVM diagnostic model is built. The vector set is diagnosed and identified by using the diagnosis model, and the diagnosis of latent mechanical faults inside the transformer core is realized. The experimental results show that the proposed method can effectively identify the latent mechanical faults inside the transformers, and the identification accuracy reaches more than 98%, which is more than 5% higher than the identification accuracy of the comparison algorithm, achieving the diagnosis effect of high identification accuracy.
2023, 50(9):57-62.
DOI: 10.12177/emca.2023.022
Abstract:
In order to further study the large amount of fault information contained in transformer vibration signals, a fault diagnosis method for transformer winding looseness based on S-transform singular value decomposition (ST-SVD) and support vector machine optimized by whale optimization algorithm (WOA-SVM) model was proposed. Firstly, based on the transformer fault simulation experiment platform, the vibration signals of transformer windings in different states were collected. Secondly, the time-frequency matrix of the transformer vibration signal was obtained by S-transformation. Thirdly, calculating the amplitude matrix corresponding to the time-frequency matrix for SVD, and defining the feature vector. Finally, the parameters of SVM model were optimized by whale optimization algorithm, and the fault diagnosis was completed by inputting feature vectors. The experimental results show that the accuracy of fault identification of the proposed method is higher than that of the traditional method model, and it is suitable for the diagnosis of transformer winding looseness fault.
In order to further study the large amount of fault information contained in transformer vibration signals, a fault diagnosis method for transformer winding looseness based on S-transform singular value decomposition (ST-SVD) and support vector machine optimized by whale optimization algorithm (WOA-SVM) model was proposed. Firstly, based on the transformer fault simulation experiment platform, the vibration signals of transformer windings in different states were collected. Secondly, the time-frequency matrix of the transformer vibration signal was obtained by S-transformation. Thirdly, calculating the amplitude matrix corresponding to the time-frequency matrix for SVD, and defining the feature vector. Finally, the parameters of SVM model were optimized by whale optimization algorithm, and the fault diagnosis was completed by inputting feature vectors. The experimental results show that the accuracy of fault identification of the proposed method is higher than that of the traditional method model, and it is suitable for the diagnosis of transformer winding looseness fault.
2023, 50(9):63-69.
DOI: 10.12177/emca.2023.102
Abstract:
In order to improve the accuracy of motor bearing fault diagnosis, and aiming at the problem of unstable vibration signals and the difficulty in extracting fault feature of motor bearing fault, a motor bearing fault diagnosis method based on the combination of variational mode decomposition (VMD) energy entropy and convolutional neural network (CNN) is proposed. In order to reflect the characteristics of faults more accurately, a three-dimensional energy entropy extraction method is adopted to divide the bearing faults into three categories, namely, inner ring wear, outer ring wear and cage fracture. Then each category is subdirided into three cases with loads of 0%, 25% and 50%, for a total of 9 cases. Firstly, the VMD method is used to decompose the fault signal into components of the intrinsic mode function (IMF) and the energy entropy of each dimension IMF is extracted to form the feature vector. The results show that the method can effectively improve the accuracy of fault diagnosis.
In order to improve the accuracy of motor bearing fault diagnosis, and aiming at the problem of unstable vibration signals and the difficulty in extracting fault feature of motor bearing fault, a motor bearing fault diagnosis method based on the combination of variational mode decomposition (VMD) energy entropy and convolutional neural network (CNN) is proposed. In order to reflect the characteristics of faults more accurately, a three-dimensional energy entropy extraction method is adopted to divide the bearing faults into three categories, namely, inner ring wear, outer ring wear and cage fracture. Then each category is subdirided into three cases with loads of 0%, 25% and 50%, for a total of 9 cases. Firstly, the VMD method is used to decompose the fault signal into components of the intrinsic mode function (IMF) and the energy entropy of each dimension IMF is extracted to form the feature vector. The results show that the method can effectively improve the accuracy of fault diagnosis.
2023, 50(9):70-77.
DOI: 10.12177/emca.2023.103
Abstract:
The failure of the receiving-end grid in the voltage source converter (VSC) based high voltage direct current (HVDC) system of offshore wind power not only affects the operation status of the AC/DC side system of the receivingend converter station, but also hinders the normal operation of the sendingend converter station and offshore wind turbines in severe cases. In order to solve this problem, the propagation mechanism of asymmetric faults in the receiving-eng grid of offshore wind power transmission system through VSC-HVDC was analyzed, and a negative sequence component suppression strategy based on Lyapunov function method was proposed. Firstly, the topology structure of the offshore wind turbine transmission system through VSC-HVDC was established, and the propagation mechanism of asymmetric faults in the receiving-end grid was analyzed. Secondly, based on the mathematical model of the receiving-end converter station, a negative sequence switching function that satisfies the global stability of the Lyapunov function is derived, and the coefficients of the switching function are solred. Thus, the corresponding Lyapunov function controller is further designed. Finally, the proposed strategy was compared with traditional PI control based on MATLAB/Simulink software simulation to verify its correctness and effectiveness.
The failure of the receiving-end grid in the voltage source converter (VSC) based high voltage direct current (HVDC) system of offshore wind power not only affects the operation status of the AC/DC side system of the receivingend converter station, but also hinders the normal operation of the sendingend converter station and offshore wind turbines in severe cases. In order to solve this problem, the propagation mechanism of asymmetric faults in the receiving-eng grid of offshore wind power transmission system through VSC-HVDC was analyzed, and a negative sequence component suppression strategy based on Lyapunov function method was proposed. Firstly, the topology structure of the offshore wind turbine transmission system through VSC-HVDC was established, and the propagation mechanism of asymmetric faults in the receiving-end grid was analyzed. Secondly, based on the mathematical model of the receiving-end converter station, a negative sequence switching function that satisfies the global stability of the Lyapunov function is derived, and the coefficients of the switching function are solred. Thus, the corresponding Lyapunov function controller is further designed. Finally, the proposed strategy was compared with traditional PI control based on MATLAB/Simulink software simulation to verify its correctness and effectiveness.
2023, 50(9):78-84.
DOI: 10.12177/emca.2023.097
Abstract:
Photovoltaic inverter system is based on the traditional droop control method to achieve the average distribution of active power, which will cause the maximum power restriction and waste of photovoltaic units. Therefore, in order to improve the optimal utilization rate of photovoltaic unit output energy, an improved droop control strategy for photovoltaic inverter is proposed. The strategy is based on the variable step perturbation observation method to track and control the maximum power of photovoltaic panels. The maximum output power constraint will generate the droop active power compensation, which will be superimposed to the correction of the frequency reference value corresponding to the traditional droop control active power, and keep the voltage amplitude corresponding to the reactive power unchanged, so as to achieve the maximum power output of photovoltaic units in the parallel system. The maximum power constrained droop control strategy of photovoltaic inverter is simulated and verified by PSIM power electronics simulation software. The simulation results show that the variable step disturbance observation method and the improved droop control strategy are effective and feasible in practical application.
Photovoltaic inverter system is based on the traditional droop control method to achieve the average distribution of active power, which will cause the maximum power restriction and waste of photovoltaic units. Therefore, in order to improve the optimal utilization rate of photovoltaic unit output energy, an improved droop control strategy for photovoltaic inverter is proposed. The strategy is based on the variable step perturbation observation method to track and control the maximum power of photovoltaic panels. The maximum output power constraint will generate the droop active power compensation, which will be superimposed to the correction of the frequency reference value corresponding to the traditional droop control active power, and keep the voltage amplitude corresponding to the reactive power unchanged, so as to achieve the maximum power output of photovoltaic units in the parallel system. The maximum power constrained droop control strategy of photovoltaic inverter is simulated and verified by PSIM power electronics simulation software. The simulation results show that the variable step disturbance observation method and the improved droop control strategy are effective and feasible in practical application.
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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.
