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Volume 49,Issue 6,2022 Table of Contents
2022, 49(6):1-8.
DOI: 10.12177/emca.2022.023
Abstract:
In order to improve the speed tracking accuracy and robustness of permanent magnet synchronous motor (PMSM) control system and suppress periodic torque ripple, a single-loop control strategy of PMSM based on integral sliding mode control and iterative learning method is proposed. The single-loop sliding mode control strategy is adopted in the controller to replace the traditional rotational speed and current cascade control, so that the control system structure is simplified and the dynamic response of the system is improved. The iterative learning control is introduced to effectively suppress the torque ripple caused by current harmonics and improve the steady-state control accuracy of rotational speed. In addition, aiming at the external load disturbances and model and parameter uncertainties of the system, a dual disturbance observer is designed to estimate the system disturbances. As a result, the robustness of the system is improved. Finally, the experimental verification of the proposed composite control strategy is completed. Experimental results show that the proposed control method has good dynamic performance, anti-interference ability and steady-state control accuracy.
In order to improve the speed tracking accuracy and robustness of permanent magnet synchronous motor (PMSM) control system and suppress periodic torque ripple, a single-loop control strategy of PMSM based on integral sliding mode control and iterative learning method is proposed. The single-loop sliding mode control strategy is adopted in the controller to replace the traditional rotational speed and current cascade control, so that the control system structure is simplified and the dynamic response of the system is improved. The iterative learning control is introduced to effectively suppress the torque ripple caused by current harmonics and improve the steady-state control accuracy of rotational speed. In addition, aiming at the external load disturbances and model and parameter uncertainties of the system, a dual disturbance observer is designed to estimate the system disturbances. As a result, the robustness of the system is improved. Finally, the experimental verification of the proposed composite control strategy is completed. Experimental results show that the proposed control method has good dynamic performance, anti-interference ability and steady-state control accuracy.
2022, 49(6):9-18.
DOI: 10.12177/emca.2022.029
Abstract:
Aiming at the problem that the traditional NSGA-Ⅱ has weak regional local search ability in multi-objective optimization of permanent magnet (PM) assisted switched reluctance motors, a regional local search algorithm based on NSGA-Ⅱ (RLS-NSGA-Ⅱ) is proposed. The improved crossover operator and mutation operator are used to enhance the search capability of the algorithm and search for the optimal solution set in the local area. The effectiveness of the algorithm is verified through standard multi-objective problems. Aiming at the problem that the optimization algorithm′s optimization precision of decision variables is too high, effective units for decision variables are reserved, and a minimum unit optimization mutation method is proposed. The multi-objective optimization of motor torque ripple, efficiency and average torque is performed using the proposed algorithm and the traditianal NSGA-Ⅱ. After optimization effect comparison and simulation, it is verified that the optimal solution derived from the proposed algorithm is more advantageous.
Aiming at the problem that the traditional NSGA-Ⅱ has weak regional local search ability in multi-objective optimization of permanent magnet (PM) assisted switched reluctance motors, a regional local search algorithm based on NSGA-Ⅱ (RLS-NSGA-Ⅱ) is proposed. The improved crossover operator and mutation operator are used to enhance the search capability of the algorithm and search for the optimal solution set in the local area. The effectiveness of the algorithm is verified through standard multi-objective problems. Aiming at the problem that the optimization algorithm′s optimization precision of decision variables is too high, effective units for decision variables are reserved, and a minimum unit optimization mutation method is proposed. The multi-objective optimization of motor torque ripple, efficiency and average torque is performed using the proposed algorithm and the traditianal NSGA-Ⅱ. After optimization effect comparison and simulation, it is verified that the optimal solution derived from the proposed algorithm is more advantageous.
2022, 49(6):19-23,59.
DOI: 10.12177/emca.2022.028
Abstract:
Based on virtual d-q current decoupling control method, we introduce the control method of dual four-quadrant pulse rectifier in single traction converter, the implementation method of carrier phase-shifting in the same controller, the implementation method of carrier phase-shifting of multiplexed four-quadrant pulse rectifier between different controllers, and the modulation compensation method when the switching frequency of four-quadrant pulse rectifier is low (less than 500 Hz). Finally, the control method is verified on an actual high-power converter. It is proved that this method can achieve the control objectives of low harmonic current at the grid side, high unit power factor at the grid side and constant voltage at the DC side.
Based on virtual d-q current decoupling control method, we introduce the control method of dual four-quadrant pulse rectifier in single traction converter, the implementation method of carrier phase-shifting in the same controller, the implementation method of carrier phase-shifting of multiplexed four-quadrant pulse rectifier between different controllers, and the modulation compensation method when the switching frequency of four-quadrant pulse rectifier is low (less than 500 Hz). Finally, the control method is verified on an actual high-power converter. It is proved that this method can achieve the control objectives of low harmonic current at the grid side, high unit power factor at the grid side and constant voltage at the DC side.
2022, 49(6):24-28,91.
DOI: 10.12177/emca.2022.053
Abstract:
The steelmaking converter dusting fan system is the main equipment of the steelmaking production dusting system. In order to ensure the normal operation of the equipment and avoid safety accidents and economic losses caused by abnormal power supply, a dual power supply switching device for the converter fan power supply and distribution system is proposed. The voltage abnormality detection method, switching timing selection and triggering control strategy of the switching device are analyzed. A simulation example based on MATLAB/Simulink proves the correctness of the phase angle difference between the standby power supply and the residual induced electromotive force and the dynamic switching strategy.
The steelmaking converter dusting fan system is the main equipment of the steelmaking production dusting system. In order to ensure the normal operation of the equipment and avoid safety accidents and economic losses caused by abnormal power supply, a dual power supply switching device for the converter fan power supply and distribution system is proposed. The voltage abnormality detection method, switching timing selection and triggering control strategy of the switching device are analyzed. A simulation example based on MATLAB/Simulink proves the correctness of the phase angle difference between the standby power supply and the residual induced electromotive force and the dynamic switching strategy.
2022, 49(6):29-35.
DOI: 10.12177/emca.2022.025
Abstract:
Aiming at noise problem in the operation of induction motor, through the multi physical field coupling finite element calculation of a 160 kW submersible induction motor, combined with the analytical method to explore the the order and frequency of the radial electromagnetic force, the space-time characteristics of radial electromagnetic force wave in the motor air gap are analyzed, and the correlation calculation of the noise is carried out through acoustic simulation. Considering the results of two-dimensional Fourier decomposition of radial electromagnetic force and the order and frequency of the mode of the shell model, the source of noise is analyzed and explained. The aim of noise control is proposed, such as changing the distribution of motor mode in order and frequency by adjusting the number of radiator ribs of the motor shell or reducing the vibration coefficient of motor shell.
Aiming at noise problem in the operation of induction motor, through the multi physical field coupling finite element calculation of a 160 kW submersible induction motor, combined with the analytical method to explore the the order and frequency of the radial electromagnetic force, the space-time characteristics of radial electromagnetic force wave in the motor air gap are analyzed, and the correlation calculation of the noise is carried out through acoustic simulation. Considering the results of two-dimensional Fourier decomposition of radial electromagnetic force and the order and frequency of the mode of the shell model, the source of noise is analyzed and explained. The aim of noise control is proposed, such as changing the distribution of motor mode in order and frequency by adjusting the number of radiator ribs of the motor shell or reducing the vibration coefficient of motor shell.
2022, 49(6):36-39,102.
DOI: 10.12177/emca.2022.050
Abstract:
Non-metallic materials used for motor windings were prone to performance degradation with changes in temperature and time. The activation energy of non-metallic materials could be used to identify the thermal life of non-metallic materials by connecting the actual service conditions and accelerated aging conditions. Its value directly determined the temperature and aging time for the thermal life identification of materials. This article mainly introduced the current main methods of activation energy estimation, including thermogravimetric analysis, DSC analysis, combination of thermogravimetric analysis and thermal aging test, and thermal aging test evaluation methods. The specific implementation process of each method , the differences between the methods and the scope of application were given in detail, so as to facilitate the selection of determination methods for different evaluation materials.
Non-metallic materials used for motor windings were prone to performance degradation with changes in temperature and time. The activation energy of non-metallic materials could be used to identify the thermal life of non-metallic materials by connecting the actual service conditions and accelerated aging conditions. Its value directly determined the temperature and aging time for the thermal life identification of materials. This article mainly introduced the current main methods of activation energy estimation, including thermogravimetric analysis, DSC analysis, combination of thermogravimetric analysis and thermal aging test, and thermal aging test evaluation methods. The specific implementation process of each method , the differences between the methods and the scope of application were given in detail, so as to facilitate the selection of determination methods for different evaluation materials.
2022, 49(6):40-46.
DOI: 10.12177/emca.2022.027
Abstract:
During the design and finalization process of an urban rail vehicle, the condensing fan was sheltered due to the limitation of the overall arrangement. In order to evaluate the influence of the shielding on the heat dissipation capacity of the whole cooling loop, the potential risk of the motor cooling system is evaluated with the help of 3D simulation method based on STAR CCM+ combined with a variety of 1D verification methods. When the current overall arrangement has an impact of 11.4% on the air intake of the condensing fan, after checking and analyzing the potential risk of the motor cooling system, it is found that the radiator still has sufficient margin and the risk is controllable. Based on this, an evaluation method for the working condition of the motor cooling system is developed.
During the design and finalization process of an urban rail vehicle, the condensing fan was sheltered due to the limitation of the overall arrangement. In order to evaluate the influence of the shielding on the heat dissipation capacity of the whole cooling loop, the potential risk of the motor cooling system is evaluated with the help of 3D simulation method based on STAR CCM+ combined with a variety of 1D verification methods. When the current overall arrangement has an impact of 11.4% on the air intake of the condensing fan, after checking and analyzing the potential risk of the motor cooling system, it is found that the radiator still has sufficient margin and the risk is controllable. Based on this, an evaluation method for the working condition of the motor cooling system is developed.
2022, 49(6):47-52.
DOI: 10.12177/emca.2022.039
Abstract:
In order to effectively provide energy buffer for the battery during the driving of hybrid electric vehicle, the state of charge (SOC) of the vehicle-mounted super-capacitor should be kept within a safe range to prevent capacitor overcharge or insufficient energy. To solve this problem, based on the working characteristics of the vehicle-mounted super-capacitors, we improve the traditional filtering distribution method of vehicle-based hybrid energy storage system. The logic gate control which uses complex algorithm logic and is difficult to design parameters is abandoned, and a simple PI control is used to realize the self-maintenance of super-capacitor power during the operation of electric vehicles. The proposed method is verified by a hybrid energy storage device based on the control of TMS320F2812 and a permanent magnet synchronous motor experimental platform based on hardware-in-the-loop simulation. The results show that this method can not only provide peak load power for the super-capacitor, achieve the "peak load shifting" of the battery, but also keep its steady-state voltage at a stable value, which can meet the energy recovery requirements of the vehicle-mounted super-capacitor for the hybrid electric vehicle.
In order to effectively provide energy buffer for the battery during the driving of hybrid electric vehicle, the state of charge (SOC) of the vehicle-mounted super-capacitor should be kept within a safe range to prevent capacitor overcharge or insufficient energy. To solve this problem, based on the working characteristics of the vehicle-mounted super-capacitors, we improve the traditional filtering distribution method of vehicle-based hybrid energy storage system. The logic gate control which uses complex algorithm logic and is difficult to design parameters is abandoned, and a simple PI control is used to realize the self-maintenance of super-capacitor power during the operation of electric vehicles. The proposed method is verified by a hybrid energy storage device based on the control of TMS320F2812 and a permanent magnet synchronous motor experimental platform based on hardware-in-the-loop simulation. The results show that this method can not only provide peak load power for the super-capacitor, achieve the "peak load shifting" of the battery, but also keep its steady-state voltage at a stable value, which can meet the energy recovery requirements of the vehicle-mounted super-capacitor for the hybrid electric vehicle.
2022, 49(6):53-59.
DOI: 10.12177/emca.2022.043
Abstract:
For the optimization design of magnetic coupling coil structure of wireless power transmission (WPT) system for electric vehicles, power level, transmission efficiency and economy should be considered comprehensively. The effect of number of coil turns and turn-spacing on transmission power, transmission efficiency and coil economy is analyzed first. Then, based on the non-dominated sorting genetic algorithm II (NSGA-II) with elitist strategy, a multi-objective optimization design method is proposed to optimize the coil parameters, such as number of coil turns and turn-spacing. The coil efficiency and coil economy are optimization objectives, and the 3.3 kW rated power and coil size are the constraint boundaries. Finally, based on the Maxwell-Simplorer co-simulation, the feasibility and validity of the optimization design method are verified. The maximum transmission efficiency of the optimized coil is 93.4%〖WTBZ〗, and the coil losses on both sides can be improved.
For the optimization design of magnetic coupling coil structure of wireless power transmission (WPT) system for electric vehicles, power level, transmission efficiency and economy should be considered comprehensively. The effect of number of coil turns and turn-spacing on transmission power, transmission efficiency and coil economy is analyzed first. Then, based on the non-dominated sorting genetic algorithm II (NSGA-II) with elitist strategy, a multi-objective optimization design method is proposed to optimize the coil parameters, such as number of coil turns and turn-spacing. The coil efficiency and coil economy are optimization objectives, and the 3.3 kW rated power and coil size are the constraint boundaries. Finally, based on the Maxwell-Simplorer co-simulation, the feasibility and validity of the optimization design method are verified. The maximum transmission efficiency of the optimized coil is 93.4%〖WTBZ〗, and the coil losses on both sides can be improved.
2022, 49(6):60-65.
DOI: 10.12177/emca.2022.032
Abstract:
The fractional-slot permanent magnet synchronous motor has high electromagnetic noise due to its lower order radial electromagnetic force. Based on theoretical analysis, Optislang multi-objective optimization platform and Ansys multi-physics-field finite element analysis platform, the electromagnetic noise of an 8-pole 36-slot permanent magnet synchronous motor for electric vehicle is analyzed and optimized. The electromagnetic noise of the motor is mainly caused by the vibration deformation of the stator core caused by the radial electromagnetic force acting on the stator teeth. The radial electromagnetic force is weakened by opening the auxiliary slots on the stator teeth and optimizing the slot parameters. The 2D finite element model of the motor is established, and the parameters of stator auxiliary slots on the stator teeth under different working conditions are optimized by Optislang, the Pareto front is calculated and the relative optimal solution is found. The radial electromagnetic forces of the stator teeth before and after the motor optimization are compared and analyzed, mapped to the corresponding 3D structure, and the electromagnetic noises before and after the motor optimization is calculated by Ansys. The effectiveness of the simulation results is verified by the prototype noise test.
The fractional-slot permanent magnet synchronous motor has high electromagnetic noise due to its lower order radial electromagnetic force. Based on theoretical analysis, Optislang multi-objective optimization platform and Ansys multi-physics-field finite element analysis platform, the electromagnetic noise of an 8-pole 36-slot permanent magnet synchronous motor for electric vehicle is analyzed and optimized. The electromagnetic noise of the motor is mainly caused by the vibration deformation of the stator core caused by the radial electromagnetic force acting on the stator teeth. The radial electromagnetic force is weakened by opening the auxiliary slots on the stator teeth and optimizing the slot parameters. The 2D finite element model of the motor is established, and the parameters of stator auxiliary slots on the stator teeth under different working conditions are optimized by Optislang, the Pareto front is calculated and the relative optimal solution is found. The radial electromagnetic forces of the stator teeth before and after the motor optimization are compared and analyzed, mapped to the corresponding 3D structure, and the electromagnetic noises before and after the motor optimization is calculated by Ansys. The effectiveness of the simulation results is verified by the prototype noise test.
2022, 49(6):66-75.
DOI: 10.12177/emca.2022.030
Abstract:
For the problem that five-phase permanent magnet synchronous motor inter-turn short-circuit fault and high resistance connection fault have the same fault characteristics, a fault detection and classification method based on current residual estimation and high-frequency current comparison is proposed. Firstly, the Kalman filter is used to detect the abnormal condition of motor by estimating the current residual of d-q axis during fault. Then the different characteristics of inductance and resistance at high frequency are used to distinguish the inter-turn short-circuit fault and high resistance connection fault. Finally, the severity and faulty phase of the two faults are studied. Simulation results show that this method can effectively diagnose motor stator faults and accurately identify inter-turn short-circuit fault and high resistance connection fault, and the severity of the fault has good robustness against the change of speed and load.
For the problem that five-phase permanent magnet synchronous motor inter-turn short-circuit fault and high resistance connection fault have the same fault characteristics, a fault detection and classification method based on current residual estimation and high-frequency current comparison is proposed. Firstly, the Kalman filter is used to detect the abnormal condition of motor by estimating the current residual of d-q axis during fault. Then the different characteristics of inductance and resistance at high frequency are used to distinguish the inter-turn short-circuit fault and high resistance connection fault. Finally, the severity and faulty phase of the two faults are studied. Simulation results show that this method can effectively diagnose motor stator faults and accurately identify inter-turn short-circuit fault and high resistance connection fault, and the severity of the fault has good robustness against the change of speed and load.
2022, 49(6):76-82.
DOI: 10.12177/emca.2022.036
Abstract:
The looseness fault of switch parts and electrical connection points often occurs in the operation of gas insulated switchgear (GIS), which leads to abnormal mechanical vibration. The vibration mechanism of three-phase community GIS and three-phase split GIS is derived from the electromagnetic force and eddy current on the conductive rod respectively, and the correctness of the vibration mechanism is proved by simulation modeling. The mechanical vibration model of the contact surface in the case of looseness fault is established, and the vibration displacement of the contact surface in the case of looseness is calculated by simulation. By comparing the vibration characteristics of normal operation with those of looseness fault, it is found that the energy of vibration signal will increase in some frequency bands when loosening fault occurs, and the energy increase is obvious in the 1 000~2 000 Hz range. By simulating the actual looseness fault on site, collecting the GIS vibration signal, and extracting the spectrum characteristics of the vibration signal by time-frequency transformation, the correctness of the simulation calculation is verified.
The looseness fault of switch parts and electrical connection points often occurs in the operation of gas insulated switchgear (GIS), which leads to abnormal mechanical vibration. The vibration mechanism of three-phase community GIS and three-phase split GIS is derived from the electromagnetic force and eddy current on the conductive rod respectively, and the correctness of the vibration mechanism is proved by simulation modeling. The mechanical vibration model of the contact surface in the case of looseness fault is established, and the vibration displacement of the contact surface in the case of looseness is calculated by simulation. By comparing the vibration characteristics of normal operation with those of looseness fault, it is found that the energy of vibration signal will increase in some frequency bands when loosening fault occurs, and the energy increase is obvious in the 1 000~2 000 Hz range. By simulating the actual looseness fault on site, collecting the GIS vibration signal, and extracting the spectrum characteristics of the vibration signal by time-frequency transformation, the correctness of the simulation calculation is verified.
2022, 49(6):83-91.
DOI: 10.12177/emca.2022.022
Abstract:
The traditional fault diagnosis methods have difficulty in accurately extracting fault characteristics in the case of complex power grids, and the fault diagnosis methods with high adaptability and recognition rates are urgently needed. A power grid fault diagnosis method based on the combination of compressed sensing, parallel convolutional neural network (CNN) and long short-term memory (LSTM) is proposed. A model of Yongfu DC transmission system is built to collect raw fault data, and the raw fault data are compressed and sampled by applying the principle of compressed sensing to obtain compressed domain fault signals to improve the computational efficiency of the network. Then, a parallel CNN-LSTM deep learning model with sparrow search algorithm (SSA) is built. The network structure and parameters of the parallel CNN-LSTM are determined by the SSA. The parallel CNN-LSTM deep learning model is used to mine the fault waveform and timing features directly in the compressed domain of the fault and identify the fault. The simulation results verify that the model has higher fault diagnosis accuracy compared with the traditional methods.
The traditional fault diagnosis methods have difficulty in accurately extracting fault characteristics in the case of complex power grids, and the fault diagnosis methods with high adaptability and recognition rates are urgently needed. A power grid fault diagnosis method based on the combination of compressed sensing, parallel convolutional neural network (CNN) and long short-term memory (LSTM) is proposed. A model of Yongfu DC transmission system is built to collect raw fault data, and the raw fault data are compressed and sampled by applying the principle of compressed sensing to obtain compressed domain fault signals to improve the computational efficiency of the network. Then, a parallel CNN-LSTM deep learning model with sparrow search algorithm (SSA) is built. The network structure and parameters of the parallel CNN-LSTM are determined by the SSA. The parallel CNN-LSTM deep learning model is used to mine the fault waveform and timing features directly in the compressed domain of the fault and identify the fault. The simulation results verify that the model has higher fault diagnosis accuracy compared with the traditional methods.
2022, 49(6):92-97.
DOI: 10.12177/emca.2022.020
Abstract:
To avoid the influence of partial demagnetization of permanent magnet on the control accuracy and safe operation of permanent magnet synchronous motors (PMSMs), a method to monitor partial demagnetization faults for fractional slot concentrated winding (FSCW) PMSM based on back electromotive force (EMF) harmonic analysis is proposed. After theoretical derivation, the mathematical models of magneto motive force (MMF) and single-slot back EMF under demagnetization are obtained. Then, with the amplitude of each harmonic component of the single-slot back EMF and winding coefficients of FSCW-PMSM, the variation of each harmonic amplitude of the single-phase back EMF can be deduced. The theoretical derivation above can verify the feasibility of judging the demagnetization fault by the variation of single-phase back EMF′s harmonics. Finally, using the prototype parameters, taking a 20-pole 24-slot interior PMSM to build a finite element model, a 2D electromagnetic simulation model is established to obtain the variation of the characteristic harmonics of the single-phase back EMF. The results show that the characteristic harmonic of single-phase back EMF changes periodically with the increase of the number of faults.
To avoid the influence of partial demagnetization of permanent magnet on the control accuracy and safe operation of permanent magnet synchronous motors (PMSMs), a method to monitor partial demagnetization faults for fractional slot concentrated winding (FSCW) PMSM based on back electromotive force (EMF) harmonic analysis is proposed. After theoretical derivation, the mathematical models of magneto motive force (MMF) and single-slot back EMF under demagnetization are obtained. Then, with the amplitude of each harmonic component of the single-slot back EMF and winding coefficients of FSCW-PMSM, the variation of each harmonic amplitude of the single-phase back EMF can be deduced. The theoretical derivation above can verify the feasibility of judging the demagnetization fault by the variation of single-phase back EMF′s harmonics. Finally, using the prototype parameters, taking a 20-pole 24-slot interior PMSM to build a finite element model, a 2D electromagnetic simulation model is established to obtain the variation of the characteristic harmonics of the single-phase back EMF. The results show that the characteristic harmonic of single-phase back EMF changes periodically with the increase of the number of faults.
2022, 49(6):98-102.
DOI: 10.12177/emca.2022.033
Abstract:
When the pumping unit is working, the actual load of each motor is different. How to adjust the actual input voltage of the motor according to the actual load of the pumping unit during the working process can significantly improve the efficiency of the pumping unit. This paper uses the neural network prediction algorithm to predict the actual input voltage of the motor, discusses the influence of the parameters of the neural network prediction algorithm on the prediction results, and compares the predicted value obtained by the neural network prediction algorithm with the measured value. The results show that the neural network prediction algorithm proposed in this paper can predict the optimal working voltage of the motor.
When the pumping unit is working, the actual load of each motor is different. How to adjust the actual input voltage of the motor according to the actual load of the pumping unit during the working process can significantly improve the efficiency of the pumping unit. This paper uses the neural network prediction algorithm to predict the actual input voltage of the motor, discusses the influence of the parameters of the neural network prediction algorithm on the prediction results, and compares the predicted value obtained by the neural network prediction algorithm with the measured value. The results show that the neural network prediction algorithm proposed in this paper can predict the optimal working voltage of the motor.
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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.
