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Volume 50,Issue 5,2023 Table of Contents
2023, 50(5):1-9.
DOI: 10.12177/emca.2023.041
Abstract:
Due to the limitations of the application range and the defects of their own structures, the traditional observers such as state observers and Kalman filters may complicate the design of motor control systems, reduce the observation accuracy and limit the observation range, etc. Deep learning has the advantages of nonlinear fitting capability, good generalization ability and strong feature extraction ability, etc. Deep learning observer is taken as the main line, the advantages of its application in motor control system is described. The principle and structure of deep learning with four typical networks is taken as examples, the analysis of the application of deep learning in motor control is listed and focused on, and on the future developing direction of deep learning in motor observer control is forecasted.
Due to the limitations of the application range and the defects of their own structures, the traditional observers such as state observers and Kalman filters may complicate the design of motor control systems, reduce the observation accuracy and limit the observation range, etc. Deep learning has the advantages of nonlinear fitting capability, good generalization ability and strong feature extraction ability, etc. Deep learning observer is taken as the main line, the advantages of its application in motor control system is described. The principle and structure of deep learning with four typical networks is taken as examples, the analysis of the application of deep learning in motor control is listed and focused on, and on the future developing direction of deep learning in motor observer control is forecasted.
2 Research on Data-Driven Control of Motor Driven Car-Like Mobile Robots with Rough Terrain Formation
2023, 50(5):10-16.
DOI: 10.12177/emca.2023.042
Abstract:
The car-like robots are often affected by dynamics disturbance in the complex terrain environment, and the formation and trajectory tracking control of high-performance robots can’t be realized only by kinematics analysis. In order to solve this problem, a data-driven dynamic inner loop controller design method is proposed. The motor and the decelerating mechanism are considered as a whole. The input and output data are used to identify the model parameters in real time and the characteristic model of dynamic inner loop is built. A discrete sliding mode controller is designed for the second-order discrete dynamic system model driven by data and its stability is analyzed. The simulation and comparison are carried out in Microsoft Robotics Developer Studio 4 (MRDS4) which is a robot simulation platform based on the physical engine of Microsoft. The simulation data are imported into MATLAB for analysis to verify the overall effectiveness of the designed control strategy. In the complex terrain environment where the disturbance torque has a large influence, the robot can still maintain fast dynamic response speed, and respond quickly to the switching and tracking in formation.
The car-like robots are often affected by dynamics disturbance in the complex terrain environment, and the formation and trajectory tracking control of high-performance robots can’t be realized only by kinematics analysis. In order to solve this problem, a data-driven dynamic inner loop controller design method is proposed. The motor and the decelerating mechanism are considered as a whole. The input and output data are used to identify the model parameters in real time and the characteristic model of dynamic inner loop is built. A discrete sliding mode controller is designed for the second-order discrete dynamic system model driven by data and its stability is analyzed. The simulation and comparison are carried out in Microsoft Robotics Developer Studio 4 (MRDS4) which is a robot simulation platform based on the physical engine of Microsoft. The simulation data are imported into MATLAB for analysis to verify the overall effectiveness of the designed control strategy. In the complex terrain environment where the disturbance torque has a large influence, the robot can still maintain fast dynamic response speed, and respond quickly to the switching and tracking in formation.
2023, 50(5):17-25.
DOI: 10.12177/emca.2023.015
Abstract:
Aiming at the problem of large amount of calculation in the process of multi-step model predictive current control of surface mounted permanent magnet synchronous motor (PMSM), a multi-step model predictive control with optimal calculation of cost function is proposed. The optimization calculation of cost function adopts the event trigger mechanism, and the calculation amount of multi-step prediction is dynamically reduced by setting the threshold of cost function. Simulation results show that the multi-step model predictive current control performance of cost function optimization calculation is good, which is completely equivalent to the traditional method, also the control effect is equivalent. Based on STM32H743 single chip microcomputer platform, the optimization method and traditional method single control cycle execution time. Experimental results show that for multi-step prediction, the optimization algorithm can reduce the single control cycle execution time, two-step prediction to 77.71%, three-step prediction to 53.95%, four-step prediction to 39.76% and five-step prediction to 33.48%. It is shown that the control performance is the same as traditional calculation method, but the real-time performance is improved.
Aiming at the problem of large amount of calculation in the process of multi-step model predictive current control of surface mounted permanent magnet synchronous motor (PMSM), a multi-step model predictive control with optimal calculation of cost function is proposed. The optimization calculation of cost function adopts the event trigger mechanism, and the calculation amount of multi-step prediction is dynamically reduced by setting the threshold of cost function. Simulation results show that the multi-step model predictive current control performance of cost function optimization calculation is good, which is completely equivalent to the traditional method, also the control effect is equivalent. Based on STM32H743 single chip microcomputer platform, the optimization method and traditional method single control cycle execution time. Experimental results show that for multi-step prediction, the optimization algorithm can reduce the single control cycle execution time, two-step prediction to 77.71%, three-step prediction to 53.95%, four-step prediction to 39.76% and five-step prediction to 33.48%. It is shown that the control performance is the same as traditional calculation method, but the real-time performance is improved.
2023, 50(5):26-38.
DOI: 10.12177/emca.2023.038
Abstract:
Based on the multi-physics field coupling analysis of electromagnetic field，structural field and acoustic field, a predictive study of the electromagnetic vibroacoustic laws of high-temperature superconducting dual-stator generator (HTSDSG) with stationary seal is carried out. According to the characteristics of stator tooth saturation in HTS-DSG, the method of combining equivalent air gap length and dynamic magnetic permeability is used to analyze and calculate the magnetic flux densities of the inner and outer air gaps in the saturated state of HTS-DSG respectively. Meanwhile, the correctness of the theoretical method is verified by the simulation and experiment. Aiming at the special structure of the split cooling Dewar in the superconducting generator, the vibration stress analysis of the Dewar at different positions is carried out, and the vibration laws of the Dewar at different positions is obtained. The maximum tensile strength is far greater than the vibration stress, that is, under the normal operation state of the motor, the superconducting coil will not fail due to the vibration of the whole machine. Finally, the electromagnetic force is coupled to the HTS-DSG sound field finite element model, and the electromagnetic vibration and noise laws of HTS-DSG are predicted by using multi-physics field coupling analysis.
Based on the multi-physics field coupling analysis of electromagnetic field，structural field and acoustic field, a predictive study of the electromagnetic vibroacoustic laws of high-temperature superconducting dual-stator generator (HTSDSG) with stationary seal is carried out. According to the characteristics of stator tooth saturation in HTS-DSG, the method of combining equivalent air gap length and dynamic magnetic permeability is used to analyze and calculate the magnetic flux densities of the inner and outer air gaps in the saturated state of HTS-DSG respectively. Meanwhile, the correctness of the theoretical method is verified by the simulation and experiment. Aiming at the special structure of the split cooling Dewar in the superconducting generator, the vibration stress analysis of the Dewar at different positions is carried out, and the vibration laws of the Dewar at different positions is obtained. The maximum tensile strength is far greater than the vibration stress, that is, under the normal operation state of the motor, the superconducting coil will not fail due to the vibration of the whole machine. Finally, the electromagnetic force is coupled to the HTS-DSG sound field finite element model, and the electromagnetic vibration and noise laws of HTS-DSG are predicted by using multi-physics field coupling analysis.
2023, 50(5):39-45.
DOI: 10.12177/emca.2023.046
Abstract:
Taking the flexibility of rotor into account, a three-dimensional surface contact model of ring type traveling wave ultrasonic motors is developed. The stator vibration, the normal contact and the tangential friction between the stator and rotor are analyzed, and the surface contact mechanism between the stator and rotor and the torque-speed characteristics of the motor are investigated. The results show that owing to the flexibility of the rotor, the shape of contact area between the stator and the rotor is irregular and the contact pressure distribution along the radial direction is inhomogeneous. The three-dimensional surface contact model is validated by comparing the calculated torque-speed characteristics with the measured values of the prototype motor. Based on the three-dimensional surface contact model, the influences of the structural parameters of the flexible rotor on the maximum contact pressure and the torque-speed characteristics of the motor are analyzed. The structure of the rotor is optimized according to the analysis results, which achieves a significant reduction in the maximum contact pressure as well as an obvious improvement of torque-speed characteristics of the motor.
Taking the flexibility of rotor into account, a three-dimensional surface contact model of ring type traveling wave ultrasonic motors is developed. The stator vibration, the normal contact and the tangential friction between the stator and rotor are analyzed, and the surface contact mechanism between the stator and rotor and the torque-speed characteristics of the motor are investigated. The results show that owing to the flexibility of the rotor, the shape of contact area between the stator and the rotor is irregular and the contact pressure distribution along the radial direction is inhomogeneous. The three-dimensional surface contact model is validated by comparing the calculated torque-speed characteristics with the measured values of the prototype motor. Based on the three-dimensional surface contact model, the influences of the structural parameters of the flexible rotor on the maximum contact pressure and the torque-speed characteristics of the motor are analyzed. The structure of the rotor is optimized according to the analysis results, which achieves a significant reduction in the maximum contact pressure as well as an obvious improvement of torque-speed characteristics of the motor.
2023, 50(5):46-52,60.
DOI: 10.12177/emca.2023.045
Abstract:
Multi-phase self-excited synchronous motor has the advantages of large starting torque, no need for permanent magnet, and adjustable air gap magnetic field, which is widely applied to the large torque demand under short-term special conditions such as low speed climbing. As a new type of motor, its excitation mechanism mathematical model is not clear, which directly restricts the development of the motor control system. Therefore, the excitation of the motor under steady state is studied. The basic structure and high-frequency excitation principle of the self-excited synchronous motor are analyzed. The mathematical relationship between the high-frequency current injected into the stator winding and the excitation current generated on the rotor excitation winding under steady-state conditions is studied. On this basis, the electromagnetic torque expression is obtained. The motion equations of the motor in stationary and rotating coordinate systems are established. Finally, the MATLAB/Simulink simulation model is built under the rotating dq coordinate system and the Maxwell finite element simulation results are compared and analyzed. The results verify the correctness of the mathematical model.
Multi-phase self-excited synchronous motor has the advantages of large starting torque, no need for permanent magnet, and adjustable air gap magnetic field, which is widely applied to the large torque demand under short-term special conditions such as low speed climbing. As a new type of motor, its excitation mechanism mathematical model is not clear, which directly restricts the development of the motor control system. Therefore, the excitation of the motor under steady state is studied. The basic structure and high-frequency excitation principle of the self-excited synchronous motor are analyzed. The mathematical relationship between the high-frequency current injected into the stator winding and the excitation current generated on the rotor excitation winding under steady-state conditions is studied. On this basis, the electromagnetic torque expression is obtained. The motion equations of the motor in stationary and rotating coordinate systems are established. Finally, the MATLAB/Simulink simulation model is built under the rotating dq coordinate system and the Maxwell finite element simulation results are compared and analyzed. The results verify the correctness of the mathematical model.
2023, 50(5):53-60.
DOI: 10.12177/emca.2023.043
Abstract:
The 48 V flat wire winding induction motor is taken as the research object, the influence of oil-passive cooling of the rotor of induction motor on the distribution of temperature field and the thermal equalization effect is studied by using COMSOL software. Three-dimensional electromagnetic field analysis is transformed into two-dimensional analysis on the axial middle plane of the motor to simplify calculation and obtain flux density distribution, the loss value of each part of the motor is calculated. A simplified three-dimensional global simulation model of the motor is established, and the transient thermal analysis of the motor is carried out under the large current condition. The simulation results show that the temperature rising of the air gap, rotor, winding in the passive oil-cooling motor is obviously reduced. Through the temperature rising experiment of air cooling and the passive oil-cooling in the two motors with the same parameters. The experiment results show that, compared with air cooling system, passive oil-cooling system can significantly improve the effect of temperature rising of the rotor and winding in the motor, and raise the output power of the motor, which is an economic and reliable cooling system.
The 48 V flat wire winding induction motor is taken as the research object, the influence of oil-passive cooling of the rotor of induction motor on the distribution of temperature field and the thermal equalization effect is studied by using COMSOL software. Three-dimensional electromagnetic field analysis is transformed into two-dimensional analysis on the axial middle plane of the motor to simplify calculation and obtain flux density distribution, the loss value of each part of the motor is calculated. A simplified three-dimensional global simulation model of the motor is established, and the transient thermal analysis of the motor is carried out under the large current condition. The simulation results show that the temperature rising of the air gap, rotor, winding in the passive oil-cooling motor is obviously reduced. Through the temperature rising experiment of air cooling and the passive oil-cooling in the two motors with the same parameters. The experiment results show that, compared with air cooling system, passive oil-cooling system can significantly improve the effect of temperature rising of the rotor and winding in the motor, and raise the output power of the motor, which is an economic and reliable cooling system.
2023, 50(5):61-71.
DOI: 10.12177/emca.2023.039
Abstract:
To solve the problem of low forecasting accuracy of wind power, a hybrid forecasting model integrating singular spectrum analysis (SSA), convolutional neural network (CNN), bi-directional gated recurrent unit (BiGRU) and Attention mechanism is proposed. In order to suppress the lag problem of the predicted power curve caused by the random fluctuation of wind power, the SSA method is used to decompose the original data into a series of subcomponents with a relatively stable fluctuation characteristics, and the effective reconstruction is realized based on the fuzzy entropy (FE) value of each component. The CNN-BiGRU-Attention model is designed for the forecasting of each reconstructed component. For example, CNN network is used to effectively extract the high-dimensional data features of each reconstructed component, BiGRU network is used to capture the nonlinear dynamic changes of key feature vectors obtained by CNN, and the Attention mechanism is used to highlight and strengthen the effective learning of key features of power data. The final forecasting results are obtained by superimposing the prediction values of each reconstruction component based on the CNN-BiGRU-Attention model. The actual operation data of wind farms in the Hami region of Xinjiang province is used as experimental data, the results show that the proposed method can effectively alleviate the lag phenomenon in wind power forecasting, and the forecasting accuracy is fully ahead of other existed prediction methods.
To solve the problem of low forecasting accuracy of wind power, a hybrid forecasting model integrating singular spectrum analysis (SSA), convolutional neural network (CNN), bi-directional gated recurrent unit (BiGRU) and Attention mechanism is proposed. In order to suppress the lag problem of the predicted power curve caused by the random fluctuation of wind power, the SSA method is used to decompose the original data into a series of subcomponents with a relatively stable fluctuation characteristics, and the effective reconstruction is realized based on the fuzzy entropy (FE) value of each component. The CNN-BiGRU-Attention model is designed for the forecasting of each reconstructed component. For example, CNN network is used to effectively extract the high-dimensional data features of each reconstructed component, BiGRU network is used to capture the nonlinear dynamic changes of key feature vectors obtained by CNN, and the Attention mechanism is used to highlight and strengthen the effective learning of key features of power data. The final forecasting results are obtained by superimposing the prediction values of each reconstruction component based on the CNN-BiGRU-Attention model. The actual operation data of wind farms in the Hami region of Xinjiang province is used as experimental data, the results show that the proposed method can effectively alleviate the lag phenomenon in wind power forecasting, and the forecasting accuracy is fully ahead of other existed prediction methods.
2023, 50(5):72-81,104.
DOI: 10.12177/emca.2023.049
Abstract:
Large-scale access of wind power will increase the peak shaving pressure of the power grid, while the allocation of energy storage can effectively alleviate the pressure. In order to improve the economy of system operation, it is necessary to formulate a reasonable peak shaving strategy of the combined system, optimizing the load shedding power of wind turbine and the charge and discharge power of energy storage. The peak shaving problem of wind-storage combined system is transformed into an optimal control problem, and an optimal peak shaving control strategy based on Pontryagin maximum principle (PMP) is proposed to solve this problem. Since the loss model of energy storage is complex and nonlinear, the indirect shooting method is used to figure out the numerical solution of the optimal control. Afterwards, an improved peak shaving strategy is proposed to reduce the solution time through solving the minimum value of Hamilton function. Finally, an example is given to analyze the proposed optimal peak shaving strategy, and the example results verify the effectiveness of the proposed peak shaving strategy.
Large-scale access of wind power will increase the peak shaving pressure of the power grid, while the allocation of energy storage can effectively alleviate the pressure. In order to improve the economy of system operation, it is necessary to formulate a reasonable peak shaving strategy of the combined system, optimizing the load shedding power of wind turbine and the charge and discharge power of energy storage. The peak shaving problem of wind-storage combined system is transformed into an optimal control problem, and an optimal peak shaving control strategy based on Pontryagin maximum principle (PMP) is proposed to solve this problem. Since the loss model of energy storage is complex and nonlinear, the indirect shooting method is used to figure out the numerical solution of the optimal control. Afterwards, an improved peak shaving strategy is proposed to reduce the solution time through solving the minimum value of Hamilton function. Finally, an example is given to analyze the proposed optimal peak shaving strategy, and the example results verify the effectiveness of the proposed peak shaving strategy.
2023, 50(5):82-91.
DOI: 10.12177/emca.2023.047
Abstract:
It is difficult to determine the global optimal condition sequence and the location of the optimal condition conversion point of complex lines. In order to solve this problem, a multi-objective optimization method based on the improved sparrow search algorithm (ISSA) is proposed. The operation performance indexes and constraints of freight trains are analyzed, the optimization model with energy-saving punctuality is constructed, and the fitness function is designed based on linear weighted summation. According to the line speed limit and ramp conditions, a method for solving the working condition sequence of freight trains under complex lines is designed, and the position of the optimal working condition conversion point under the working condition sequence is obtained by the ISSA based on adaptive weight and Levy flight disturbance. The simulation results show that the target speed curve generated by the designed working condition sequence and the position of the conversion point can achieve energy-saving on the premise of meeting the on-time operation of freight trains.
It is difficult to determine the global optimal condition sequence and the location of the optimal condition conversion point of complex lines. In order to solve this problem, a multi-objective optimization method based on the improved sparrow search algorithm (ISSA) is proposed. The operation performance indexes and constraints of freight trains are analyzed, the optimization model with energy-saving punctuality is constructed, and the fitness function is designed based on linear weighted summation. According to the line speed limit and ramp conditions, a method for solving the working condition sequence of freight trains under complex lines is designed, and the position of the optimal working condition conversion point under the working condition sequence is obtained by the ISSA based on adaptive weight and Levy flight disturbance. The simulation results show that the target speed curve generated by the designed working condition sequence and the position of the conversion point can achieve energy-saving on the premise of meeting the on-time operation of freight trains.
2023, 50(5):92-96.
DOI: 10.12177/emca.2023.037
Abstract:
Partial discharge （PD） on-line monitoring is a common technology in condition of high-voltage motor monitoring. However, it is difficult to avoid noise interference on site. The most common noises are white noise and periodic narrowband noise. A new denoising method combining singular value decomposition and wavelet transform (SVD-WT) is proposed. The original signal is decomposed by SVD. Based on calculating the kurtosis value of the singular value sequence, the periodic narrowband noise is removed by adaptively selecting the singular value to be reconstructed. Then, the starting position of PD signal is determined by calculating the variance of the signal in the sliding window. Finally, the PD signal after denoising is obtained by zeroing the no PD location. The simulated and measured PD signals are denoised and compared with empirical mode decomposition and wavelet transform (EMD-WT) and adaptive singular value decomposition (ASVD). The results of simulated and measured PD signals show that the SVD-WT method has excellent performance.
Partial discharge （PD） on-line monitoring is a common technology in condition of high-voltage motor monitoring. However, it is difficult to avoid noise interference on site. The most common noises are white noise and periodic narrowband noise. A new denoising method combining singular value decomposition and wavelet transform (SVD-WT) is proposed. The original signal is decomposed by SVD. Based on calculating the kurtosis value of the singular value sequence, the periodic narrowband noise is removed by adaptively selecting the singular value to be reconstructed. Then, the starting position of PD signal is determined by calculating the variance of the signal in the sliding window. Finally, the PD signal after denoising is obtained by zeroing the no PD location. The simulated and measured PD signals are denoised and compared with empirical mode decomposition and wavelet transform (EMD-WT) and adaptive singular value decomposition (ASVD). The results of simulated and measured PD signals show that the SVD-WT method has excellent performance.
2023, 50(5):97-104.
DOI: 10.12177/emca.2023.034
Abstract:
Aiming at the problem of non-ideal deviation on sampling envelope surface in current resolver software decoding, the current mainstream error correction methods are analyzed and divided into three categories: input correction, phase locked loop correction and output feedback correction. Then it is deduced theoretically that the amplitude deviation and DC deviation will superimpose a double frequency fluctuation on the output angle decoded by the software, and the orthogonal deviation will superimpose a fundamental frequency fluctuation. An input correction calibration method based on discrete Fourier transform (DFT) is proposed. The amplitude deviation, DC deviation and orthogonal deviation are extracted by this method, and the corresponding correction steps are designed for these three deviations. At the same time, it is deduced that there is a fluctuation error related to the initial phase of the envelope surface in the amplitude deviation and DC deviation extracted by DFT method when the rotational speed error occurs, and the influence of this error on the extraction results is solved by taking the average value of the fluctuation during a period of time. Finally, the correctness of the derivation is verified by simulation, and a resolver calibration experiment is set up for the towing platform. Comparing the data before and after calibration, it is shown that the output angle linearity of the phase locked loop with corrected deviation is better, the rotation speed fluctuation is smaller, and the corresponding dq axis current of the specified order is also smaller.
Aiming at the problem of non-ideal deviation on sampling envelope surface in current resolver software decoding, the current mainstream error correction methods are analyzed and divided into three categories: input correction, phase locked loop correction and output feedback correction. Then it is deduced theoretically that the amplitude deviation and DC deviation will superimpose a double frequency fluctuation on the output angle decoded by the software, and the orthogonal deviation will superimpose a fundamental frequency fluctuation. An input correction calibration method based on discrete Fourier transform (DFT) is proposed. The amplitude deviation, DC deviation and orthogonal deviation are extracted by this method, and the corresponding correction steps are designed for these three deviations. At the same time, it is deduced that there is a fluctuation error related to the initial phase of the envelope surface in the amplitude deviation and DC deviation extracted by DFT method when the rotational speed error occurs, and the influence of this error on the extraction results is solved by taking the average value of the fluctuation during a period of time. Finally, the correctness of the derivation is verified by simulation, and a resolver calibration experiment is set up for the towing platform. Comparing the data before and after calibration, it is shown that the output angle linearity of the phase locked loop with corrected deviation is better, the rotation speed fluctuation is smaller, and the corresponding dq axis current of the specified order is also smaller.
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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.
