Aiming at obtaining high power density of surface-mounted and interior permanent magnet synchronous motor(SIPMSM),it is important to accurately calculate the temperature field distribution of SIPMSM,and a magnetic-the...Aiming at obtaining high power density of surface-mounted and interior permanent magnet synchronous motor(SIPMSM),it is important to accurately calculate the temperature field distribution of SIPMSM,and a magnetic-thermal coupling method is proposed.The magnetic-thermal coupling mechanism is analyzed.The thermal network model and finite element model are built by this method,respectively.The effects of power frequency on iron losses and temperature fields are analyzed by the magnetic-thermal coupling finite element model under the condition of rated load,and the relationship between the load and temperature field is researched under the condition of the synchronous speed.In addition,the equivalent thermal network model is used to verify the magnetic-thermal coupling method.Then the temperatures of various nodes are obtained.The results show that there are advantages in both computational efficiency and accuracy for the proposed coupling method,which can be applied to other permanent magnet motors with complex structures.展开更多
Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training a...Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.展开更多
In the design of the motor used for electric vehicles(EVS),vibration and noise problems are often ignored,which reduce the reliability and service life of the motor.In this paper,an interior permanent magnet synchrono...In the design of the motor used for electric vehicles(EVS),vibration and noise problems are often ignored,which reduce the reliability and service life of the motor.In this paper,an interior permanent magnet synchronous motor(IPMSM)with high power density is taken as an example,and its electromagnetic vibration and noise problem is investigated and optimized.Firstly,the factors that generate the electromagnetic force harmonic of IPMSM are analyzed by theoretical derivation.Furthermore,the mode and electromagnetic harmonic distribution of the motor are calculated and analyzed by establishing the electromagnetic-structure-sound coupling simulation model.Then,by combining finite element method(FEM)with modern optimization algorithm,an electromagnetic vibration and noise performance optimization method is proposed in the electromagnetic design stage of the motor.Finally,an IPMSM is optimized by this method for electromagnetic vibration and noise performance.The results of comparison between before and after optimization prove the feasibility of the method.展开更多
为提高车用内置式永磁同步电机驱动系统的速度响应能力和抗干扰性,提出在最大转矩比电流控制下,采用基于误差判断的反馈补偿型二自由度最大转矩比电流控制策略。通过对电机的数学模型进行分析,结合空间矢量脉宽调制技术,实现最大转矩比...为提高车用内置式永磁同步电机驱动系统的速度响应能力和抗干扰性,提出在最大转矩比电流控制下,采用基于误差判断的反馈补偿型二自由度最大转矩比电流控制策略。通过对电机的数学模型进行分析,结合空间矢量脉宽调制技术,实现最大转矩比电流控制;构建传统PI控制系统和二自由度(two degree of freedom,2DOF)最大转矩比电流(maximum torque per ampere,MTPA)控制系统进行对比仿真分析。通过MATLAB/Simulink平台系统仿真分析,使用基于误差判断的反馈补偿型2DOF调节可使转速响应超调量控制在0.5%以内,响应时间缩短70%~80%。验证了所提控制策略的可行性和有效性。展开更多
This paper introduces a novel method for fast calculating the electromagnetic forces in interior permanent magnet synchronous machines(IPMSMs)under pulse width modulation(PWM)voltage source inverter(VSI)supply based o...This paper introduces a novel method for fast calculating the electromagnetic forces in interior permanent magnet synchronous machines(IPMSMs)under pulse width modulation(PWM)voltage source inverter(VSI)supply based on the small-signal time-harmonic finite element analysis(THFEA),which has been successfully utilized for fast calculating the PWMinduced losses in silicon steel sheets and permanent magnets.Based on the small-signal THFEA,the functional relationships between high-frequency harmonic voltages(HFHVs)and corresponding airgap flux densities are established,which are used for calculating the flux density spectra caused by each HFHV in the PWM voltage spectra.Then,the superposition principle is applied for calculating the flux density spectra caused by fundamental currents and all HFHVs,which are converted to the electromagnetic force spectra at last.The relative errors between the force density spectra calculated with the proposed method and those obtained from traditional time-stepping finite element analysis(TSFEA)using PWM voltages as input are within 3.1%,while the proposed method is 24 times faster than the traditional TSFEA.展开更多
基金This work was supported by Natural Science Foundation of China(Item number:51777060,U1361109)Natural Science Foundation of Henan province(Item number:162300410117)the he innovative research team plan of Henan Polytechnic University(Item number:T2015-2).
文摘Aiming at obtaining high power density of surface-mounted and interior permanent magnet synchronous motor(SIPMSM),it is important to accurately calculate the temperature field distribution of SIPMSM,and a magnetic-thermal coupling method is proposed.The magnetic-thermal coupling mechanism is analyzed.The thermal network model and finite element model are built by this method,respectively.The effects of power frequency on iron losses and temperature fields are analyzed by the magnetic-thermal coupling finite element model under the condition of rated load,and the relationship between the load and temperature field is researched under the condition of the synchronous speed.In addition,the equivalent thermal network model is used to verify the magnetic-thermal coupling method.Then the temperatures of various nodes are obtained.The results show that there are advantages in both computational efficiency and accuracy for the proposed coupling method,which can be applied to other permanent magnet motors with complex structures.
基金the National Natural Science Foundation of China (60374032).
文摘Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.
基金This work was supported by the Fundamental Research Funds for the Central Universities(No.2019YJS181).
文摘In the design of the motor used for electric vehicles(EVS),vibration and noise problems are often ignored,which reduce the reliability and service life of the motor.In this paper,an interior permanent magnet synchronous motor(IPMSM)with high power density is taken as an example,and its electromagnetic vibration and noise problem is investigated and optimized.Firstly,the factors that generate the electromagnetic force harmonic of IPMSM are analyzed by theoretical derivation.Furthermore,the mode and electromagnetic harmonic distribution of the motor are calculated and analyzed by establishing the electromagnetic-structure-sound coupling simulation model.Then,by combining finite element method(FEM)with modern optimization algorithm,an electromagnetic vibration and noise performance optimization method is proposed in the electromagnetic design stage of the motor.Finally,an IPMSM is optimized by this method for electromagnetic vibration and noise performance.The results of comparison between before and after optimization prove the feasibility of the method.
文摘为提高车用内置式永磁同步电机驱动系统的速度响应能力和抗干扰性,提出在最大转矩比电流控制下,采用基于误差判断的反馈补偿型二自由度最大转矩比电流控制策略。通过对电机的数学模型进行分析,结合空间矢量脉宽调制技术,实现最大转矩比电流控制;构建传统PI控制系统和二自由度(two degree of freedom,2DOF)最大转矩比电流(maximum torque per ampere,MTPA)控制系统进行对比仿真分析。通过MATLAB/Simulink平台系统仿真分析,使用基于误差判断的反馈补偿型2DOF调节可使转速响应超调量控制在0.5%以内,响应时间缩短70%~80%。验证了所提控制策略的可行性和有效性。
基金supported in part by the National Natural Science Foundation of China under projects 51907053by Natural Science Foundation of Jiangsu Province of China under Project BK20190489+1 种基金by the Fundamental Research Funds for the Central Universities under grant B200202167by the China Postdoctoral Science Foundation under grant no.2019M661708。
文摘This paper introduces a novel method for fast calculating the electromagnetic forces in interior permanent magnet synchronous machines(IPMSMs)under pulse width modulation(PWM)voltage source inverter(VSI)supply based on the small-signal time-harmonic finite element analysis(THFEA),which has been successfully utilized for fast calculating the PWMinduced losses in silicon steel sheets and permanent magnets.Based on the small-signal THFEA,the functional relationships between high-frequency harmonic voltages(HFHVs)and corresponding airgap flux densities are established,which are used for calculating the flux density spectra caused by each HFHV in the PWM voltage spectra.Then,the superposition principle is applied for calculating the flux density spectra caused by fundamental currents and all HFHVs,which are converted to the electromagnetic force spectra at last.The relative errors between the force density spectra calculated with the proposed method and those obtained from traditional time-stepping finite element analysis(TSFEA)using PWM voltages as input are within 3.1%,while the proposed method is 24 times faster than the traditional TSFEA.
