Analysis of temperature field for a surface-mounted and interior permanent magnet synchronous motor adopting magnetic-thermal coupling method

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.

Application of neural networks for permanent magnet synchronous motor direct torque control

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.

Optimization of Vibration and Noise Performance of Permanent Magnet Synchronous Motor for Electric Vehicles

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.

Multi-Objective Optimization of Surface-Mounted and Interior Permanent Magnet Synchronous Motor Based on Taguchi Method and Response Surface Method

The surface-mounted and interior permanent magnet synchronous motor(SIPMSM)has the characteristics of multiple variables,strong coupling and nonlinearity.In order to improve the performance of SIPMSM,this paper presents a multi-objective optimal design process using Taguchi and response surface methodology(RSM).The peak value of cogging torque(PVCT),ratio value of average torque and permanent magnet weight(RTW),torque ripple and back-EMF total harmonics distortion(ETHD)are selected as optimization goals.The experiment matrix is established by Taguchi method,and analyzed the tendency and proportion of the effect of the optimization parameters on SIPMSM performance.The rules of choosing multi-objective optimization parameters are obtained.The least-squares method is used to establish the optimal objective function,and RSM is used to obtain the resolutions of the optimization objective function.Comparing the initial performance with optimized performance verifies the effectiveness of the proposed method.

Sensorless Control of IPMSM for Last 10 Years and Next 5 Years

This paper presents the developments of sensorless control of interior permanent magnet synchronous machine(IPMSM)for last 10 years,which could be divided into the past and the present for each 5 years.Several popular methods developed for last 10 years would be described and evaluated,and the limitations with the methods are discussed.In the past a concept extended EMF(EEMF)was introduced and it can model IPMSM as a non-salient motor,meaning that the representation of IPMSM in the estimated rotor reference frame would be much simpler and accurate.However,because it still relied on back EMF,standstill operation was impossible.And,the position control of IPMSM could not be achieved with EEMF concept.For sensorless drive,the high-frequency signal injection method exploiting inherent saliency of IPMSM has been continuously developed for last 10 years and applied to various industry fields,where torque control at standstill is essential.Its performance has been improved but there are still many problems to be solved.In the present,the square-wave signal injection at estimated d-axis has improved the control performance conspicuously.However,there are strong demands to improve the control performance of sensorless drive,yet.Based on the problems in the present,in this paper the possible developments of sensorless drive of IPMSM in next 5 years are enlightened as the future of sensorless control.