| The PMSM is small in size and high in power density,which leads to high unit heat loss.The object of this paper is TFY132P8-8 motor,which is used in industrial powder.Due to the worse working environment than ordinary motors,a large amount of heat will be generated after a long period of operation,and overheating will lead to the motor not working normally,and even irreversible demagnitization of permanent magnets will cause the motor to be scrapped.Therefore,this paper analyzes and studies the temperature field of the motor and carries out optimization design,including the following points:First,calculate the motor loss.Motor loss mainly includes: core loss,winding copper loss,mechanical loss,eddy current loss,etc.In this paper,the cause of motor loss was analyzed in depth through modeling,and the magnetic field distribution of the motor was calculated by Ansoft Maxwell simulation software,and various losses of the motor were calculated according to the simulation results,so as to prepare for the calculation of motor temperature rise.Secondly,the temperature field of the motor in steady state operation is analyzed.Based on the theory of fluid mechanics and the basic law of heat transfer,the heat transfer mode,direction and amount of heat transfer in the motor are analyzed.In this paper,the equivalent heat network method is adopted to establish the profile model of the motor,and then the profile is divided into grids to analyze the heat transfer process and mode of each node.The heat matrix equation is established and the temperature field is calculated and solved by programming,so as to determine the internal temperature distribution of the motor.The feasibility of the method and the calculation process is verified by the temperature rise experiment.Finally,the motor is optimized.In this paper,starting from the development of traditional motor optimization design and the latest development,genetic algorithm is used to optimize the motor design.Firstly,the motor to be optimized is modeled and the objective function to be optimized is determined.The optimization variables are then selected and constraints are set.Finally,the validity and feasibility of the optimization method are verified by comparison with the results before optimization. |