Application Of Particle Swarm Optimization In Optimization Design Of High Density Permanent Magnet Motor For Vehicle

With the development of the times and the increasing awareness of environmental protection,many automobile companies have replaced the internal combustion engine with electric motors,so the electrification of cars is a trend.All kinds of motor power consumption in a very important part of the world energy consumption,in response to energy saving plan and the implementation of the national energy conservation and emissions reduction and industry,high density permanent magnet motor become the main new energy electric vehicle power system,optimize the efficiency of the motor and industrial upgrading has become one of hot topics in the study of scholars at home and abroad.Permanent magnet motor has small volume,light quality,high control precision and the torque density is big,smooth and excellent performance and motor torque advantage such as less noise at work,at the same time,permanent magnet motor because of its permanent magnet magnetic circuit structure makes its weak magnetic is strong,increase the speed range of the motor,so for an electric car permanent magnet motor as a driving force to lay a certain foundation.Permanent magnet motor can not need external energy to maintain its magnetic field,but it is hard to adjust the control voltage from outside and related power factor,so the speed control of permanent magnet motor will not be able to change the form of excitation is used to implement,because of its rare earth permanent magnet motor of the cost of the permanent magnet is expensive,more strict with the temperature of the work environment at the same time,when the temperature is too a certain temperature,will be irreversible and the risk of failure,at the same time because of the motor in its work and hard to control temperature can also lead to rupture,so the coating of surface material demand is also quite high.Mainstream new energy vehicles requires optimizing the efficiency of the motor control system,such as improve the efficiency of the motor,the temperature of the related components estimation and design,at the same time also require permanent magnet motor has high security,high level of EMC,high voltage,high power density and related devices,integrated and customized motor and motor performance between various components can not only promote each other,also conflict each other,mutual constraints,make it hard for permanent magnet motor to realize manual optimization design.Particle swarm optimization(PSO)is an efficient computational method.The particle swarm optimization algorithm is simple and easy to implement,without adjusting many parameters and other advantages.Motor optimization design is a kind of optimization of the related parameters,because the process is complicated,the traditional algorithm is difficult to meet the global optimal,in order to make permanent magnet motor is more efficient,lower cost,this paper through the particle swarm algorithm to optimize design permanent magnet motor with high density,self optimization related parameters,the permanent magnet motor in the case of no more than rated voltage,torque have been increased,the temperature also be reduced.This paper mainly designs and optimizes the structure and key parameters of high density permanent magnet motor,and conducts the following research:1.Optimization and design research status of permanent magnet motor at home and abroad and introduction of future development;An improved particle swarm optimization algorithm(PSO)is analyzed to optimize the key parameters of the permanent magnet motor with this particle swarm optimization algorithm.2.Study and analyze the design theory of permanent magnet motor for electric vehicles,establish a mathematical model of permanent magnet motor,and prepare for the optimization of permanent magnet motor for vehicle;3.The key dimensions of permanent magnet motor(motor armature(stator)diameter,core of effective length,etc.)as optimization variables,through setting and the scope of optimized variables as constraint condition to choose effective optimization variables,build on electromagnetic torque calculation formula and the calculating formula of the temperature rise of the key parts as the target function,then the multi-objective function is optimized.The optimization design of the permanent magnet motor in electric vehicle is obtained through the improved particle swarm optimization algorithm,and the optimum design method is obtained for the maximum torque under the temperature rise condition of the key part of the motor.4.Subject to explore through a large number of experiments,according to the related parameters of the prototype,a series of parameters is obtained by Ansys maxwell and Motor CAD simulation of the simulation diagram,then use Ansys and maxwell Motor CAD related parameters obtained by the optimized simulation,contrast prototype parameters the simulation diagram,and Motor parameters to optimize algorithm applied in the Motor optimization and practicality.