Multi-objective Optimization Design Of Permanent Magnet Synchronous Motor

The development direction of the manufacturing industry today is to closely integrate industrial automation and information,technology.As one of the most important power sources in industrial automation production,permanent magnet synchronous motors have been extensively studied for their optimization design issues.However,due to the different working environment and design specifications,the design of permanent magnet synchronous motors has become a constrained problem.To solve this problem,in addition to using traditional optimization methods such as the control variable method,step-by-step optimzation method,and comparative experiment method,combining heuristic algorithm with multi-objective optimization is also one of the important research directions.The algorithms used in the current research all need to have certain control parameters,or it is difficult to deal with the conflicts between the optimization goals.Therefore,this paper proposes a multi-objective comprehensive teaching algorithm and carries out a multi-objective optimization design of permanent magnet synchronous motor based on the weighting method and Pareto solution set respectively.The main research contents and results are as follows:(1)The electromagnetic relationship model of radial and axial permanent magnet synchronous motors is analyzed and summarized,and the induced electromotive force,electromagnetic torque,and air gap magnetic flux density are derived.On this basis,the working environment of the motor to be designed is analyzed,and different motor parameters are selected as variables,objective functions,and constraints.(2)For the basic teaching-learning-based optimization algorithm,this article introduces the concept of comprehensive teaching in the teacher stage according to the actual situation of the permanent magnet synchronous motor;in the value of the coefficient,the random value is changed to a more scientific formula;the adaptive learning times and the two-way learning process are proposed in.Through these changes,a multi-objective comprehensive teaching algorithm is obtained,and the calculation process is separately planned based on the weighted sum method and the Pareto optimal solution set.(3)The multi-objective optimization design of radial and axial flux permanent magnet synchronous motors is carried out according to the two calculation processes,and the performance improvement with other heuristic algorithms is compared.The calculated optimal values of the motor parameters were used for Maxwell finite element simulation and prototype experiment verification,and the conclusions in each design were analyzed and summarized.(4)In the optimization based on the weighted summation method to convert multi-objective into single-objective,the efficiency of multi-objective comprehensive teaching algorithm is relatively limited compared with teaching-learning based optimization algorithm,genetic algorithm,and particle swarm algorithm.In the optimization design based on the Pareto solution set,the efficiency of the multi-objective comprehensive teaching algorithm is more obvious than that of the non-dominated sorting teaching-learning-based optimization algorithm and the non-dominated sorting genetic algorithm-2,which has been reflected in many experiments.Fast convergence speed,more uniform individual distribution,more diverse Pareto solution sets,and better optimization results.This paper verifies the effectiveness,simplicity,correctness,and enlightenment of the multi-objective comprehensive teaching algorithm in the multi-objective optimization of permanent magnet synchronous motors through optimization design comparison,simulation,and prototype experiments.It provides a new solution to the problem of multi-objective optimization of perm anent magnet synchronous motors,and is of great significance for improving the design quality of permanent magnet synchronous motors.