Research On Axial Excitation 9/6 Pole Doubly Salient Motor Based On Intelligent Optimization Algorithm

Axial excitation 9/6 pole doubly salient motor（9/6AEDSM）,as an improved type of doubly salient reluctance motor,has all the advantages of traditional doubly salient reluctance motor,with simple and robust structure and high reliability.The 9/6AEDSM is designed with two sets of stator and rotor structures.and the single set is a 9/6-pole doubly salient structure.The central coil is designed in the middle to substitute the permanent magnet to accomplish the aim of adjusting the magnetic field of the motor and surmount the problem of permanent magnet demagnetization.By adjusting the size and direction of the current passing through the central coil,the magnetization and weakening effects of the main magnetic field are achieved.The speed regulation performance of 9/6AEDSM is better than that of the traditional double salient motor,but there are still some problems in the motor body,such as large torque ripple and low efficiency.The main purpose of this thesis is the use of intelligent optimization algorithm for motor structure parameters optimization to decrease the torque ripple and enhance the efficiency of motor.9/6AEDSM nonlinear model is established by taking advantage of the way of magnetic circuit analysis.Based on the nonlinear model,the parameters that have a great influence on the torque ripple and efficiency of the motor are screened out through sensitivity analysis.In this thesis,the particle swarm algorithm（PSO）and the Beetle Antennae search algorithm（BAS）are combined with the nonlinear model to solve the multi-objective optimization of the motor,and another particle swarm optimization algorithm based on Beetle Antennae search algorithm（BAS-PSO）is proposed and applied to the optimization of motor.The three algorithms respectively obtain the motor structure parameters when the target is optimal and the three optimization results are compared and analyzed.The effect of the three algorithms in this optimization is verified by the finite element method.The specific process is as follows:Firstly,the research status of domestic and foreign doubly salient motor optimization,the application and research status of intelligent algorithms in motor optimization,and the research status of doubly salient motor modeling are expounded.Then,according to the theory and characteristics of 9/6AEDSM,the nonlinear modeling method of reluctance motor at home and abroad is used for reference,and the 9/6AEDSM is nonlinearly modeled by magnetic circuit analysis method.The magnetization curves of the four important positions of the motor are calculated,and the flux linkage-current-angle data table is obtained by fitting,and then the calculation formula of the steady-state performance of the motor is obtained.Next,the sensitivity analysis of plentiful design parameters of the motor is carried out through the nonlinear model,and the optimization variables used for optimization are acquired.Parametric scanning of the optimization variables is carried out to explain the influence of motor parameters on torque ripple and efficiency,and to determine the reasonable range of parameters.Finally,this thesis expounds the basic principles of BAS and PSO,combined with the characteristics of the two kinds of algorithm and the characteristics of the optimization model,a particle swarm algorithm based on beetles is proposed.The three kinds of algorithm act on the optimization model,and the optimized results are obtained.The results of the three algorithms for motor torque ripple and efficiency optimization are compared through finite element method analysis,and the good control performance of the central coil for the optimized motor is verified.