# An Investigation of Parameter Dimension Reduction Optimization of PMA-Synrm
## 1 Introduction
[17] optimized the design of a switched reluctance motor. The optimization parameters include motor body design parameters and motor control system parameters. According to the sensitivity of the parameters, the 10 optimization parameters are divided into three layers, and the multi-objective genetic algorithm is used for hierarchical optimization design. Ref. [18] proposed that the multi-objective genetic algorithm is used to optimize the design parameters of seven stator and rotor structures of a three-layer magnetic barrier permanent magnet-assisted synchronous reluctance motor. In the selection of optimization parameters, only some parameters that are considered to have a greater impact are selected, and the full-parameter influence of the permanent magnet-assisted synchronous reluctance motor is not considered. Refs. [19, 20] shows that the optimization design of an asynchronous starting synchronous reluctance motor adopts the optimization method of the response surface. There are only three optimization parameters selected in this paper, and there is no clear explanation for the selection of optimization parameters. Only a few optimization parameters can achieve the optimization design when considering all the parameters. Ref. [21] optimizes the design of a three-layer magnetic barrier permanent magnet-assisted synchronous reluctance motor. Among them, the multi-objective genetic algorithm is used to optimize the rotor magnetic barrier of the permanent magnet-assisted synchronous reluctance motor. The nine magnetic barrier design parameters are divided into three levels according to the parameter sensitivity to optimize them respectively. The influence of parameters such as magnetic barrier thickness, permanent magnet length, and magnetic barrier bridge thickness is not considered in the selection of optimization parameters [22]. The multi-objective genetic algorithm is used to optimize the design of a permanent magnet-assisted synchronous reluctance motor with three-layer magnetic barriers, mainly to optimize the design parameters of magnetic barriers and permanent magnets. Eleven design parameters were selected for optimization, and the influence of magnetic bridge thickness was missing in the selection of optimization parameters. In addition, 11 optimization parameters will make the optimization process cumbersome and lengthy. It can be known from the above literature that the current research on the optimization design of a permanent magnet-assisted synchronous reluctance motor is mainly the exploration of optimization algorithms, and the optimization parameters selected in this literature are only a few, which is incomplete. The rotor design parameters of a permanent magnet-assisted synchronous reluctance motor are very many, and the parameters are coupled with each other, which jointly affect the performance of the motor. Therefore, it is not enough to select only a few parameters when optimizing the permanent magnet-assisted synchronous reluctance motor. The optimization of a permanent magnet-assisted synchronous reluctance motor should take into account comprehensiveness and globality. In this paper, the influence of rotor design parameters of a permanent magnet-assisted synchronous reluctance motor on the main performance of the motor is considered, and a parameter dimension reduction optimization method is provided. The optimization parameters are effectively reduced from 26 to 7, and the comprehensive global optimization of a permanent magnet-assisted synchronous reluctance motor is realized. In this paper, based on a 7.5 kW, 1500 rpm permanent magnet-assisted synchronous reluctance motor, the research on parameter dimension reduction optimization is carried out. In Section 2, the performance index of the permanent magnet-assisted synchronous reluctance motor and the initial design scheme and performance data of the motor are proposed.