基于径向基神经网络潜油永磁同步电机优化设计

An Optimization Design of Submersible Permanent Magnet Synchronous Motor(SPMSM) Based on Radial Basis Function(RBF) Network

电机优化设计的主要目标就是提高电机工作效率,降低电机齿槽转矩。油田用潜油电机工作空间狭窄、散热环境恶劣,电机损耗产生的热量若不能及时散发,将对电机性能产生很大的影响。以114系列闭口槽12极36槽油田用低速潜油永磁同步电机为载体,对电机进行电磁参数的优化设计:首先提出影响潜油永磁同步电机损耗和齿槽转矩的电磁结构参数,并根据初始条件确定各参数的初始值以及取值范围;其次构建径向基神经网络数学模型并进行拟合分析;最后通过多目标优化方法得到让损耗较小,齿槽转矩较低的满意解。

The main goal of the motor optimization design is to improve motor efficiency and reduce the cog- ging torque. The working space of the submersible motor used in oil field is narrow, and the heat radiation environment is terrible. It will have a great impact on the performance of the motor if the heat generated by the motor can not be distributed in time. The optimization of electromagnetic parameters is based on a low speed PMSM with the series of 114, 12 poles and 36 closed slots. Firstly, the main electromagnetic parameters which can influence the motor efficiency and cogging torque is proposed, and the initial value and range of parameters are ensured according to the initial condition at the same time. And then building an RBF network mathematic model and fitting analysis. Finally, getting the satisfaction solution that makes the loss is small and the cogging torque is low through method of multi--objective optimization.