散绕组电机改进型采样算法及其运行状态评估  

Improved Sampling Algorithm and Operational State Evaluation of Scattered Winding Motor

作　　者：付晓军[1] Fu Xiaojun(Xiantao Vocational College,Xiantao Hubei 433000,China)

机构地区：[1]仙桃职业学院,湖北仙桃433000

出　　处：《电气自动化》2022年第2期4-6,10,共4页Electrical Automation

基　　金：2017年度湖北省教育厅科学研究计划指导性项目“基于移动互联和CAN总线的汽车远程控制终端设计”(B2018533)。

摘　　要：针对当前散绕组电机模型测量精度不高、误差率过大等问题,设计了改进型SVPWM算法采样模型。将频率因素与正交改进型VPWM算法相结合,使定子磁链旋转速度与转子磁链旋转速度在空间中表现出来,在减少模型复杂性的同时,对模型中出现的误差进行控制。通过使用SVPWM算法与三角窗加权采样算法相结合的方式,对散绕组电机在相对频偏下的相对误差进行分析。通过构建灰色系统模型实现散绕组电机运行状态评估,提高了电机监控力度。试验结果表明,算法相对误差小,评估精确度高。Aiming at the problems of low measurement accuracy and large error rate of the current scattered winding motor model,an improved SVPWM algorithm sampling model was designed.Combining the frequency factor with the orthogonal modified VPWM algorithm,the stator flux rotation speed and the rotor flux rotation speed are expressed in space,which reduces the complexity of the model and also controls the errors in the model.By using the combination of SVPWM algorithm and triangular window weighted sampling algorithm,the relative errors of the scattered winding motor under the relative frequency deviation are analyzed.And by constructing a gray system model to evaluate the running state of the scattered winding motor,the monitoring degree of the motor has been at the end.The experimental results show that the relative errors are small and the evaluation accuracy is high.

关 键 词：散绕组电机 模型变换 SVPWM算法 采样算法 误差分析 

分 类 号：TM35[电气工程—电机]