An Optimi-ation Method for Turn-on and Turn-off Angles of Switched Reluctance Motors Using Kriging Model

doi:10.7652/xjtuxb202010011

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An Optimi-ation Method for Turn-on and Turn-off Angles of Switched Reluctance Motors Using Kriging Model

更新时间：2025-07-09

- An Optimi-ation Method for Turn-on and Turn-off Angles of Switched Reluctance Motors Using Kriging Model
- Vol. 54, Issue 10, Pages: 94-99+107(2020)
- 作者机构：
  
  上海交通大学机械与动力工程学院,上海,200240
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202010011
  CLC： TM352
- Online First：10 October 2020，
  
  Published：2020
- 稿件说明：
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An Optimi-ation Method for Turn-on and Turn-off Angles of Switched Reluctance Motors Using Kriging Model[J]. 2020, 54(10): 94-99+107.
DOI：

An Optimi-ation Method for Turn-on and Turn-off Angles of Switched Reluctance Motors Using Kriging Model[J]. 2020, 54(10): 94-99+107. DOI： 10.7652/xjtuxb202010011.

摘要

针对传统密集采样方法获得采用角度位置控制的开关磁阻电机最优开通角与关断角所需实验次数多、耗时长

效率低的问题

提出一种采用Kriging模型的最优开通角和关断角实验求取方法来减少实验采样次数

提高寻优效率。首先

通过少量的初始样本点建立开通角和关断角与电机振动加速度之间的预测模型; 之后

根据得到的预测模型有针对性地在最优开通角和关断角可能出现的区域进行采样计算; 最后

当区域缩小到满足精度要求的大小后

对该区域进行密集采样

从而快速准确发现最优开通角和关断角。实验结果表明

基于Kriging预测模型获取相同开关磁阻电机最优开通角和关断角(误差小于1%以内)所需样本数仅为传统的密集采样方法的12.4%

计算时间缩短了62.8%。因此

所提方法能显著提高开关磁阻电机的开通角和关断角寻优实验效率。

Abstract

An experimental method for turn-on and turn-off angles based on Kriging prediction model is proposed to solve the problem that the traditional intensive sampling method requires many experiments

long time and low efficiency to obtain optimal switching angles of switched reluctance motor controlled by angle position control strategy. First

a model to predict the relationship between the switching angles and the motor vibration is established via a small number of sample points. Then

prediction results from the model are used to the sampling and calculation in the area where the optimal switching angles probably exist. Finally

when the area is reduced to meet an accuracy requirement

intensive sampling is conducted in the area so as to rapidly and exactly obtain the optimal switching angles. Experimental results show that the number of samples used by the proposed method to obtain the optimal switching angle(error is less than 1%)of the same switched reluctance motor is only 12.4% of

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references

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