扩展卡尔曼滤波在无传感器同步磁阻电机驱动中的自动调谐

IF 5 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Saverio Rigon;Benedikt Haus;Paolo Mercorelli;Mauro Zigliotto
{"title":"扩展卡尔曼滤波在无传感器同步磁阻电机驱动中的自动调谐","authors":"Saverio Rigon;Benedikt Haus;Paolo Mercorelli;Mauro Zigliotto","doi":"10.1109/OJPEL.2025.3546752","DOIUrl":null,"url":null,"abstract":"A substantial reduction in the human environmental footprint can be achieved through the use of more efficient motors, such as synchronous reluctance motors (SynRM). As low-cost motors, SynRMs are commonly employed in sensorless AC drives. Sensorless algorithms based on the Extended Kalman Filter (EKF) offer several advantages, but they require a time-consuming trial-and-error tuning procedure. This paper proposes the automatic tuning of the EKF through a second Kalman Filter (KF) in a primary–secondary (PS) configuration. The two KFs work concurrently: the first estimates the required quantities for machine control, and the second updates the process noise statistics of the first KF. The second KF is much easier to tune, requiring only one non-critical parameter. Experimental results confirm the validity of this approach.","PeriodicalId":93182,"journal":{"name":"IEEE open journal of power electronics","volume":"6 ","pages":"734-746"},"PeriodicalIF":5.0000,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10907945","citationCount":"0","resultStr":"{\"title\":\"Automatic Tuning of Extended Kalman Filter in Sensorless Synchronous Reluctance Motor Drives\",\"authors\":\"Saverio Rigon;Benedikt Haus;Paolo Mercorelli;Mauro Zigliotto\",\"doi\":\"10.1109/OJPEL.2025.3546752\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A substantial reduction in the human environmental footprint can be achieved through the use of more efficient motors, such as synchronous reluctance motors (SynRM). As low-cost motors, SynRMs are commonly employed in sensorless AC drives. Sensorless algorithms based on the Extended Kalman Filter (EKF) offer several advantages, but they require a time-consuming trial-and-error tuning procedure. This paper proposes the automatic tuning of the EKF through a second Kalman Filter (KF) in a primary–secondary (PS) configuration. The two KFs work concurrently: the first estimates the required quantities for machine control, and the second updates the process noise statistics of the first KF. The second KF is much easier to tune, requiring only one non-critical parameter. Experimental results confirm the validity of this approach.\",\"PeriodicalId\":93182,\"journal\":{\"name\":\"IEEE open journal of power electronics\",\"volume\":\"6 \",\"pages\":\"734-746\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2025-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10907945\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE open journal of power electronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10907945/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE open journal of power electronics","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10907945/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

通过使用更高效的电机,如同步磁阻电机(SynRM),可以大幅减少人类的环境足迹。作为低成本电机,synrm通常用于无传感器交流驱动。基于扩展卡尔曼滤波(EKF)的无传感器算法有几个优点,但它们需要一个耗时的试错调整过程。本文提出了在主-辅(PS)结构中通过第二个卡尔曼滤波器(KF)对EKF进行自动调谐的方法。两个KF同时工作:第一个估计机器控制所需的数量,第二个更新第一个KF的过程噪声统计。第二个KF更容易调优,只需要一个非关键参数。实验结果证实了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Tuning of Extended Kalman Filter in Sensorless Synchronous Reluctance Motor Drives
A substantial reduction in the human environmental footprint can be achieved through the use of more efficient motors, such as synchronous reluctance motors (SynRM). As low-cost motors, SynRMs are commonly employed in sensorless AC drives. Sensorless algorithms based on the Extended Kalman Filter (EKF) offer several advantages, but they require a time-consuming trial-and-error tuning procedure. This paper proposes the automatic tuning of the EKF through a second Kalman Filter (KF) in a primary–secondary (PS) configuration. The two KFs work concurrently: the first estimates the required quantities for machine control, and the second updates the process noise statistics of the first KF. The second KF is much easier to tune, requiring only one non-critical parameter. Experimental results confirm the validity of this approach.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
8.60
自引率
0.00%
发文量
0
审稿时长
8 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信