Online Multiparameter Estimation With Position Error Correction for Unified Synchronous Machine Sensorless Drives

IF 4.5 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Industry Applications Pub Date : 2024-10-03 DOI:10.1109/TIA.2024.3473898
Zirui Liu;Wubin Kong;Hengyang Liu;Kai Peng;Fei Wang;Xinggang Fan;Ronghai Qu
{"title":"Online Multiparameter Estimation With Position Error Correction for Unified Synchronous Machine Sensorless Drives","authors":"Zirui Liu;Wubin Kong;Hengyang Liu;Kai Peng;Fei Wang;Xinggang Fan;Ronghai Qu","doi":"10.1109/TIA.2024.3473898","DOIUrl":null,"url":null,"abstract":"For model-based sensorless drives in synchronous machines (SMs), real-time parameter information is essential for accurate position observation. Considering the challenges in fundamental frequency model-based parameter estimation, this article presents an online multiparameter estimation method. The adaptive robust observer in the misaligned synchronous frame small signal model for unified SMs is designed to mitigate the position observation error caused by parameter mismatches. The small signal model, derived from flux linear assumption, effectively accounts for the <italic>dq</i>-axis magnetic path asymmetry. With extra small-signal excitation guaranteed by the persistent excitation (PE) condition analysis, the estimated parameters are proven to converge to their actual value under sensorless control within the rated speed. Additionally, a robust feedback function is designed to address the speed fluctuations related to fundamental flux linkage, mitigating their influence on parameter estimation results. For isotropic SMs, the estimated parameters are directly utilized in the model-based observer. For anisotropic SMs, an optimizer is introduced to locate the <italic>dq</i>-axis inductance from the coupled inductance matrix in the misaligned synchronous frame. The effectiveness of the proposed method is evaluated through sufficient experiments, showing position observation error within 0.1 rad for IPMSM and SPMSM and 0.15 rad for SynRM.","PeriodicalId":13337,"journal":{"name":"IEEE Transactions on Industry Applications","volume":"61 1","pages":"345-358"},"PeriodicalIF":4.5000,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industry Applications","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10704951/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

For model-based sensorless drives in synchronous machines (SMs), real-time parameter information is essential for accurate position observation. Considering the challenges in fundamental frequency model-based parameter estimation, this article presents an online multiparameter estimation method. The adaptive robust observer in the misaligned synchronous frame small signal model for unified SMs is designed to mitigate the position observation error caused by parameter mismatches. The small signal model, derived from flux linear assumption, effectively accounts for the dq-axis magnetic path asymmetry. With extra small-signal excitation guaranteed by the persistent excitation (PE) condition analysis, the estimated parameters are proven to converge to their actual value under sensorless control within the rated speed. Additionally, a robust feedback function is designed to address the speed fluctuations related to fundamental flux linkage, mitigating their influence on parameter estimation results. For isotropic SMs, the estimated parameters are directly utilized in the model-based observer. For anisotropic SMs, an optimizer is introduced to locate the dq-axis inductance from the coupled inductance matrix in the misaligned synchronous frame. The effectiveness of the proposed method is evaluated through sufficient experiments, showing position observation error within 0.1 rad for IPMSM and SPMSM and 0.15 rad for SynRM.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
统一同步电机无传感器驱动的多参数在线估计及位置误差校正
对于同步电机(SMs)中基于模型的无传感器驱动器,实时参数信息对于精确的位置观测至关重要。针对基于基频模型的参数估计存在的问题,提出了一种在线多参数估计方法。设计了统一SMs同步帧小信号模型中的自适应鲁棒观测器,以减轻参数不匹配引起的位置观测误差。基于磁通线性假设的小信号模型有效地解释了dq轴磁路的不对称性。通过持续激励(PE)条件分析保证了额外的小信号激励,证明了在额定转速内无传感器控制下,估计参数收敛于实际值。此外,设计了一个鲁棒反馈函数来处理与基本磁链相关的速度波动,减轻其对参数估计结果的影响。对于各向同性SMs,估计参数直接用于基于模型的观测器。对于各向异性异步电动机,引入了一个优化器,从错位同步框架中的耦合电感矩阵中定位dq轴电感。通过充分的实验验证了该方法的有效性,IPMSM和SPMSM的位置观测误差在0.1 rad以内,SynRM的位置观测误差在0.15 rad以内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
IEEE Transactions on Industry Applications
IEEE Transactions on Industry Applications 工程技术-工程:电子与电气
CiteScore
9.90
自引率
9.10%
发文量
747
审稿时长
3.3 months
期刊介绍: The scope of the IEEE Transactions on Industry Applications includes all scope items of the IEEE Industry Applications Society, that is, the advancement of the theory and practice of electrical and electronic engineering in the development, design, manufacture, and application of electrical systems, apparatus, devices, and controls to the processes and equipment of industry and commerce; the promotion of safe, reliable, and economic installations; industry leadership in energy conservation and environmental, health, and safety issues; the creation of voluntary engineering standards and recommended practices; and the professional development of its membership.
期刊最新文献
IEEE Transactions on Industry Applications Publication Information IEEE Transactions on Industry Applications Publication Information Get Published in the New IEEE Open Journal of Industry Applications IEEE Transactions on Industry Applications Information for Authors IEEE Transactions on Industry Applications Information for Authors
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1