{"title":"Dual-Sliding-Mode-Observer-Based IPMSM Sensorless Control Technique","authors":"Sang Xu, Anwen Shen, Mingzhen Zhang, Qipeng Tang, Xin Luo, Jinbang Xu","doi":"10.1155/2024/5512231","DOIUrl":null,"url":null,"abstract":"<div>\n <p>Back electromotive force (EMF)-based sliding mode observer (SMO) is increasingly employed for interior permanent magnet synchronous machine (IPMSM) sensorless drives due to its high robustness to external disturbance and low sensitivity to system parameter variations. However, its control performance is severely weakened by the inherent chattering and speed iteration operation. In order to effectively resolve these problems, a strategy to design a dual-SMO is proposed in this paper. With the proposed strategy, the combination of the stator-voltage transformation matrix (SVTM) and the low-pass filter is developed to obtain the rotor position information, which greatly alleviates the chattering without any deviations. Meanwhile, three independent equations are constructed and extracted by placing two SVTMs in different locations. By solving these three equations, the rotor position can be calculated directly with zero phase shift, which eliminates the speed iteration operation and improves the system’s dynamic performance. Furthermore, by analyzing the influences of machine parameters’ variations, the suitable virtual <i>q</i>-axis inductance can be selected to quickly achieve the optimal-efficiency sensorless control of the IPMSM. Finally, the experimental results on an IPMSM demonstrate that the rotor position with good steady-state and dynamic performance can be obtained accurately by using the proposed sensorless control strategy.</p>\n </div>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/5512231","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Complexity","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/5512231","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Back electromotive force (EMF)-based sliding mode observer (SMO) is increasingly employed for interior permanent magnet synchronous machine (IPMSM) sensorless drives due to its high robustness to external disturbance and low sensitivity to system parameter variations. However, its control performance is severely weakened by the inherent chattering and speed iteration operation. In order to effectively resolve these problems, a strategy to design a dual-SMO is proposed in this paper. With the proposed strategy, the combination of the stator-voltage transformation matrix (SVTM) and the low-pass filter is developed to obtain the rotor position information, which greatly alleviates the chattering without any deviations. Meanwhile, three independent equations are constructed and extracted by placing two SVTMs in different locations. By solving these three equations, the rotor position can be calculated directly with zero phase shift, which eliminates the speed iteration operation and improves the system’s dynamic performance. Furthermore, by analyzing the influences of machine parameters’ variations, the suitable virtual q-axis inductance can be selected to quickly achieve the optimal-efficiency sensorless control of the IPMSM. Finally, the experimental results on an IPMSM demonstrate that the rotor position with good steady-state and dynamic performance can be obtained accurately by using the proposed sensorless control strategy.
期刊介绍:
Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.