一种基于飞电容腿混合NPC的多电平主动磁轴承驱动变换器

IF 7.2 1区工程技术 Q1 AUTOMATION & CONTROL SYSTEMS

IEEE Transactions on Industrial Electronics Pub Date : 2025-01-14 DOI:10.1109/TIE.2024.3525112

Jianfu Ding;Yuanhao Xie;Dong Jiang;Zicheng Liu;Yixuan Shuai;Mingqu Zhou

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引用次数: 0

摘要

多电平功率转换技术代表了电力电子领域的重大进步，而主动磁轴承驱动器是一种典型的电力电子设备。本文介绍了一种新型的混合中性点夹紧（NPC）多电平AMB驱动器，该驱动器包含一个飞行电容器（FC）分支，将传统的NPC结构与FC配置相结合。它将磁轴承（MB）绕组的电压等级从3级升级到5级，从而增强了系统的电压容量，并促进了更快的电流响应时间。此外，在相同电压水平下，该方法改善了AMB驱动的电磁干扰特性，减小了电流纹波和功率损耗，提高了MB的悬挂精度。在MB鼓风机实验平台上，该拓扑及其控制方法的有效性得到了严格验证，证明了其实用性和性能优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Novel Multilevel Converter as Active Magnetic Bearing Drive Based on Hybrid NPC With Flying-Capacitor Leg

Multilevel power conversion technology represents a significant advancement in the field of power electronics, and the active magnetic bearing (AMB) drive is a typical power electronics equipment. This article introduces a novel hybrid neutral point clamped (NPC) multilevel AMB drive that incorporates a flying-capacitor (FC) leg, merging traditional NPC structures with the FC configuration. It upgrades the voltage levels of the magnetic bearing (MB) windings from three to five levels, thereby enhancing the system's voltage capacity and facilitating swifter current response times. Additionally, at the same voltage level, this approach improves the electromagnetic interference (EMI) characteristics of the AMB drive, diminishes current ripple and power loss, and improves the suspension precision of the MB. The efficacy of the proposed topology and its control methods has been rigorously validated on a MB blower experimental platform, demonstrating their practical applicability and performance benefits.

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来源期刊

IEEE Transactions on Industrial Electronics 工程技术-工程：电子与电气

CiteScore

16.80

自引率

9.10%

发文量

1396

审稿时长

6.3 months

期刊介绍： Journal Name: IEEE Transactions on Industrial Electronics Publication Frequency: Monthly Scope: The scope of IEEE Transactions on Industrial Electronics encompasses the following areas: Applications of electronics, controls, and communications in industrial and manufacturing systems and processes. Power electronics and drive control techniques. System control and signal processing. Fault detection and diagnosis. Power systems. Instrumentation, measurement, and testing. Modeling and simulation. Motion control. Robotics. Sensors and actuators. Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems. Factory automation. Communication and computer networks.