用反电动势SMO估计永磁同步电机转子速度和定子电阻

Q3 Mathematics

International Journal of Sensors, Wireless Communications and Control Pub Date : 2023-02-14 DOI:10.2174/2210327913666230214101119

O. Saadaoui, O. Khlaief, M. Abassi, A. Chaari

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引用次数: 0

摘要

永磁同步电动机的无传感器低速控制一直是一个具有挑战性的课题。本文提出了一种基于反电动势滑模观测器(SMO)结构的永磁同步电机无传感器矢量控制方法。为了去除机械传感器，建立了一个反向EMF-SMO来估计永磁同步电机驱动器的转子位置和速度。SMO用s型函数代替符号函数，可以减少抖振现象。这种无传感器速度控制对定子电阻和系统噪声具有很高的灵敏度。为了提高无传感器矢量控制的鲁棒性，将反电动势- SMO技术用于定子电阻估计。在无传感器驱动中加入了一种新的定子电阻估计器，以补偿定子电阻变化的影响。通过实际实验验证了该方法在1.1 kw低速无传感器PMSM矢量控制下的有效性。

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Estimation of rotor velocity and stator resistance for PMSM drive using Back-EMF SMO

Sensorless control of permanent magnet synchronous motor (PMSM) at low speed remains a challenging task. In this paper, a sensorless vector control of PMSM using a new structure of a back EMF sliding mode observer (SMO) is proposed. To remove the mechanical sensors, a back EMF-SMO is built to estimate the rotor position and speed of PMSM drives. The SMO, which replaces a sign function with a sigmoid function, can reduce the chattering phenomenon. This sensorless speed control shows great sensitivity to stator resistance and system noise. To improve the robustness of sensorless vector control, the back EMF- SMO technique has been used for stator resistance estimation. A novel stator resistance estimator is incorporated into the sensorless drive to compensate for the effects of stator resistance variation. The validity of the proposed SMO with a 1.1 kw low-speed PMSM sensorless vector control has been demonstrated by real experiments.

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来源期刊

International Journal of Sensors, Wireless Communications and Control Engineering-Electrical and Electronic Engineering

CiteScore

2.20

自引率

0.00%

发文量

期刊介绍： International Journal of Sensors, Wireless Communications and Control publishes timely research articles, full-length/ mini reviews and communications on these three strongly related areas, with emphasis on networked control systems whose sensors are interconnected via wireless communication networks. The emergence of high speed wireless network technologies allows a cluster of devices to be linked together economically to form a distributed system. Wireless communication is playing an increasingly important role in such distributed systems. Transmitting sensor measurements and control commands over wireless links allows rapid deployment, flexible installation, fully mobile operation and prevents the cable wear and tear problem in industrial automation, healthcare and environmental assessment. Wireless networked systems has raised and continues to raise fundamental challenges in the fields of science, engineering and industrial applications, hence, more new modelling techniques, problem formulations and solutions are required.