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http://dx.doi.org/10.6113/JPE.2017.17.2.358

A Novel Filtering Method Based on a Nonlinear Tracking Differentiator for the Speed Measurement of Direct-drive Permanent Magnet Traction Machines  

Wang, Gaolin (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Wang, Bowen (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Zhao, Nannan (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Xu, Dianguo (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Publication Information
Journal of Power Electronics / v.17, no.2, 2017 , pp. 358-367 More about this Journal
Abstract
This paper presents a novel filtering method for speed measurements to improve the low-speed performance of the direct-drive permanent magnet traction machines for elevators. Based on the theory of nonlinear tracking differentiator (NTD), this method, which can act as a high performance filter of a raw speed signal, obtains a more accurate speed feedback signal when applying a low-resolution encoder. In addition, it can relieve the interference caused by the position derivative for speed sampling. By analyzing the frequency response of the NTD, the influence of its parameters on the performance of the speed filtering is investigated. Compared with different types of low-pass filters, the proposed method shows a shorter time delay and a stronger ability in terms of noise suppression when the parameters are selected carefully. In addition, when using the measured speed signal through a nonlinear tracking differentiator as the feedback of the system, the motor runs more steadily at low speeds. As a result, the riding comfort of a direct-drive elevator can be improved. The feasibility of the proposed strategy was verified on an 11.7kW elevator traction machine using a commercial inverter.
Keywords
Elevator; Low speed; Nonlinear tracking differentiator; Permanent magnet traction machine; Speed measurement;
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Times Cited By KSCI : 2  (Citation Analysis)
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