@inproceedings{aea5318001ee41f9874207718ceafc7e,
title = "Estimation of Unbalance Mass for Sensorless Electric Drive System Based on Sliding Mode Observer and FFT",
abstract = "The unbalance mass may cause the decentration and vibration adversely affecting the working performance and service life of the rotating machinery equipped in sensorless electric drive systems, such as fans and drum washing machines. The unbalance mass is almost inevitable, and it's difficult to estimate it due to the lack of corresponding sensors. This paper proposes an estimation scheme of unbalance mass for sensorless electric drive systems equipped with rotating machineries. A sliding mode observer is implemented to determine the rotor position and velocity information. The overall moment of inertia is computed by the fast Fourier transform method. The unbalance mass is estimated according to the dynamic model of motors and the values obtained above. Simulations and experimental validations demonstrate that the proposed estimation scheme can achieve accurate estimation of the unbalance mass in spite of variation of balanced loads.",
keywords = "Rotating machinery, Sensorless electric driving system, Sliding mode observer, Unbalance mass",
author = "Yiyan Su and Deliang Liang and Peng Kou",
note = "Publisher Copyright: {\textcopyright} 2020 The Institute of Electrical Engineers of Japan.; 23rd International Conference on Electrical Machines and Systems, ICEMS 2020 ; Conference date: 24-11-2020 Through 27-11-2020",
year = "2020",
month = nov,
day = "24",
doi = "10.23919/ICEMS50442.2020.9291007",
language = "英语",
series = "23rd International Conference on Electrical Machines and Systems, ICEMS 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "545--549",
booktitle = "23rd International Conference on Electrical Machines and Systems, ICEMS 2020",
}