@inproceedings{a83d56fe02d94b0a9c3ac474fd4390f0,
title = "Harmonic Suppression Method of Motor Drive System Based on Full-Order Extended Kalman Filter",
abstract = "Aiming at the problem that the position sensor and current sensor may be disturbed by noise and the error of the sensor feedback measurement value caused by the fault of the sensor itself leads to the performance degradation of the motor drive system, this paper constructs a full-order state observer based on the extended Kalman filter (EKF) algorithm, and proposes a current harmonic suppression algorithm for the motor drive system. The position and current signals obtained by the state observer are fused with the actual position and current signals measured by the sensor to minimize the motor current and position signal errors. The simulation results show that the proposed method is superior to the traditional method, which can effectively improve the current waveform and reduce the total harmonic distortion (THD) of the motor phase current.",
keywords = "EKF, Harmonic Suppression, THD",
author = "Nianzhong Zhang and Qiang Song",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 2nd CCF Intelligent Vehicles Symposium, CIVS 2024 ; Conference date: 19-10-2024 Through 20-10-2024",
year = "2025",
doi = "10.1007/978-981-95-0848-8\_7",
language = "English",
isbn = "9789819508471",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "74--85",
editor = "Huiyun Li and Peng Sun and Daxin Tian and Zhengguo Sheng and Victor Leung and Huaxia Xia and Yong Hong",
booktitle = "Intelligent Vehicles - 2nd CCF Intelligent Vehicles Symposium, CIVS 2024, Revised Selected Papers",
address = "Germany",
}