Sensorless Control of Permanent Magnet Motor for Electric Tractor Based on Fuzzy Sliding Mode Observer

Developing electricized and intelligent modern agricultural equipment system and improving the modernization level of agricultural equipment is one of the important measures to vigorously promote the comprehensive revitalization of rural areas and quickly realize the “modernization of agriculture and rural areas”. Because of its potential advantages of green, intelligent and efficient, electric tractors have become one of the effective means to support the green and sustainable development of agriculture and ensure the safety of food production. Among them, as the core and key of electrification technology of tractor, driving motor is the power source of electric tractor, which directly determines the operation efficiency and tillage quality of the whole machine. The closed-loop control system of permanent magnet motor needs accurate rotor position information, while the reliability of traditional mechanical sensors is difficult to guarantee under bad working conditions. In order to improve the system reliability, the sensorless control method was studied. In the traditional sensorless control based on sliding mode observer, the problem of poor parameter robustness and stability seriously affected the control effect of sensorless operation. Therefore, a sensorless control method based on fuzzy sliding mode observer and fuzzy phase-locked loop was proposed to effectively solve this problem. Firstly, fuzzy controller was used to process the control parameters of the sliding mode observer and phase-locked loop, and these parameters were adjusted in real time according to the actual working conditions of the motor. Secondly, the recursive least squares adaptive linear harmonic extractor was used to effectively filter the high harmonic component of the back electromotive force, which avoided the influence of the high frequency component on the observed results. The experimental results showed that the proposed control method can improve the accuracy of speed and position estimation. © 2023 Chinese Society of Agricultural Machinery. All rights reserved.