Estimated Position Correction Algorithm for Sliding Mode Observer of Surface Mounted Permanent Magnet Synchronous Motor Based on Variable Gain Steepest Gradient Descent Method
Wang Yiming, Zhang Xuefeng, Gao Longjiang, Xu Qiwei, Luo Lingyan
State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing 400044 China
Abstract:Due to its high robustness and simplicity, sliding mode observer (SMO) has been widely used in sensorless control of surface mounted permanent magnet synchronous motor (SPMSM) at medium and high speeds. However, various non-ideal factors in actual control systems will lead to calculation errors and control delays, which will seriously affect the position estimation accuracy of SMO. To solve the above problem, this paper first analyzes the mechanism of position estimation error, and establishes the mathematical model in the error coordinate; Then, the steepest gradient descent position error observer based on nonlinear flux observer is proposed, and the variable gain cyclic iteration method is proposed to improve the speed and accuracy of the estimated position correction process. Finally, the accuracy and robustness of the proposed algorithm are verified through an SPMSM experimental platform. Firstly, the SMO principle and the rotor position estimation error mechanism in SPMSM sensorless control system are analyzed. Secondly, the mathematical model including the estimated position error is established at the observation error coordinate system(γ-δ frame). Thirdly, a rotor position error observer based on the steepest gradient descent method and nonlinear flux observer at the γ-δ frame is proposed, and the observer’s stability is proved. Finally, variable gain and one cycle iterative algorithm are proposed to improve the speed of the position correction process. Because the proposed observer only needs the rotor angle and speed information calculated by the SMO, it has no coupling with the current control loop and can be configured and adjusted more conveniently. Experimental results on the 750 W SPMSM experimental platform show that, when the load torque is kept at 0.5 N∙m and the speed is adjusted from 800 rad/s to 3 000 rad/s, the maximum rotor position error is 2° and the average error is 0°. At 3 000 rad/s, when the load torque increases from 0.5N∙m to 2.4 N∙m (rated torque), the maximum rotor position error is 3°; after the speed is stable, the average error is 0° and the maximum error is 2°. When the estimated angle of the rotor suddenly changes ± 10 °, the position error corrected by the observer is reduced to within 1° within 4ms. During the parameter sensitivity bench test, the resistance changes by ± 50%, and the position error deviate from the center point by ±1.5°. The inductance changes by ±50%, and the position error deviates from the center point by ±2.5°. Then the theoretical analysis of parameter sensitivity is carried out. The analysis results show that the maximum position error of 5.13° occurs at the lowest speed and maximum current when the resistance changes, and the maximum position error of 3.77° occurs at the maximum current when the inductance changes. The following conclusions can be drawn from the experimental results and theoretical analysis: (1) The proposed algorithm can be configured and adjusted conveniently, due to the decoupling of SMO and the current control loop. (2) The proposed algorithm can effectively track the position error when changing speed and load. In case of a sudden change of angle, it can realize rapid observation of angle error. (3) The proposed algorithm has good robustness when the resistance and inductance parameters change.
王益明, 张雪锋, 高龙将, 徐奇伟, 罗凌雁. 基于变增益最速梯度下降法的表贴式永磁同步电机滑模观测估算位置修正策略[J]. 电工技术学报, 0, (): 106-106.
Wang Yiming, Zhang Xuefeng, Gao Longjiang, Xu Qiwei, Luo Lingyan. Estimated Position Correction Algorithm for Sliding Mode Observer of Surface Mounted Permanent Magnet Synchronous Motor Based on Variable Gain Steepest Gradient Descent Method. Transactions of China Electrotechnical Society, 0, (): 106-106.
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