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基于改进SMO的永磁同步电机全速段位置估算研究 被引量:8

Research on position estimation of permanent magnet synchronous motorat full speed based on improved SMO
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摘要 为了改善传统滑模观测器(sliding mode observer, SMO)存在高频抖振、相位延迟、低速段失效等问题,提出一种改进SMO控制策略。该方法在低通滤波器之前引入一个放大因子,放大反电动势信号以便于提取估计;采用双曲正切函数替换符号函数,减少系统的高频抖振与信号干扰;采用自适应滤波器来提高检测精度,减小相位延迟。通过MATLAB/Simulink仿真分析比较了改进SMO和传统SMO两种策略,结果显示改进SMO相较于传统SMO相位延迟时间缩短了97.5%,并且能够显著减少抖振现象,精准估计20 r/min以下的电机转速,实现在全速段保持良好的估算性能,表明改进SMO策略具有更优的估算精度和适应性能。 In order to improve the problems of high-frequency chattering, phase delay, and low-speed failure in traditional sliding mode observers(SMO), this paper proposes an improved SMO control strategy. This method introduces an amplification factor before the low-pass filter to amplify the back-EMF signal for easy extraction and estimation;adopts the hyperbolic tangent function as the sign function to reduce the high-frequency chattering and signal interference of the system;adopts an adaptive filter to improve detection Accuracy, reduce phase delay. Through MATLAB/Simulink simulation analysis, the two strategies of improved SMO and traditional SMO are compared. The results show that the improved SMO reduces the phase delay time by 97.5% compared with the traditional SMO, and it can significantly reduce chattering phenomenon, and accurately estimate the motor below the speed of 20 r/min., to achieve good estimation performance at full speed, indicating that the improved SMO strategy has better estimation accuracy and adaptability.
作者 张港 高文根 杭孟荀 李鹏飞 裴同 Zhang Gang;Gao Wengen;Hang Mengxun;Li Pengfei;Pei Tong(Key Laboratory of Detection Technology and Energy Saving Devices of Anhui Province,Anhui Polytechnic University,Wuhu 241000,China;Chery New Energy Automobile Co,Ltd,Wuhu 241002,China)
出处 《电子测量与仪器学报》 CSCD 北大核心 2021年第7期185-193,共9页 Journal of Electronic Measurement and Instrumentation
基金 安徽省重点研究与开发计划项目(201904a05020007) 安徽省支持新能源汽车产业创新发展和推广应用项目 国家级大学生创新创业训练计划项目(202010363026)资助。
关键词 永磁同步电机 滑模观测器 双曲正切函数 放大因子K 自适应滤波器 仿真分析 permanent magnet synchronous motor sliding mode observer hyperbolic tangent function amplification factor K adaptive filter simulation analysis
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