| 考虑铁损的永磁同步电机无位置传感器控制算法 |
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| 引用本文： | 曾小华,陈虹旭,崔臣,宋大凤. 考虑铁损的永磁同步电机无位置传感器控制算法[J]. 东北大学学报(自然科学版), 2021, 42(1): 102-110. DOI: 10.12068/j.issn.1005-3026.2021.01.016 |
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| 作者姓名： | 曾小华 陈虹旭 崔臣 宋大凤 |
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| 作者单位： | (吉林大学 汽车仿真与控制国家重点实验室, 吉林 长春130025) |
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| 摘 要： | 为开发有效可靠的永磁同步电机无位置传感器控制算法,针对考虑铁损电阻的电机等效电路模型,分别在d-q旋转坐标系和α-β静止坐标系下推导得到了扭矩电流状态微分表达式,在此基础上设计滑模观测器观测电机转速和转子位置信号.为验证观测效果,对两种坐标系下的无位置传感器算法进行了仿真和对比分析.根据d-q轴系下转子位置信号准确度低、α-β轴系下观测信号存在高频抖振但准确性高的特点,提出一种基于扩展卡尔曼滤波的融合观测算法.仿真结果表明,该融合观测算法的观测结果误差更小,且具有良好的动态特性,并通过实验验证了融合观测算法的有效性.
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| 关 键 词： | 永磁同步电机 铁损电阻 无位置传感器控制 扩展卡尔曼滤波 融合观测算法, |
Sensorless Control Algorithm for Permanent Magnet Synchronous Motors Considering Iron Loss |
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| ZENG Xiao-hua,CHEN Hong-xu,CUI Chen,SONG Da-feng. Sensorless Control Algorithm for Permanent Magnet Synchronous Motors Considering Iron Loss[J]. Journal of Northeastern University(Natural Science), 2021, 42(1): 102-110. DOI: 10.12068/j.issn.1005-3026.2021.01.016 |
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| Authors: | ZENG Xiao-hua CHEN Hong-xu CUI Chen SONG Da-feng |
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| Affiliation: | State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China. |
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| Abstract: | Aiming at developing an effective and reliable sensorless control algorithm for permanent magnet synchronous motors, for the equivalent circuit model considering iron loss resistance, the differential expression of the torque current state was derived under the d-q rotating axis system and the α-β stationary axis system. On this basis, a sliding mode observer was designed to estimate the speed and rotor position signals. In order to verify the observation effect, the sensorless algorithm was simulated and compared under the two axis systems. A fusion observation algorithm based on the extended Kalman filtering was proposed according to the characteristics of the low accuracy of the rotor position signal under the d-q axis system and the high frequency chattering of the signals under the α-β axis system. Simulation results showed that the fusion observation algorithm has less error and good dynamic characteristics. Besides, the effectiveness of the fusion observation algorithm was verified by experiments. |
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| Keywords: | permanent magnet synchronous motor(PMSM) iron loss resistance sensorless control extended Kalman filter fusion observation algorithm, |
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