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作 者:何坚彪 张蔚[1] 翟良冠 HE Jianbiao;ZHANG Wei;ZHAI Liangguan(School of Electrical Engineering,Nantong University,Nantong 226019,Jiangsu Province,China;Bosch Innovation Software Development(Wuxi)Co.,Ltd.,Wuxi 214000,Jiangsu Province,China)
机构地区:[1]南通大学电气工程学院,江苏省南通市226019 [2]博世创新软件开发(无锡)有限公司,江苏省无锡市214000
出 处:《中国电机工程学报》2023年第3期1189-1199,共11页Proceedings of the CSEE
基 金:国家自然科学基金项目(51507087);江苏省六大人才高峰项目(XNYQC-017);江苏省自然科学基金项目(BK20211332)。
摘 要:为了提高轴向磁场磁通切换永磁(axial field fluxswitching permanent magnet,AFFSPM)电机无位置传感器位置检测精度,同时抑制该电机的转矩和磁链脉动,该文提出一种基于改进滑模观测器(sliding mode observer,SMO)的无位置传感器AFFSPM电机模型预测磁链控制方法。首先,基于传统滑模观测器,设计边界层可随滑模面误差自调节的反正弦饱和函数,削弱系统抖振,改善系统稳态性能;接着,将扩展卡尔曼滤波器及幅值补偿环节代替单一低通滤波器,并通过内嵌二阶广义积分器的软件锁相环估算转子位置角和速度,消除位置角补偿,提高位置观测精确度;最后,将估算的转子位置角和速度反馈到模型预测磁链控制模块,完成无位置传感器控制。该文通过理论推导、仿真与实验研究验证所提出的控制策略可有效提高AFFSPM电机无传感器控制的稳态和动态性能。A sensorless model predictive flux control method based on improved sliding mode observer(SMO)is proposed in order to improve the accuracy of the position detection for the sensorless control of axial field flux-switching permanent magnet(AFFSPM)machine,and to suppress the torque and flux ripple of the machine.First,based on the traditional sliding mode observer,an arcsin saturation function whose boundary layer is self-adjusting with the sliding mode surface error is designed to weaken the system chattering and improve the system steady-state performance.Then,an extended Kalman filter with amplitude compensation is introduced to replace the low-pass filter,and a software phase-locked loop is used to estimate the rotor position angle and speed,so that the position angle compensation is eliminated,and the accuracy of position observation is improved.Finally,the information of the estimated rotor position angle and speed are fed back to the model predictive flux control module to complete the sensorless control.In this paper,the proposed control method is validated by the theoretical derivation and the research of simulation and experiment to improve the static and dynamic performances of sensorless control for AFFSPM machine effectively.
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