一种新型PMSM负载转矩和转动惯量辨识策略

doi:10.16180/j.cnki.issn1007-7820.2023.06.012

摘要/Abstract

摘要：

精确的负载转矩和转动惯量辨识是实现永磁同步电机高性能伺服控制的关键之一,而目前负载转矩和转动惯量的辨识多局限于其本身,未能联系到负载转矩和转动惯量之间的相互影响与制约。针对该问题,文中首先设计了一种互相连接的扩展滑模观测器,充分考虑负载转矩和转动惯量间的相互影响,并且将已辨识转动惯量值作用于电机速度环的比例系数和积分系数,使得两个扩展滑模观测器拥有更加精确和稳定的速度输入。然后,文中将新型策略与其他算法进行了对比分析,结果表明新型辨识策略使负载转矩和转动惯量的辨识拥有更快的响应能力和更好的辨识精度。此外,为了验证辨识系统的抗干扰能力和辨识的稳定性,基于变速和负载突变环境进行辨识,仿真结果表明即使在复杂环境下,文中所提的新型策略依旧具有较为稳定的辨识效果。

关键词: 永磁同步电机, 扩展滑模观测器, 负载转矩, 转动惯量, 参数辨识, 速度环, PI控制器, 自整定

Abstract:

Accurate identification of load torque and moment of inertia is one of the keys to realize high-performance servo control of permanent magnet synchronous motor. Currently, the identification of load torque and moment of inertia is mostly limited to itself, which is not related to the interaction and restriction between load torque and moment of inertia. In view of this problem, firstly, an interconnected extended sliding mode observer is designed, which fully considers the interaction between load torque and moment of inertia, and the identified moment of inertia is applied to the proportional coefficient and integral coefficient of motor speed loop, so that the two extended sliding mode observers have more accurate and stable speed input. The comparison between the proposed strategy and other algorithms show that the new identification strategy makes the identification of load torque and moment of inertia have faster response ability and better identification accuracy. In addition, in order to verify the anti-interference ability and identification stability of the identification system, the identification is carried out based on the variable speed and load mutation environment. The simulation results show that the new strategy in this study still has a relatively stable identification effect even in the complex environment.

Key words: permanent magnet synchronous motor, extended sliding mode observer, load torque, moment of inertia, parameter identification, speed loop, PI controller, self tuning

中图分类号:

TP202

朱凌童,蒋全. 一种新型PMSM负载转矩和转动惯量辨识策略[J]. 电子科技, 2023, 36(6): 80-86.

ZHU Lingtong,JIANG Quan. A Novel PMSM Load Torque and Moment of Inertia Identification Strategy[J]. Electronic Science and Technology, 2023, 36(6): 80-86.

图/表 11

图1

图2

图3

图4

图5

表1

图6

图7

图8

图9

图10

参考文献 18

[1]	周涛, 蒋全. 无传感器永磁同步电机全速范围控制技术综述[J]. 电子科技, 2021, 34(4):59-69.
	Zhou Tao, Jiang Quan. Overview of sensorless control technology for full speed range permanent magnet synchronous motors[J]. Electronic Science and Technology, 2021, 34(4):59-69.
[2]	李抑非, 蒋全. 永磁同步电机转子初始位置检测技术研究进展[J]. 电子科技, 2021, 34(4):24-33.
	Li Yifei, Jiang Quan. Research development of initial rotor position detection of permanent magnet synchronous motors[J]. Electronic Science and Technology, 2021, 34(4):24-33.
[3]	Zhang G, Furusho J. Speed control of two-inertia system by PI/PID control[J]. IEEE Transactions on Industrial Electronics, 2000, 47(3):603-609. doi: 10.1109/TIE.41
[4]	Zhang Y, Akujuobi C M, Ali W H, et al. Load disturbance resistance speed controller design for PMSM[J]. IEEE Transactions on Industrial Electronics, 2006, 53(4):1198-1208. doi: 10.1109/TIE.2006.878313
[5]	何晓会. 基于惯量辨识的永磁同步电机自抗扰控制策略研究[D]. 哈尔滨: 哈尔滨工业大学, 2020:40-50.
	He Xiaohui. Research on the active disturbance rejection control strategy of PMSM with inertia identification[D]. Harbin:Harbin Institute of Technology, 2020:40-50.
[6]	鲍文龙, 顾正皓, 高宽, 等. 基于卡尔曼滤波器的转子转动惯量计算方法[J]. 热能动力工程, 2020, 35(7):58-64.
	Bao Wenlong, Gu Zhenghao, Gao Kuan, et al. A calculation method for the rotor moment of inertia based on Kalman filter[J]. Journal of Engineering for Thermal Energy and Power, 2020, 35(7):58-64.
[7]	汤瑞洁. 基于自适应扩展卡尔曼滤波的永磁同步电机转动惯量辨识方法[D]. 西安: 西安理工大学, 2020:30-35.
	Tang Ruijie. Moment of inertia identification based on adaptive extended Kalman filter for interior permanent magnet synchronous motors[D]. Xi'an: Xi'an University of Technology, 2020:30-35.
[8]	Zhang C W, Yang T, Zhou G X, et al. Research on the identification of moment of inertia based on fuzzy rules for variable gain model reference adaptive[C]. Shanghai: Proceedings of the Chinese Automation Congress, 2020:5934-5937.
[9]	Song Z, Mei X S, Jiang Ge D. Inertia identification based on model reference adaptive system with variable gain for AC servo systems[C]. Takamatsu: IEEE International Conference on Mechatronics and Automation, 2017:188-192.
[10]	杜帅. 永磁同步电机转动惯量辨识研究[J]. 电机与控制应用, 2012, 39(4):17-22.
	Du Shuai. Research of inertia identification of permanent magnet synchronous motor servo system[J]. Electric Machines & Control Application, 2012, 39(4):17-22.
[11]	Lian C Q, Xiao F, Gao S, et al. Load torque and moment of inertia identification for permanent magnet synchronous motor drives based on sliding mode observer[J]. IEEE Transactions on Power Electronics, 2019, 34(6):5675-5683. doi: 10.1109/TPEL.63
[12]	Haridas A K, Vasudevan K. Design and analysis of load torque observer for high precision position control of PMSM[C]. Lisbon: IECON the Forty-fifth Annual Conference of the IEEE Industrial Electronics Society, 2019:998-1003.
[13]	Gong C, Hu Y H, Ni K, et al. SM load torque observer-based FCS-MPDSC with single prediction horizon for high dynamics of surface-mounted PMSM[J]. IEEE Transactions on Power Electronics, 2019, 35(1):20-24. doi: 10.1109/TPEL.2019.2929714
[14]	朱军, 李紫豪, 刘炳辰, 等. 基于自适应插值扩展卡尔曼滤波的永磁同步电机状态估计[J]. 电子科技, 2020, 33(5):66-71.
	Zhu Jun, Li Zihao, Liu Bingchen, et al. State estimation of permanent magnet synchronous motor based on adaptive interpolation extended Kalman filter[J]. Electronic Science and Technology, 2020, 33(5):66-71.
[15]	Zhang X G, Li Z X. Sliding-mode observer-based mechanical parameter estimation for permanent magnet synchronous motor[J]. IEEE Transactions on Power Electronics, 2016, 31(8):5732-5745. doi: 10.1109/TPEL.2015.2495183
[16]	Lu W Q, Zhang Z Y, Wang D, et al. A new load torque identification sliding mode observer for permanent magnet synchronous machine drive system[J]. IEEE Transactions on Power Electronics, 2019, 34(8):7852-7862. doi: 10.1109/TPEL.63
[17]	赵国鹏. 永磁同步电机运动学参数辨识算法研究[D]. 哈尔滨: 哈尔滨工业大学, 2016:38-59.
	Zhao Guopeng. Research on kinematic parameter identification algorithm of PMSM[D]. Harbin:Harbin Institute of Technology, 2016:38-59.
[18]	Yang C B, Song B, Xie Y L, et al. Online parallel estimation of mechanical parameters for PMSM drives via a network of interconnected extended sliding-mode observers[J]. IEEE Transactions on Power Electronics, 2021, 36(10):11818-11834. doi: 10.1109/TPEL.2021.3067328

参数	数值
额定功率P/kW	1.1
极对数	4
定子电阻R_s/Ω	2.875
定子(转子)电感L_s/mH	8.5
转子磁链Ψ_f/Wb	0.175
转动惯量J/kg·m²	0.003
粘滞摩擦系数B/N·m·s	0.000 2