基于自适应EKF的永磁同步电机无传感控制

微特电机 ›› 2023, Vol. 51 ›› Issue (5): 36-43.

基于自适应EKF的永磁同步电机无传感控制

曹元¹, 吴琦¹, 胡昌青¹, 周洪文¹, 刘宴华²

1.河海大学信息学部(物联网工程学院),常州 213022;
2.上海空间电源研究所,上海 200245

收稿日期:2022-11-21 出版日期:2023-05-28 发布日期:2023-05-29
通讯作者: 吴琦(1999—),男,硕士,研究方向为永磁同步电机无传感控制。
作者简介:曹元(1988—),男,博士,教授,研究方向为集成电路。胡昌青(1998—),男,硕士,研究方向为永磁同步电机无传感控制。周洪文(1988—),男,硕士,研究方向为永磁同步电机无传感控制。刘宴华(1986—),男,博士,研究方向为太空空间电源。
基金资助:
国家自然科学基金项目(62274056);江苏省重点研发计划项目(BE2022098);江苏省博士后科研资助计划项目(2021K605C)

Sensorless Control of Permanent Magnet Synchronous Motor Based on Adaptive EKF Algorithm

CAO Yuan¹, WU Qi¹, HU Changqin¹, ZHOU Hongwen¹, LIU Yanhua²

1. Department of Informatics (School of Internet of Things Engineering), Hohai University,Changzhou 213022, China;
2. Shanghai Institute of Space Power-Sources, Shanghai 200245, China

Received:2022-11-21 Online:2023-05-28 Published:2023-05-29

摘要/Abstract

摘要： 传统扩展卡尔曼滤波(EKF)算法会受到永磁同步电机在实际运行中电机参数变化的影响,在速度的估算过程中会产生较大抖动,造成位置估算结果偏差。通过引入类Sigmoid函数来构建自适应EKF算法,用类Sigmoid函数取代传统EKF算法中关键的固定参数,实现参数的动态调整,抑制电机参数变化带来的扰动,降低超调量。建立仿真模型进行仿真验证,结果表明,自适应EKF算法相比于传统最优参数EKF算法,动态响应速度更快,抗干扰能力和鲁棒性更强,转速误差缩小了约60%,转子位置估算误差缩小了约9%。

关键词: 永磁同步电机, 无传感控制, 扩展卡尔曼滤波, 类Sigmoid 函数, 参数自适应

Abstract: The traditional extended Kalman filter (EKF) algorithm is affected by the changes of motor parameters in the actual operation of the permanent magnet synchronous motor, which generates large jitter during the estimation of the velocity and causes deviations in the position estimation results. The adaptive EKF algorithm was constructed by introducing the Sigmoid-like function to replace the key fixed parameters in the traditional EKF algorithm with the Sigmoid-like function to realize the dynamic adjustment of parameters, suppress the perturbation caused by the change of motor parameters, and reduce the amount of overshoot. A simulation model for experimental verification was established. The experimental results show that compared with the traditional optimal parameter EKF algorithm, the adaptive EKF algorithm has faster dynamic response speed, stronger anti-interference ability and robustness, the speed error is reduced by about 60%, and the rotor position estimation error is reduced by about 9%.

Key words: permanent magnet synchronous motor (PMSM), sensorless control, extended Kalman filter (EKF), Sigmoid-like function, parameter adaptation

中图分类号:

TM351
TM464

曹元, 吴琦, 胡昌青, 周洪文, 刘宴华. 基于自适应EKF的永磁同步电机无传感控制[J]. 微特电机, 2023, 51(5): 36-43.

CAO Yuan, WU Qi, HU Changqin, ZHOU Hongwen, LIU Yanhua. Sensorless Control of Permanent Magnet Synchronous Motor Based on Adaptive EKF Algorithm[J]. Small & Special Electrical Machines, 2023, 51(5): 36-43.

参考文献

[1] CHOU M C,LIAW C M.dynamic control and diagnostic friction estimation for an SPMSM-driven satellite reaction wheel[J].IEEE Transactions on Industrial Electronics,2011,58(10):4693-4707.
[2] 陈广辉,曾敏,魏良红.无位置传感器永磁同步电动机矢量控制系统综述[J].微特电机,2011,39(12):64-67,75.
[3] BLASCHKE F.A new method for the structural decoupling of AC induction machines [C]//Conference Record of IFAC.Duesseldorf,Germany,1971: 1-15.
[4] SAADAOUI O,KHLAIEF A,ABASSI M,et al.Position sensorless vector control of PMSM drives based on SMO[C]//International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA),IEEE,2016:545-550.
[5] LAGRIOUI A,MAHMOUDI H.Speed and current control for the PMSM using a Luenberger observer [C]//2011 International Conference on Multimedia Computing and Systems.IEEE,2011.
[6] OUVANG Y,DOU Y.Speed sensorless control of PMSM based on mras parameter identification[C]//21st International Conference on Electrical Machinesand Systems (ICEMS).IEEE,2018:1618-1622.
[7] TERMIZI M S,LAZI J M, IBRAHIM Z, et al.Sensorless PMSM drives using extended kalman filter (EKF)[C]//IEEE Conference on Energy Conversion(CENCON),2017:145-150.
[8] DAI Y ,YE C ,ZHAO S ,et al.EKF for three-vector model predictive current control of PMSM[C]//IEEE 1st China International Youth Conference on Electrical Engineering (CIYCEE).IEEE,2020:1-6.
[9] WANG G ,VALLA M I ,SOLSONA J A .Position sensorless permanent magnet synchronous machine drives—a review[J].IEEE Transactions on Industrial Electronics,2019,67(7):5830-5842.
[10] 龙吟江,吴晓东,王锐松.基于EKF的车用永磁同步电机无电流传感器鲁棒控制[J].微特电机,2022,50(3):38-45.
[11] WALAMBE R A ,APTE A A ,JOSHI V A.Disturbance observer based sensor-less vector control drive for PMSM using EKF[C]//IEEE Symposium on Sensorless Control for Electrical Drives (SLED).IEEE,2016:1-5.
[12] QUN-TAO A N,SUN L,BO L I.Variable parameters EKF for speed estimation of PMSM[J].Electric Machines and Control,2007,11(6):559-563.
[13] ZHANG Y,CHENG X.Sensorless control of permanent magnet synchronous motors and EKF parameter tuning research[J].Mathematical Problems in Engineering,2016,1(25):1-12.
[14] LU K,XIAO J.Speed estimation with parameter adaptation of induction motors based on single filter multi-model algorithm[J].Transactions of China Electrotechnical Society,2009,24(1):70-75.
[15] HE D,PENG X,JIANG X,et al.The improved EKF velocity estimation algorithm for PMSM and experimental assessment[C]//Proceedings of the 31st Chinese Control Conference.IEEE,2012:4273-4277.
[16] WALAMBE R A,JOSHI V A.Survey of EKF based sensorless vector control methodologies for a permanent magnet synchronous motor[C]//Indian Control Conference.IEEE,2016:93-98.
[17] LIU G,ZHANG H,SONG X.Position-estimation deviation-suppression technology of PMSM combining phase self-compensation SMO and feed-forward PLL[J].IEEE Journal of Emerging and Selected Topics in Power Electronics,2021,9(1):335-344.
[18] 李波.基于扩展卡尔曼滤波的无位置传感器PMSM系统研究[D].哈尔滨:哈尔滨工业大学,2007.
[19] 苗敬利,于俊林,马晨浩,等.基于EKF的PMSM滑模控制策略研究[J].机械工程与自动化,2021(5):1-3,6.