基于扩展卡尔曼滤波器的电机参数辨识算法

电气工程学报 ›› 2015, Vol. 10 ›› Issue (5): 34-42.

基于扩展卡尔曼滤波器的电机参数辨识算法

李洪宇¹,王群京²,李国丽³,谢芳⁴,谢鹏⁵,杨新年¹

1.安徽大学电气工程与自动化学院合肥 230601
2.安徽大学高节能电机及控制技术国家地方联合实验室合肥 230601
3.安徽大学教育部电能质量工程研究中心合肥 230601
4.安徽大学安徽省工业节电与用电安全实验室合肥 230601
5.安徽大学工业节电与电能质量控制协同创新中心合肥 230601

收稿日期:2014-11-03 出版日期:2015-05-25 发布日期:2015-05-25
作者简介:李洪宇男 1989 年生,硕士研究生,研究方向为交流无速度传感器变频调速控制策略。|王群京男 1960 年生,教授,博士生导师,主要从事特种电机及其控制、电磁场计算等方面的研究。
基金资助:
2014年安徽省教育厅重点项目,“EV车用电机预测控制方法研究”资助项目

Electromagnetic Parameter Identification Algorithm of AC Motor Based on Extended Kalman Filter

Li Hongyu¹,Wang Qunjing²,Li Guoli³,Xie Fang⁴,Xie Peng⁵,Yang Xinnian¹

1.College of Electrical and Automation Anhui University Hefei 230601 China
2.National Engineering Laboratory of Energy-Saving Motor & Control Technique Anhui University Hefei 230601 China;
3.Quality of Electric Energy Engineering Research Center of the Ministry of Education Anhui University Hefei 230601 China
4.Industrial Power Saving and Electrical Safety Laboratory Anhui University Hefei 230601 China
5.Collaborative Innovation Center of Industrial Power Saving and Power Quality Control Anhui University Hefei 230601 China

Received:2014-11-03 Online:2015-05-25 Published:2015-05-25

摘要/Abstract

摘要：

准确的电机参数是无速度传感器交流调速系统设计的前提。运行过程中,由于温度、频率和磁通的影响,电机参数通常会发生变化,特别是,转子电阻和磁链电感的变化直接关系到磁链和转速的辨识精度,影响驱动系统性能。本文通过测量定子电压和电流,基于扩展卡尔曼滤波器（EKF）,研究了一种新颖算法,通过将两个基于扩展卡尔曼滤波器模型有机结合,协同工作,实现了对转子电阻、励磁电感、转子磁链和转速在线辨识。仿真和实验结果表明这种新颖的电机参数辨识算法具有较小的辨识误差,可以满足无速度传感器交流调速系统对电机参数准确性的要求。

关键词: 参数辨识, 扩展卡尔曼滤波器, 磁场定向, 无速度传感器, 数字信号处理器

Abstract:

It is the precondition for AC drive system to determine the electromagnetic parameters of induction machine exactly. But in the running process of the motor, the electrical parameters will change, that maybe result from the effect of temperature, frequency, and flux. Especially, variations of stator resistance and magnetizing inductance are not only relevant to identification error of flux and speed directly, but also impact of the driven system performance. By measuring stator voltage and current, a novel algorithm is presented based on the serial operation of two extend Kalman filter (EKF) in this paper. This approach will achieve rotor stator resistance, magnetizing inductance, rotor flux, speed as well as high-precision identifications online. Experimental and simulation results show that the developed algorithm leads to smaller system error than the traditional one and can meet the precision requirement in speed sensor-less vector control system of induction motor.

Key words: Parameter identification, extend Kalman filter, field-oriented, speed-sensorless, digital singnal process

中图分类号:

TM301.02

李洪宇,王群京,李国丽,谢芳,谢鹏,杨新年. 基于扩展卡尔曼滤波器的电机参数辨识算法[J]. 电气工程学报, 2015, 10(5): 34-42.

Li Hongyu,Wang Qunjing,Li Guoli,Xie Fang,Xie Peng,Yang Xinnian. Electromagnetic Parameter Identification Algorithm of AC Motor Based on Extended Kalman Filter[J]. Journal of Electrical Engineering, 2015, 10(5): 34-42.

图/表 13

图1

图2

图3

图4

图5

图6

图7

图8

图9

表

图10

图11

图12

参考文献 17

[1]	Radhakrishnan K, Unnikrishnan A, Balakrishnan K G . EM based extended Kalman filter for estimation of rotor time-constant of induction motor[C]. 2006 IEEE International Symposium on Industrial Electronics, 2006,3:2434-2438.
[2]	Vukadinovic , Dinko , Mateo Basic , et al. Stator resistance identification based on neural and fuzzy logic principles in an induction motor drive[J]. Neurocomputing, 2010,73(4):602-612. doi: 10.1016/j.neucom.2009.06.017
[3]	Jouili , Mabrouk , Kamel Jarray , et al. A luenberger state observer for simultaneous estimation of speed and rotor resistance in sensorless indirect stator flux orientation control of induction motor drive[J]. IJCSI International Journal of Computer Science, 2011,8(6):116-125.
[4]	Du T, Vas P, Stronach F . Design and application of extended observers for joint state and parameter estimation in high-performance AC drives[C]. IEE Proceedings-Electric Power Applications, 1995,142(2):71-78.
[5]	Maes , Jehudi , Melkebeek Jan A . Speed-sensorless direct torque control of induction motors using an adaptive flux observer[J]. IEEE Transactions on Industry Applications, 2000,36(3):778-785. doi: 10.1109/28.845053
[6]	Doan P T, Bui T L, Kim H K , et al. Sliding-mode observer design for sensorless vector control of AC induction motor[J]. Asian Control Conference, 2013: 1-5.
[7]	A dnan Derdiyok, Zhang Yan, Mustafa Guven , et al. A sliding mode speed and rotor time constant observer for induction machines[C]. The 27th Annual Conference of the IEEE Industrial Electronics Society, 2001,2:1400-1405.
[8]	Comanescu , Mihai , Todd Batzel . Sliding mode MRAS speed estimators for sensorless control of induction machine under improper rotor time constant[C]. IEEE International Symposium on Industrial Electronics, 2007.
[9]	Zai , Li Cheng, Christopher L D , et al. An extended Kalman filter approach to rotor time constant measurement in PWM induction motor drives[J]. IEEE Transactions on Industry Applications, 1992,28(1):96-104. doi: 10.1109/28.120217
[10]	Madadi Kojabadi,H, Chang L . Model reference adaptive system pseudoreduced-order flux observer for very low speed and zero speed estimation in sensorless induction motor drives[C]. IEEE 33rd Annual Power Electronics Specialists Conference, 2002,1:301-308.
[11]	阮毅, 陈伯时 . 电力拖动自动控制系统—运动控制系统[M].4版. 北京: 机械工业出版社, 2010.
[12]	Bogosyan O S, Gokasan M, Hajiyev C . An application of EKF for the position control of a single link arm[C]. The 27th Annual Conference of the IEEE Industrial Electronics Society, 2001,1:564-569.
[13]	Aydeniz, Mustafa Gürkan, Ibrahim Senol . A luenberger-sliding mode observer with rotor time constant parameter estimation in induction motor drives[J]. Turkish Journal Electrical Engineering & Computer Sciences, 2011,19(6):901-912. doi: 10.1126/science.aat7487 pmid: 31488661
[14]	杜磊 . 基于卡尔曼滤波的交流异步电机无速度传感器矢量控制系统[D]. 南京:南京航空航天大学, 2010.
[15]	Douiri , Moulay Rachid, Mohamed Cherkaoui , et al. Rotor resistance and speed identification using extended Kalman filter and fuzzy logic controller for induction machine drive[C]. 2012 IEEE International Conference on Multimedia Computing and Systems, 2012.
[16]	Zaky M S, Khater M M, Yasin H , et al. Magnetizing inductance identification algorithm for operation of speed-sensorless induction motor drives in the field weakening region[C]. IEEE 12th International Middle-East Power System Conference, 2008: 103-108.
[17]	Barut , Murat , Seta Bogosyan , et al. Experimental evaluation of braided EKF for sensorless control of induction motors[J]. IEEE Transactions on Industrial Electronics, 2008,55(2):620-632. doi: 10.1109/TIE.2007.911956

	程序/字	数据/字	指令周期
环形链式	10 035	5 262	5 162（单次）
传统算法	4 517	2 904	5 081（两次）
二者差	5 518	2 358	81