Parameter Identification for Interior Permanent Magnet Synchronous Motor Based on Experimental Calibration and Stochastic Approximation Theory With Two Time Scales

被引：0

作者：

Lian C. ^{[1
]}

Xiao F. ^{[1
]}

Gao S. ^{[1
]}

Liu J. ^{[1
]}

机构：

[1] National Key Laboratory of Science and Technology on Vessel Integrated Power System, Naval University of Engineering, Wuhan, 430033, Hubei Province

来源：

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2019年 / 39卷 / 16期

关键词：

Convergence analysis; Experimental calibration; Interior permanent magnet synchronous motor; Parameter identification; Stochastic approximation with two time scales;

D O I：

10.13334/j.0258-8013.pcsee.181393

中图分类号：

学科分类号：

摘要：

A parameter identification method of interior permanent magnet synchronous motor (IPMSM) was proposed, which realizes the high precision identification of stator resistance, permanent magnet flux linkage and d-q axis inductance. Firstly, the mathematical expressions of stator resistance and temperature, permanent magnet flux and temperature and d-q axis current were obtained via experiments, and then an on-line identification method of d-q axis inductance was developed based on stochastic approximation theory with two time scales. The convergence and optimality of the proposed on-line identification algorithm were proved theoretically, and the criteria to obtain key parameters were also given to ensure the algorithm has favorable dynamic characteristic and steady state accuracy. Experimental results show that the presented identification method not only has fast convergence speed, but also has higher identification accuracy than the traditional recursive least square algorithm. © 2019 Chin. Soc. for Elec. Eng.

引用

页码：4892 / 4898

页数：6

共 18 条

[1] Lu D., Ouyang M., Gu J., Et al., Optimal regenerative braking control for permanent magnet synchronous motors in electric vehicles, Proceedings of the CSEE, 33, 3, pp. 83-91, (2013)
[2] Chen Z., Liu X., Jin Y., Et al., Direct torque control of permanent magnet synchronous motors based on extended Kalman filter observer of flux linkage, Proceedings of the CSEE, 28, 33, pp. 75-81, (2008)
[3] Feng J., Xu J., Permanent magnet synchronous machines direct torque control system based on adaptive stator flux observer, Proceedings of the CSEE, 26, 12, pp. 122-127, (2006)
[4] Liu J., Xiao F., Shen Y., Et al., Position-sensorless control technology of permanent-magnet synchronous motor-a review, Transactions of China Electrotechnical Society, 32, 16, pp. 76-88, (2017)
[5] Li H., Chen T., Review of research on parameter identification of PMSM, Journal of Electronic Measurement and Instrumentation, 29, 5, pp. 638-647, (2015)
[6] Sandre-Hernandez O., Morales-Caporal R., Rangel-Magdaleno R., Et al., Parameter identification of PMSMs using experimental measurements and a PSO algorithm, IEEE Transactions on Instrumentation and Measurement, 64, 8, pp. 2146-2154, (2015)
[7] Rahman K.M., Hiti S., Identification of machine parameters of a synchronous motor, IEEE Transactions on Industry Application, 41, 2, pp. 557-565, (2005)
[8] Niu L., Research on high performance control strategies for pmsm based on parameter identification algorithm, (2015)
[9] Shi J., Ge B., Lu Y., Et al., Research of parameter identification of permanent magnet synchronous motor on line, Electric Machines and Control, 22, 3, pp. 17-24, (2018)
[10] Xiao X., Zhang M., Li Y., On-line estimation of permanent-magnet flux linkage ripple for PMSM, Proceedings of the CSEE, 27, 24, pp. 43-47, (2007)

← 1 2 →