基于变异珊瑚礁算法的永磁同步电机参数辨识

doi:10.16182/j.issn1004731x.joss.201808025

摘要/Abstract

摘要： 永磁同步电机参数的高精度辨识是进行控制器设计的基础。针对传统的珊瑚礁算法在辨识电机参数时速度慢,误差大的缺点,提出了一种基于柯西和高斯变异的改进珊瑚礁算法,并将其应用于永磁同步电机的多参数辨识。在dq坐标系下建立永磁同步电机参数辨识模型,将柯西与高斯变异混合入珊瑚礁算法产生子代的过程中,分别将改进前后的珊瑚礁算法应用于求解永磁同步电机参数辨识问题,并在Matlab/Simulink 中进行了对比验证。实验结果表明变异珊瑚礁算法能同时辨识定子电阻、d轴电感、q轴电感、转子磁链等电磁参数并且具有较好的收敛精度。

关键词: 珊瑚礁算法, 永磁同步电机, 参数辨识, 柯西与高斯变异

Abstract: High accuracy identification of parameters in Permanent magnet synchronous motor (PMSM) is the basis of controller design. According to the drawbacks of slow speed, big error, and small number of parameters in particle swarm optimization (PSO), least square method, and classical coral reefs optimization (CRO), an improved CRO with Cauchy and Gaussian mutation is proposed to solve the parameter identification problem in PMSM. The mathematical model of PMSM in dq coordinate system is established. The Cauchy and Gaussian mutation operator is introduced to CRO. Both of the two versions are applied for identifying parameters in PMSM, and are verified in Matlab/Simulink for comparison. The simulation results indicate that the improved CRO algorithm is able to improve the identification accuracies of stator resistance, d-axis inductance, q-axis inductance, and rotor flux; and guarantee the performance improvement in PMSM.

Key words: coral reefs optimization, permanent magnet synchronous motor, parameter identification, Cauchy and Gaussian mutation

中图分类号:

TM391.9

吴定会, 黄旭, 全亚威, 纪志成. 基于变异珊瑚礁算法的永磁同步电机参数辨识[J]. 系统仿真学报, 2018, 30(8): 3024-3032.

Wu Dinghui, Huang Xu, Quan Yawei, Ji Zhicheng. Parameter Identification of Permanent Magnet Synchronous Motor Based on Mutation Coral Reef Algorithm[J]. Journal of System Simulation, 2018, 30(8): 3024-3032.

参考文献

[1] 王松. 永磁同步电机的参数辨识及控制策略研究[D]. 北京: 北京交通大学, 2011.
WANG Song.Research on Parameter Identification and Control Strategy of Permanent Magnet Synchronous Motor[D]. Beijing: Beijing Jiaotong University, 2011.
[2] Rahman M A, Vilathgamuwa D M, Uddin M N, et al.Nonlinear control of interior permanent-magnet synchronous motor[J]. Industry Applications IEEE Transactions on (S0093-9994), 2003, 39(2): 408-416.
[3] 安群涛, 孙力, 赵克, 等. 一种永磁同步电动机参数的自适应辨识方法[J]. 电工技术学报, 2008, 23(6): 31-36.
AN Quntao, SUN Li, ZHAO Ke, et al.An Adaptive On-Line Identification Method for the Parameters of Permanent Maget Synchronous Motor[J]. TRANSACTIONS OF CHINA ELECTROTECHNICAL SOCIETY, 2008, 23(6): 31-36.
[4] Underwood S J, Husain I.Online Parameter Estimation and Adaptive Control of Permanent-Magnet Synchronous Machines[J]. Industrial Electronics IEEE Transactions on (S0278-0046), 2010, 57(7): 2435-2443.
[5] Xia Youshen1, Kamel, Mohamed S, et al. A fast algorithm for AR parameter estimation using a novel noise-constrained least-squares method[J]. Neural Networks (S0893-6080), 2010, 23(3): 396-405.
[6] 张瑞峰, 于森林, 刘婷, 等. 基于模型参考自适应的永磁同步电机在线参数辨识方法研究[J]. 机车电传动, 2015(2): 71-76.
ZHANG Ruifeng, YU Senlin, LIU Ting, et al.Research on online Parameter Identification of Permanent Magnet Synchronous Motor Based on Model Reference Adaptive System[J]. ELECTRIC DRIVE FOR LOCOMOTIVES, 2015(2): 71-76.
[7] Boileau T, Leboeuf N, Nahid-Mobarakeh B, et al.Online Identification of PMSM Parameters: Parameter Identifiability and Estimator Comparative Study[J]. IEEE Transactions on Industry Applications (S0093-9994), 2011, 47(4): 1944-1957.
[8] 王磊, 李宏, 武明珠, 等. 基于扩展卡尔曼滤波的永磁同步电动机参数辨识[J]. 微特电机, 2012,40(7): 19-22.
WANG Lei, LI Hong, WU Mingzhu, et al.Parameters Identification of PMSM Based on Extended Kalman Filter[J]. Small & Special Electrical Machines, 2012, 40(7): 19-22.
[9] 年珩, 李嘉文, 万中奇, 等. 基于参数在线辨识的永磁风力发电机无位置传感器控制技术[J]. 中国电机工程学报, 2012, 32(12): 146-154.
NIAN Heng, LI Jiawen, WAN Zhongqi, et al.Sensorless Control Technique of PMSG for Wind Power Application Based on on1ine Parameter Identification[J]. Proceedings of the CSEE, 2012, 32(12): 146-154.
[10] 陈振锋, 钟彦儒, 李洁. 感应电机参数辨识三种智能算法的比较[J]. 电机与控制学报, 2010, 14(11): 7-12.
CHEN Zhenfeng, ZHONG Yanru, LI Jie.Comparison of three intelligent optimization algorithms for parameter identification of induction motors[J]. ELECTRIC MACHINES AND CONTROL, 2010, 14(11): 7-12.
[11] 王少威, 万山明, 周理兵, 等. 利用蚁群算法辨识PMSM伺服系统负载转矩和转动惯量[J]. 电工技术学报, 2011, 26(6): 18-25.
WANG Shaowei, WAN Shanming, ZHOU Libing, et al.Identification of PMSM Servo System’s Load Torque and Moment of Inertia by Ant Colony Algorithm[J]. TRANSACTIONS OF CHINA ELECTROTECHNICAL SOCIETY, 2011, 26(6): 18-25.
[12] Liu L, Liu W, Cartes D A.Permanent Magnet Synchronous Motor Parameter Identification using Particle Swarm Optimization[J]. Int.j.comput.intell.res (S1875-6883), 2008, 4(2): 211-218.
[13] Liu K, Zhang Q, Chen J, et al.Online Multiparameter Estimation of Nonsalient-Pole PM Synchronous Machines with Temperature Variation Tracking[J]. Industrial Electronics IEEE Transactions on (S0278-0046), 2011, 58(5): 1776-1788.
[14] Salcedo-Sanz S, Gallo-Marazuela D, Pastor-Sánchez A, et al.Offshore wind farm design with the Coral Reefs Optimization algorithm[J]. Renewable Energy (S0960-1481), 2014, 63(2): 109-115.
[15] Salcedo-Sanz S, Del Ser J, Gil-López S, et al.The Coral Reefs Optimization Algorithm: An Efficient Meta- heuristic for Solving Hard Optimization Problems[C]//Proc. of the 15th International Conference on Applied Stochastic Models and Data Analysis (ASMDA), Mataró, Barcelona. 2013: 751-758.
[16] Salcedo-Sanz S, Pastor-Sánchez A, Del Ser J, et al.Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization-Extreme learning machine approach[J]. Energy Conversion and Management (S0916-8904), 2014, 87(5): 10-18.
[17] 傅小利, 顾红兵, 陈国呈, 等. 基于柯西变异粒子群算法的永磁同步电机参数辨识[J]. 电工技术学报, 2014, 29(5): 127-131.
FU Xiaoli, GU Hongbin, CHEN Guocheng, et al.Permanent Magnet Svnchronou Motors Parameters Identification Based on Cauchy Mutation Particle Swarm Optimization[J]. TRANSACTl0NS OF CHINA ELECTROTECHNICAL SOCIETY, 2014, 29(5): 127-131.
[18] 石永生, 陈家琪. 基于高斯变异的量子粒子群算法[J]. 电脑与信息技术, 2010, 18(6): 9-12.
SHI Yongsheng, CHEN Jiaqi.An Improved Quantum- behaved Particle Swarm Optimization Based on Gaussian Mutation[J]. Computer and Information Technology, 2010, 18(6): 9-12.