Abstract Aiming at the difficulty of multi-parameter identification of permanent magnet synchronous motor (PMSM), this paper proposed a chaotic mutation niche particle swarm optimization algorithm with initial parameter optimization (NCOPSO), and designed a full-rank mathematical system with five parameters (stator winding resistance, stator cross-axis and direct-axis inductance, permanent magnet flux, moment of inertia) to be identified. Firstly, the particle swarm optimization was used to optimize the three initial parameters (inertia coefficient ω, learning factor c1, c2) of the basic particle swarm optimization algorithm. Then the niche strategy was applied to the optimized particle swarm: a niche population centering on the particles with small adaptive value changes in successive iterations was constructed. Finally, the chaotic mutation strategy is used: in each iteration process, a chaotic sequence was generated based on the optimal particles of each niche group. The optimal particles in the sequence were randomly replaced by a certain particle of the current niche population, and the worst particle of the niche mirror population was initialized at the same time. The feasibility and accuracy of the algorithm were verified by motor simulation and experiment.
Liu Xiping,Hu Weiping,Ding Weizhong等. Research on Multi-Parameter Identification Method ofPermanent Magnet Synchronous Motor[J]. Transactions of China Electrotechnical Society, 2020, 35(6): 1198-1207.
[1] Masahiro Aoyama, Deng Jianing.Visualization and quantitative evaluation of eddy current loss in bar-wound type permanent magnet synchronous motor for mild-hybrid vehicles[J]. CES Transactions on Electrical Machines and Systems, 2019, 3(3): 269-278. [2] 李键, 牛峰, 黄晓艳, 等. 永磁同步电机有限控集模型预测电流控制预测误差分析[J]. 电机与控制学报, 2019, 23(4): 2-7. Li Jian, Niu Feng, Huang Xiaoyan, et al.Prediction error analysis of finite-controlset model predictive current control for PMSMs[J]. Electric Machines and Control, 2019, 23(4): 2-7. [3] Underwood S J, Husain I.Online parameter estimation and adaptive control of permanent-magnet synchronous machines[J]. IEEE Transactions on Industrial-Electronics, 2010, 57(7): 2435-2443. [4] Babel A S, Cintron-Rivera J G, Foster S N, et al. Evaluation of a parameter identification method for permanent magnet AC machines through parametric sensitivity analysis[J]. IEEE Transactions on Energy Conversion, 2014, 29(1): 240-249. [5] Huang Wenqing, Zhang Yontong, Zhang Xingchun, et al.Accurate torque control of interior permanent magnet synchronous machine[J]. IEEE Transactions on Energy Conversion, 2014, 29(1): 29-37. [6] Underwood S J, Husain I.Online parameter estimation and adaptive control of permanent-magnet synchronous machines[J]. IEEE Transactions on Industrial Electronics, 2010, 57(7): 2435-2443. [7] Zhang Xiaoguang, Li Zhengxi.Sliding mode observer-based mechanical parameter estimation for permanentmagnet synchronous motor[J]. IEEE Transactions on Power Electronics, 2016, 31(8): 5732-5745. [8] Liu Kan, Zhu Z Q, Stone D A.Parameter estimation for condition monitoring of PMSM stator winding and rotor permanent magnets[J]. IEEE Transactions on Industrial Electronics, 2013, 60(12): 5902-5913. [9] 刘金海, 陈为. 表贴式永磁同步电机准稳态多参数在线辨识[J]. 电工技术学报, 2016, 31(17): 155-160. Liu Jinghai, Chen Wei.Online multi-parameter identification for surface-mounted permanent magnet synchronous motors under quasi-steady-state[J]. Transactions of China Electrotechnical Society, 2016, 31(17): 155-160. [10] Shi Yuchao.Online identification of permanent magnet flux based on extended Kalman filter for IPMSM drive with position sensorless control[J]. IEEE Transactions on Industrial Electronics, 2012, 59(11): 4169-4178. [11] 杨宗军, 王莉娜. 表贴式永磁同步电机的多参数在线辨识[J]. 电工技术学报, 2014, 29(3): 112-118. Yang Zongjun, Wang Lina.Online multi-parameter identification for surface-mountrd permanent magnet synchronous motors[J]. Transactions of China Electrotechnical Society, 2014, 29(3): 112-118. [12] Zhang Yanqing, Yin Zhonggang, Sun Xiangdong, et al.On-line identification- methods of parameters for permanent magnet synchronous motors based on cascade MRAS[C]//9th International Conference on Power Electronics and E-CCE Asia, 2015: 345-353. [13] 谷鑫, 胡升, 史婷娜, 等. 基于神经网络的永磁同步电机多参数解耦在线辨识[J]. 电工技术学报, 2015, 30(6): 115-121. Gu Xin, Hu Sheng, Shi Tingna, et al.Muti-parameter decoupling online identification of permanent magnet synchronous motor based on neural network[J]. Transactions of China Electrotechnical Society, 2015, 30(6): 115-121. [14] 张立伟,张鹏,刘曰峰, 等. 基于变步长Adaline神经网络的永磁同步电机参数辨识[J]. 电工技术学报, 2018, 33(2): 378-384. Zhang Liwei, Zhang Peng, Liu Yuefeng, et al.Parameter identification of permanent magnet synchronous motor based on variable step-size adaline neural network[J]. Transactions of China Electrotechnical Society, 2018, 33(2): 378-384. [15] 肖曦, 许青松, 王雅婷, 等. 基于遗传算法的内埋式永磁同步电机参数辨识方法[J]. 电工技术学报, 2014, 29(3): 22-26. Xiao Xi, Xu Qingsong, Wang Yating, et al.Parameter identification of interior permanent magnet synchronous motors based on genetic algorithm[J]. Transactions of China Electrotechnical Society, 2014, 29(3): 22-26. [16] Liu Kan, Zhu Z Q.Quantum genetic algorithm-based parameter estimation of PMSM under variable speed control accounting for system identifiability and VSI nonlinearity[J]. IEEE Transactions on Industrial- Electronics, 2015, 62(4): 2363-2371. [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 Hongbing, Chen Guocheng, et al.Permanent magnet synchronous motors parameters identification based on cauchy mutation particle swarm optimization[J]. Transactions of China Electrotechnical Society, 2014, 29(5): 127-131. [18] 刘朝华, 李小花, 周少武, 等. 面向永磁同步电机参数辨识的免疫完全学习型粒子群算法[J]. 电工技术学报, 2014, 29(5): 119-126. Liu Chaohua, Li Xiaohua, Zhou Shaowu, et al.Comprehensive learning particle swarm optimization algorithm based on immune mechanism for permanent magnet synchronous motor parameter identification[J]. Transactions of China Electrotechnical Society, 2014, 29(5): 119-126. [19] 谷苗, 夏超英, 田聪颖. 基于综合型卡尔曼滤波的锂电池荷点状态估算[J]. 电工技术学报, 2019, 34(2): 420-426. Gu Miao, Xia Chaoying, Tian Congying, Li-ion battery state of charge estimation based on comprehensive Kalman filter[J]. Transactions of China Electrotechnical Society, 2019, 34(2): 420-426. [20] 赵希梅, 吴勇慷. 基于自适应修正拉盖尔递归神经网络的永磁直线同步电机反推控制[J]. 电工技术学报, 2018, 33(10): 2393-2399. Zhao Ximei, Wu Yongkang.Backstepping control based on adaptive modified laguerre ecurrent neural network for permanent magnet linear synchronous motor[J]. Transactions of China Electrotechnical Society, 2018, 33(10): 2393-2399. [21] 杜林, 杨峰, 蔚超, 等. 基于频域介电谱的油纸绝缘宽频等效模型参数辨识研究[J]. 电工技术学报, 2018, 33(5): 1159-1166. Du Lin, Yang Feng, Wei Chao, et al.Parameter identification of the wide-band model of oil- impregnated paper insulation using frequency[J]. Transactions of China Electrotechnical Society, 2018, 33(5): 1159-1166. [22] 彭道刚, 陈跃伟, 钱玉良, 等. 基于粒子群优化-支持向量回归的变压器绕组温度软测量模型[J]. 电工技术学报, 2018, 33(8): 1743-1749. Peng Daogang, Chen Yuewei, Qian Yuliang, et al.Transformer winding temperature soft measurement model based on particle swarm optimization suport vector regression[J]. Transactions of China Elec- trotechnical Society, 2018, 33(8): 1743-1749. [23] 介婧, 徐新黎. 智能粒子群优化计算控制方法、协同策略及优化应用[M]. 北京: 科学出版社, 2016. [24] Brits R, Engelbrecht A P, Bergh F V D. A niching particle swarm optimizer[C]//Conference on Simulated Evolution & Learning, South Africa, 2002: 1037-1040. [25] 贾东立, 张家树, 张超. 基于混沌遗传算法的基元提取[J]. 西南交通大学学报, 2005, 40(4): 496-500. Jia Dongli, Zhang Jiashu, Zhang Chao.Geomet ricpri-mitive extraction using chaos genetic algo- rithm[J]. Journal of Southwest Jiaotong University, 2005, 40(4): 496-500. [26] 施特凡格雷席克. 混沌与其秩序[M]. 上海: 百家出版社, 2001. [27] 纪震, 廖惠连, 吴青华. 粒子群算法与应用[M]. 北京: 科学出版社, 2009. [28] 李立毅, 于吉坤, 曹继伟, 等. 新型定子结构永磁同步电机弱磁调速性能分析[J]. 电工技术学报, 2015, 30(14): 87-93. Li Liyi, Yu Jikun, Cao Jiwei, et al.Analysis of permanent magnet synchronous motor with new stator- design for adjustable-speed by flux weakening[J]. Transactions of China Electrotechnical Society, 2015, 30(14): 87-93.
2020, Vol. 35 
