Abstract：Based on model reference adaptive theory, an online multi-parameter identification method is proposed for surface-mounted permanent magnet synchronous motors(SPMSM). The winding resistance, inductance and PM flux are achieved in the same model. This method utilizes Popov's hyper-stability theory, which guarantees the convergence of the identification under certain conditions. Besides, step-by-step program also avoids the deficient rank of system and obtains unique solution. In step-by-step identification, q-axis equation is used to estimate inductance firstly, and then, rotor resistance and flux are estimated by setting a low d-axis current. Further, the estimated inductance and flux can also be used to track the resistance variation. The simulation and experiment illustrate the validity and efficiency of the proposed method for multi-parameter identification, regardless of the motor operating state.
[1] 李崇坚. 交流同步电机调速系统[M]. 北京: 科学出版社, 2006. [2] De Almeida A T, Ferreira F J T E, Fong J A C. Standards for efficiency of electric motors[J]. IEEE Industry Applications Magazine, 2011, 17(1), 12-19. [3] 白华, 赵争鸣, 袁立强, 等. 磁场定向与直接转矩控制变频器鲁棒性分析[J]. 中国电机工程学报, 2006, 26(1): 91-95. Bai Hua, Zhao Zhengming, Yuan Liqiang, et al. Comparison and analysis of inverters' robustness based on the field oriented control and direct torque control[J]. Proceeings of the CSEE, 2006, 26(1): 91-95. [4] Zaky M S. Stability analysis of speed and stator resistance estimators for sensorless induction motor drives[J]. IEEE Transactions on Industrial Electronics, 2012, 59(2): 858-870. [5] Rashed M, Macconnell P F A, Stronach A F, et al. Sensorless indirect-rotor-field-orientation speed control of a permanent-magnet synchronous motor with stator-resistance estimation[J]. IEEE Transactions on Industrial Application, 2007, 54(3): 1664-1675. [6] Liu L, Cartes D A. Synchronisation based adaptive parameter identification for permanent magnet synchronous motors[J]. IET Control Theory & Application, 2007, 1(4): 1015-1022. [7] 安群涛, 孙力, 赵克. 一种永磁同步电动机参数的自适应在线辨识方法[J]. 电工技术学报, 2008, 23(6): 31-36. An Quntao, Sun Li, Zhao Ke. 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. [8] Ramakrishnan R, Islam R, Islam M, et al. Real time estimation of parameters for controlling and monitoring permanent magnet synchronous motors[C]. IEEE International Electric Machines and Drives Conference, 2009: 1194-1199. [9] 刘侃, 章兢. 基于自适应线性元件神经网络的表面式永磁同步电机参数在线辨识[J]. 中国电机工程学报, 2010, 30(30): 68-73. Liu Kan, Zhang Jing. Adaline neural network based online parameter estimation for surface-mounted permanent magnet synchronous machines[J]. Procee- dings of the CSEE, 2010, 30(30): 68-73. [10] Boileau T, Mobarakeh Nahid B, Meibody Tabar F. On-line identification of PMSM parameters: model- reference vs EKF[C]. IEEE Industry Application Society Annual Meeting, 2008: 1-8. [11] [英] N N汉可克. 电机的矩阵分析[M]. 北京: 科学出版社, 1980. [12] Morimoto S, Sanada M, Yakeda Y. Mechanical sensorless drives of IPMSM with online parameter identification[J]. IEEE Transactions on Industry Applications, 2006, 42(5): 1241-1248. [13] 张侨. 永磁同步电机参数辨识的研究[D]. 武汉: 华中科技大学, 2010. [14] 王莉娜, 杨宗军. Simulink中PMSM模型的改进及在参数辨识中的应用[J]. 电机与控制学报, 2012, 16(7): 77-82. Wang Lina, Yang Zongjun. PMSM model's reform in Simulink and application in parameters' identification [J]. Electric Machines and Control, 2012, 16(7): 77-82.
2014, Vol. 29 
