吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (06): 1596-1600.doi: 10.7964/jdxbgxb201306026

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Off-line parameter identification for induction motor based on reconstructed voltage

ZHAO Fei-xiang1, ZHANG Jian-wei1, GUO Kong-hui1, ZHANG Li-hao1, ZHENG Zhong2   

  1. 1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China;
    2. College of Automotive Engineering, Jilin University, Changchun 130022, China
  • Received:2012-11-21 Online:2013-11-01 Published:2013-11-01

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Abstract:

Vector control schemes for induction motor drive systems have been widely adopted in high performance applications. Vector control transforms the control of an induction motor to that of separately excited dc motor by creating independent channels for flux and torque control. Crucial to the success of a vector control scheme is the knowledge of the instantaneous position of the rotor flux. The position of the rotor flux is estimated in the direct vector control scheme, which requires a priori knowledge of the machine parameters. Identification of machine parameters is a basic step in designing a motor controller. In traditional method, voltage required for off-line identification of induction motor parameters is commonly obtained by filter circuit and data acquisition equipment, and the equivalent circuit of the induction motor is usually modified. The reason that traditional off-line identification result of induction motor parameters is not suitable to online model is analyzed. The internal resistance of the power devices is equivalised to the stator resistance of the motor first. Then the voltage distortion caused by dead-time is eliminated through offline voltage correction. Finally, a genetic algorithm is used to identify the equivalent electrical parameters of induction motor. Experiment results show that the parameters obtained by this method can accurately describe the steady-state and transient response of the induction motor under specific inverter power supplying conditions.

Key words: electrical engineering, induction motor, parameter identification, reconstructed voltage, distortion correction, genetic algorithm

CLC Number: 

  • TM343

[1] 夏超英. 交直流传动系统的自适应控制[M]. 北京:机械工业出版社,1998:220.

[2] Maurizio Cirrincione, Marcello Pucci, Giansalvo Cirrincione, et al. A new experimental application of least-squares techniques for the estimation of the induction motor parameters[J]. IEEE Transactions on Industry Applications, 2003, 39: 1247-1256.

[3] Yassine Koubaa, Mohamed Boussak. Rotor resistance tuning for indirect stator flux orientated induction motor drive based on MRAS scheme[J]. European Transactions on Electrical Power, 2005, 15:557-570.

[4] 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 Zhen-feng, Zhong Yan-ru,Li Jie. Comparison of three intelligent optimization algorithms for parameter identification of induction motors[J]. Electric Machines And Control, 2010, 14(11): 7-12.

[5] Mustafa Arslan, Mehmet Cunkas, Tahir Sag. Determination of induction motor parameters with differential evolution algorithm[J]. Neural Computing and Applications, 2012, 21(8): 1995-2004.

[6] Hwang Seon-Hwan, Kim Jang-Mok. Dead time compensation method for voltage-fed PWM inverter[J]. IEEE Transactions on Energy Conversion, 2010, 25(1): 1-10.

[7] 刘军锋,李叶松. 死区对电压型逆变器输出误差的影响及其补偿[J]. 电 工 技 术 学 报,2007, 22(5): 117-122. Liu Jun-feng, Li Ye-song. Dead-time influence on output error of voltage source inverter and compensation[J]. Transactions of China Electrotechnical Society, 2007, 22(5): 117-122.

[8] 程小猛,陆海峰,瞿文龙,等. 用于逆变器死区补偿的空间矢量脉宽调制策略[J]. 清华大学学报:自然科学版,2008,48(7):1077-1080. Cheng Xiao-meng, Lu Hai-feng, Qu Wen-long, et al. SVPWM strategy for inverter dead time compensation[J]. Journal of Tsinghua University (Science and Technology), 2008, 48(7): 1077-1080.

[9] Choi Jong-Woo,Sul Seung-Ki. Inverter output voltage synthesis using novel dead time compensation[J]. IEEE Transactions on Power Electronics, 1996, 11(2): 221-227.

[10] 窦汝振,刘钧,温旭辉,等. SVPWM控制逆变器死区补偿方法的研究[J]. 电力电子技术,2004,38(6):59-61. Dou Ru-zhen,Liu Jun,Wen Xu-hui,et al. Research on dead-time compensation of inverter using SVPWM[J]. Power Electronics, 2004, 38(6): 59-61.
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