Different viable torque control schemes of induction motor for electric propulsion systems

被引:0
作者
Vasudevan, M [1 ]
Arumugam, R [1 ]
机构
[1] St Josephs Coll Engn, Madras, Tamil Nadu, India
来源
CONFERENCE RECORD OF THE 2004 IEEE INDUSTRY APPLICATIONS CONFERENCE, VOLS 1-4: COVERING THEORY TO PRACTICE | 2004年
关键词
field oriented control; direct torque control; stator resistance; ANFIS and electric propulsion systems;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents a detailed comparison between various control strategies, emphasizing advantages and disadvantages. The scope of this paper is to choose an adaptive induction motor drive for an electric propulsion system. Recent advances in induction motor control have made it suitable for fast dynamic response applications. In this paper, the performance of the various control schemes such as Indirect Field Oriented Control (IFOC), Direct Field Oriented Control (DFOC), Direct Torque Control (DTC) and Neuro-Fuzzy DTC (DTNFC) are evaluated. The analysis has been carried out on the basis of the results obtained by numerical simulations. A new estimator is also designed to estimate the stator resistance of induction motor. The sensitivity of DTC to temperature variations, leading to stator resistance changes, is eliminated by online estimation of stator resistance. In this paper, detailed analysis and investigation are carried out and an adaptive control is proposed for electric propulsion system.
引用
收藏
页码:2728 / 2737
页数:10
相关论文
共 20 条
[1]  
BIDEN P, 2000, IEEE T POWER ELECT, V16
[2]   EXPERT-SYSTEM, FUZZY-LOGIC, AND NEURAL-NETWORK APPLICATIONS IN POWER ELECTRONICS AND MOTION CONTROL [J].
BOSE, BK .
PROCEEDINGS OF THE IEEE, 1994, 82 (08) :1303-1323
[3]   A simple direct-torque neuro-fuzzy control of PWM-inverter-fed induction motor drive [J].
Grabowski, PZ ;
Kazmierkowski, MP ;
Bose, BK ;
Blaabjerg, F .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2000, 47 (04) :863-870
[4]  
GRABOWSKI PZ, SIMPLE DIRECT TORQUE
[5]   ANFIS - ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEM [J].
JANG, JSR .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1993, 23 (03) :665-685
[6]   NEURO-FUZZY MODELING AND CONTROL [J].
JANG, JSR ;
SUN, CT .
PROCEEDINGS OF THE IEEE, 1995, 83 (03) :378-406
[7]   IGSPICE SIMULATION OF INDUCTION MACHINES WITH SATURABLE INDUCTANCES [J].
KEYHANI, A ;
TSAI, H .
IEEE TRANSACTIONS ON ENERGY CONVERSION, 1989, 4 (01) :118-125
[8]  
Krose B. J. A., 1991, INTRO NEURAL NETWORK
[9]   MODELING AND SIMULATION OF INDUCTION-MOTORS WITH SATURABLE LEAKAGE REACTANCES [J].
LIPO, TA ;
CONSOLI, A .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 1984, 20 (01) :180-189
[10]   THE INFLUENCE OF SATURATION ON INDUCTION MACHINE DRIVE DYNAMICS [J].
MELKEBEEK, JAA ;
NOVOTNY, DW .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 1983, 19 (05) :671-681