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Wednesday, 10 February 2016

Investigations on Energy Efficient Sensor less Induction Motor Drive


In this paper a high performance induction motor drive without speed sensor is investigated. The rotor flux oriented indirect vector control scheme is used for obtaining high performance. In order to eliminate the speed sensor, a MRAS based speed estimator is designed for gathering the rotor speed information. Also a simple but effective loss minimization algorithm is integrated to calculate the optimal flux for efficiency improvement of the drive. Complete simulation model is
developed in Simulink/MATLAB software. The performance of the developed system I analyzed with different operating conditions.

1.Field oriented control,
2.induction motor,
4.loss minimization algorithm



 Fig. 1. Block diagram of sensor less IFOC induction motor drive


Fig. 2. Block diagram of rotor flux based MRAS speed estimator


Fig. 3. Speed, speed error and flux response with  constant (rated) flux    
 Fig. 4. Speed, speed error and flux response with optimal flux                                                                      
Fig. 5. Low speed tracking response of the  drive with constant (rated) flux     
Fig. 6. Low speed tracking response of the drive  with optimal flux
Fig. 7. Drive response with step load torque  with constant flux mode                                     
  Fig. 8. Drive response with step load torque with optimal flux mode


In this paper, developed model of sensor less induction motor drive in Simulink/MATLAB software is investigated. Speed estimator is also developed using rotor flux based MRAS technique for sensor less operation. For efficiency improvement particularly under partial loads a model based loss minimization technique is applied. The drive performance is investigated for constant flux and the optimal flux. Drive shows good performance with the optimal flux under various operating conditions


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[5] S.M. Gadoue; D. Giaouris and J.W.Finch, “MRAS Sensor less Vector Control of an Induction Motor Using New Sliding-Mode and Fuzzy- Logic Adaptation Mechanisms”, IEEE Transactions on Energy Conversion, Vol. 25 , No. 2, pp. 394 – 402, 2010. 3767, 2012.