Direct vector control of im.

1. SEMINAR ON
FIELD ORIENTED CONTROL OF INDUCTION MOTOR
PRESENTED BY
AMRITA

2. Contents
 Introduction
 Industry application
 FOC types
 Matlab Simulation
 Results comparison using different controllers
 Conclusion

3. Introduction
Drive implementation with SQIM is common in Industry. It aims quick
response, stability, variable speed, disturbance rejection. With FOC of IM it
set to achieve variable frequency drive at all speed using various models and
references. In present thesis using Stanley model and rotor reference frame
direct type FOC is implement and aims to achieve proper implementation of
indirect control at low speed though DFOC is achieved at low speeds using
current estimation.

4. Direct control vs indirect control
 Conventional direct field-oriented control (DFOC)
 Algorithms provide more precision for torque control than scalar schemes
 Require sensors for the speed control of the rotor and the magnetic flux
to provide the data for the FOC algorithms.
 They also face challenges in the dynamic response and the dependence
on measuring the parameters in the motor.
 Good at high speed as current model fails to give sufficient response
 Instead an indirect field-oriented control (IFOC) method estimates the
phase angle of the rotor magnetic field flux, eliminating the need for
additional sensors.

5. Continued..
 Adds to the complexity and the computation time of
the control system.
 Good at below zero and start up
 schemes, but require sensors for the speed control of
the rotor and the magnetic flux to provide the data for
the FOC algorithms. They also face challenges in the
dynamic response and the dependence on measuring
the parameters in the motor.

6. Application
 Applications from pumps and fans to conveyors
 Industrial automation
 Elevators
 Textile and paper mills
 Electric vehicle
 Hoists

7. FOC
 It is usually oriented in rotor flux linkage vector.
 Uses coordinate transformation.
 Separate regulation of flux and torque by regulation of stator current
decomposition.
 Cascade controllers need to be tuned.
 Multiple mathematical transformation done.
 Machine parameters to be very precise for proper alignment.

8. DIRECT VECTOR DIAGRAM WITH ROTOR FLUX ORIENTATION

9. Matlab diagram

10. The machine parameters for 3KW/4HP 3phase 380V IM
Rs=2.2
Lls=0.012
Rr=2.68
Llr=0.012
Lm=0.217
Lr=0.229
Ls=0.229
Ts=2e-6
P=4
Tr=0.0854
It takes 0.386 seconds to reach steady state at no load.
Following machine parameters used in simulink

11. Response comparison at no loads and T= [0 3 6 0] at [0 2 4 6] seconds.
Figure 1 Figure 2

12. Responses with
controllers(conventional PI
and FLC)
du e
de
NS Z PS PM PL
NS NS NS Z PS PM
Z NS Z PS PM PL
PS Z PS PM PL PL
PM PS PM PL PL PL
PL PM PL PL PL PL
By trial and error method found
Flux loop
Kp=3
Ki=0.1
Speed loop
Kp=2
Ki=10
Membership function rule

13. Speed response
FIGURE 1A (FLC) FIGURE 2A(PI)

14. Torque Response
Figure 1b (FLC) Figure 2b(PI)

15. Figure 1c,1d
Figure 2c,2d
CURRENT AND ROTOR FLUX PLOT

16. Conclusion and work to do
 DFOC can be implemented on voltage model and current model. Simulation to be done in
Simulink after implementing both models in separately and hybrid model using current model
requires proper sensor.
 FOC is variable frequency drive control method in which the stator currents of a three-phase AC
or brushless DC electric motor are identified as two orthogonal components or vectors. In FOC
IM is treated like separately excited dc machine. The direct FOC is implemented using voltage
model.The Tuning of PI controller is but response at low speed is not sufficient.The fuzzy logic
control based sensorless FDFOC performance is more efficient in comparison with the PI control
based sensorless DFOC. The main improvements of the new structure are quick load torque
rejection and quick response, decrease of the stator phase current on startup, elimination of
the overshoot and the steady state errors, system stability, good dynamic behaviour in normal
directions at low speeds.Flux response is better in case of fuzzy controller
 The hybrid model with indirect type of control with direct type can be developed.