Abstract
In this paper, the Model Reference Adaptive System (MRAS) based speed estimation technique is proposed which estimates the rotor speed/position in a vector controlled Synchronous Reluctance Motor (SynRM) drive to give the successful speed sensorless operation of the drive. The functional candidate chosen to build the MRAS system is the reactive power quantity ‘Q’ expressed in terms of dq quantities in voltages and currents. The advantage of using reactive power ‘Q’ as the functional candidate is that it eliminates the presence of stator resistance in the adjustable model thus making the speed estimator independent to stator resistance variations. Apart from it, the speed estimator is free from derivative and integrator terms in the adjustable model. Also, the speed estimator involves simple processing and is not hardware intensive like injection-based speed estimators available in the literature. Finally, the effectiveness of the proposed speed estimator is verified through exhaustive simulations carried out in MATLAB/SIMULINK platform.
Keywords
MRAS
Reactive
Power
Sensorless
SynRM
Vector
Control
Block
diagram:
Fig.
1. Vector Control of SynRM Drive with MRAS Speed Estimator
EXPECTED
SIMULATION RESULTS:
Fig. 2. Variable speed operation including zero speed operation
Fig.
3. Four quadrant operations of SynRM Drive
Fig.
4. Speed estimation under the step change in motor speed
Fig.
5. Speed estimation under the variation in stator resistance at low speed
Fig.
6. Speed estimation under variation in stator resistance at low speeds in all
the four quadrants of operation
Conclusion
A
new speed estimator is proposed for a vector controlled SynRM drive involving
reactive power as the functional candidate in constructing the MRAS reference
and adjustable models. The proposed speed estimator is found to be independent
of stator resistance of the machine, apart from it the speed estimator involves
less signal processing and too is hardware non-intensive. The speed estimator
performs well in all the four quadrants of operation and is proved by performing
the MATLAB simulations. Making the proposed speed estimator totally independent
of the parameters is future aspect of this research.
References
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