scholarly journals A Novel Analytical Approach Using Rough Set and Genetic Algorithm of a Stable Sensorless Induction Motor Drives in the Regenerating Mode

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 157748-157761
Author(s):  
Mohamed S. Zaky ◽  
Tamer Fetouh ◽  
Shaaban M. Shaaban ◽  
Haitham Z. Azazi
Keyword(s):  
Genetic Algorithm ◽  
Induction Motor ◽  
Rough Set ◽  
Analytical Approach ◽  
Motor Drives ◽  
Induction Motor Drives ◽  
Regenerating Mode

scholarly journals Sensorless Induction Motor Drives Using Adaptive Flux Observer at Low Frequencies

2018 ◽  
Vol 8 (1) ◽  
pp. 2572-2576 ◽  
Author(s):  
M. S. Zaky ◽  
H. A. Maksoud ◽  
H. Z. Azazi
Keyword(s):  
Induction Motor ◽  
Motor Drives ◽  
Operating Conditions ◽  
Estimation Methods ◽  
Speed Estimation ◽  
Induction Motor Drives ◽  
Machine Model ◽  
Low Frequencies ◽  
Flux Observer ◽  
Regenerating Mode

Operation at low frequencies of sensorless drives using machine model-based estimation methods is a challenging issue. This paper proposes an adaptive flux observer (AFO) method of speed estimation for sensorless induction motor drives. The observer feedback gains are designed to guarantee accurate speed estimation, especially at low frequencies in the regenerating mode operation. A complete sensorless IM drive with the proposed AFO is executed in the laboratory. Extensive experimental results under different operating conditions are provided to prove the effectiveness of the proposed AFO, particularly under low stator frequencies in both motoring and regenerating modes of operation.

Sign in / Sign up

Export Citation Format

Share Document