scholarly journals Simple Hybrid Model for Efficiency Optimization of Induction Motor Drives with Its Experimental Validation

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Branko Blanuša ◽  
Bojan Knezevic
Keyword(s):  
Induction Motor ◽  
Hybrid Model ◽  
Experimental Tests ◽  
Motor Drives ◽  
Control Technique ◽  
Induction Motor Drives ◽  
Loss Model ◽  
Efficiency Optimization ◽  
Model Control ◽  
Search Control

New hybrid model for efficiency optimization of induction motor drives (IMD) is presented in this paper. It combines two strategies for efficiency optimization: loss model control and search control. Search control technique is used in a steady state of drive and loss model during transient processes. As a result, power and energy losses are reduced, especially when load torque is significant less related to its rated value. Also, this hybrid method gives fast convergence to operating point of minimal power losses and shows negligible sensitivity to motor parameter changes regarding other published optimization strategies. This model is implemented in vector control induction motor drive. Simulations and experimental tests are performed. Results are presented in this paper.

scholarly journals Design of Robust Adaptive Observer against Measurement Noise for Sensorless Vector Control of Induction Motor Drives

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Asma Boulmane ◽  
Youssef Zidani ◽  
Mohammed Chennani ◽  
Driss Belkhayat
Keyword(s):  
Induction Motor ◽  
Position Control ◽  
Motor Drives ◽  
Measurement Noise ◽  
Adaptive Observer ◽  
Control Technique ◽  
Induction Motor Drives ◽  
Sensor Noise ◽  
Parametric Variation ◽  
Luenberger Observer

Position control in electrical drives is a challenging problem which is complicated by sensor noise and unknown disturbances. This paper proposes a new cascade sensorless speed control technique for induction motor drives suitable for electric vehicle applications using the full-order adaptive Luenberger observer that is insensitive to measurement noise and parametric variation. The adaptive speed law is obtained by the Lyapunov method using the estimated currents and fluxes. This technique ensures the stability of the induction motor considered as nonlinear dynamic system. Since the Luenberger observer works on deterministic environment, and it is most effective when sensor noise is limited, the present study aims to design a robust observer insensitive to measurement noise and parametric variation integrated in a cascade structure. The observer allows the filtering of the measured currents. To highlight the advantages of the new scheme, a comparative study and spectrum analysis will be presented. The proposed structure is verified using MATLAB/Simulink.

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