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Optimal speed–torque control of doubly-fed induction motors: Analytical and graphical analysis.

Authors :
Zerzeri, Mouna
Khedher, Adel
Source :
Computers & Electrical Engineering. Jul2021, Vol. 93, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

This paper proposes an optimized control approach of a Doubly-Fed Induction Motor (DFIM) based on a field weakening algorithm. This technique ensures a nearly doubled torque–speed operation region in the motor's acceleration and deceleration operation modes. The novelty of the proposed control lies in the fact of using a DFIM for Electric Vehicle (EV) applications where both stator and rotor circuits are connected to voltage source inverters controlled by Space Vector with Pulse Width Modulation (SVPWM) algorithms. Accordingly, the active power distribution law between the stator and rotor sides is thoroughly investigated. This law imposes a relationship between the rotor and stator pulsations leading to a new variation scenario in the DFIM speed. Besides, a Stator Flux Oriented Control (SFOC) is used to provide a decoupled control between the torque and the flux. Considering the voltage and current constraints in the structure, the reference flux is chosen such that the optimal torque for any operation mode, and at any given speed range, is achieved. Nevertheless, the speed measurement as well as the sensitivity to motor parameter variations remains a major limitation in the over-speed region. Therefore, a Sliding Mode Flux Observer (SMFO) is integrated into the control scheme to ensure a sensorless command. The performance of the proposed optimized control algorithm are assessed by computer numerical simulations and its effectiveness in terms of achieving maximum torque in a wide speed range is verified. [Display omitted] • Doubly-fed induction motor fed with two voltage source inverters for electric vehicle applications. • Analytical and graphical resolution based field-weakening control algorithm. • Maximum available torque and power in a wide speed range. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00457906
Volume :
93
Database :
Academic Search Index
Journal :
Computers & Electrical Engineering
Publication Type :
Academic Journal
Accession number :
151952840
Full Text :
https://doi.org/10.1016/j.compeleceng.2021.107258