Self-Commissioning Parameter Estimation Algorithm for Loaded Induction Motors

Induction motor (IM) drive systems are pivotal in modern industrial and commercial applications, driving essential processes and systems across various sectors efficiently and reliably. The accurate estimation of IM and load parameters is challenging but vital to guarantee the optimal performance of...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) Vol. 71; no. 11; pp. 13890 - 13900
Main Authors: Travieso-Torres, Juan Carlos, Lee, Sze Sing, Veliz-Tejo, Adolfo, Leiva-Silva, Felipe, Ricaldi-Morales, Abdiel
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptive algorithms
Adaptive systems
Commissioning
Induction motors
Induction motors (IMs)
Load modeling
model reference adaptive system (MRAS)
Observers
Parameter estimation
Proposals
Real time
Rotors
Stators
ISSN:0278-0046, 1557-9948
Online Access:Get full text
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Summary:Induction motor (IM) drive systems are pivotal in modern industrial and commercial applications, driving essential processes and systems across various sectors efficiently and reliably. The accurate estimation of IM and load parameters is challenging but vital to guarantee the optimal performance of the entire drive system. The IEEE Standard 112A and existing online methods take hours to estimate only IM parameters after shutting down, disconnecting, estimating, reconnecting, and realigning the motor and its load using specialized tools. Offline techniques assume a known IM manufacturer datasheet, which is often unavailable. Therefore, this article proposes a novel online self-commissioning algorithm that estimates the parameters of an IM and its load in a remarkably swift time frame of just 180 s without disconnecting the IM from the load or using the IM manufacturer datasheet. The proposed method only requires the IM nameplate information and employs a discrete normalized model reference adaptive system. In addition, its computational burden is minimal, making it suitable for practical real-time implementation using the commercial and cost-effective microcontroller for power electronics, i.e., c2000 TMS320F28388D control platform. Comprehensive experimental results for fan-type loads driven by 1.1- and 7.5-kW IMs are discussed to validate the proposal.
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ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2024.3357900