An Auxiliary Variable-Based MRAS Speed Observer for Stable Wide-Speed Operation in Sensorless Induction Motor Drives

For speed-sensorless induction motors (IMs) that require operation over a wide-speed range, the commonly used rotor flux-based model reference adaptive system (MRAS) cannot guarantee the speed estimation stability for the following two reasons: 1) the poor damping performance of current model (CM) observer resulting in the accuracy degradation and potential discretization instability in high-speed range and 2) the margin stability of the open-loop integrator in voltage model (VM) observer, resulting in the instability issue in low-speed range. To address these problems, this article proposes the corresponding solutions: 1) a coordinate transformation-based Euler method is studied to discretize CM observer leading to stability and accuracy improvement in high-speed range and 2) an auxiliary variable, representing the rotor flux error, is modeled in the VM, and a closed-loop auxiliary variable observer is designed to overcome the open-loop integrator problem. Furthermore, the stability of the overall MRAS is investigated in both continuous domain and discrete domain, verifying the stable wide-speed sensorless operation. Finally, the proposed auxiliary variable-based MRAS is tested on a 3.7-kW IM platform to prove its effectiveness.

Authors

Institutions

Publication Details

Journal
IEEE Journal of Emerging and Selected Topics in Power Electronics
Published
2024-08-13
DOI
https://doi.org/10.1109/jestpe.2024.3443077
Citations
7
Primary Topic
Sensorless Control of Electric Motors
Type
article
Field-Weighted Citation Impact
1.46
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Auxiliary Variable-Based MRAS Speed Observer for Stable Wide-Speed Operation in Sensorless Induction Motor Drives

Zhonglei Zhang, Bo Wang, Tianqing Wang, Yong Yu et al.
7 citations
IEEE Journal of Emerging and Selected Topics in Power Electronics
Sensorless Control of Electric Motors
1.46
article

An Auxiliary Variable-Based MRAS Speed Observer for Stable Wide-Speed Operation in Sensorless Induction Motor Drives

Zhonglei Zhang, Bo Wang, Tianqing Wang, Yong Yu, Dianguo Xu, Shuhui Jin
article en
7 citations

Abstract

For speed-sensorless induction motors (IMs) that require operation over a wide-speed range, the commonly used rotor flux-based model reference adaptive system (MRAS) cannot guarantee the speed estimation stability for the following two reasons: 1) the poor damping performance of current model (CM) observer resulting in the accuracy degradation and potential discretization instability in high-speed range and 2) the margin stability of the open-loop integrator in voltage model (VM) observer, resulting in the instability issue in low-speed range. To address these problems, this article proposes the corresponding solutions: 1) a coordinate transformation-based Euler method is studied to discretize CM observer leading to stability and accuracy improvement in high-speed range and 2) an auxiliary variable, representing the rotor flux error, is modeled in the VM, and a closed-loop auxiliary variable observer is designed to overcome the open-loop integrator problem. Furthermore, the stability of the overall MRAS is investigated in both continuous domain and discrete domain, verifying the stable wide-speed sensorless operation. Finally, the proposed auxiliary variable-based MRAS is tested on a 3.7-kW IM platform to prove its effectiveness.

IEEE Journal of Emerging and Selected Topics in Power ElectronicsVol. 12(5)
Harbin Institute of Technology (CN), Tianjin Research Institute of Electric Science (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 18%
Sensorless Control of Electric Motors
1.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.