Parameter estimation of inverter and motor model at standstill using measured currents only

Rasmussen, Henrik; Knudsen, Morten; Tønnes, Michael

doi:10.1109/isie.1996.548442

Cited by 30 publications

(13 citation statements)

References 10 publications

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“…1. (Tarchała et al, 2011) Algorithmic methods, based on the mathematical model of the machine, depend on the induction motor (IM) parameters and thus are sensitive to motor parameter uncertainty and works stable only in a specified speed region (Rasmusen et al, 1999;Orlowska-Kowalska and Dybkowski, 2010;Tarchała et al, 2011). Those simple solutions, based on simple simulators, like voltage or current models, should be modified.…”

Section: Concept Of the Universal Speed And Flux Estimatormentioning

confidence: 99%

Universal Speed and Flux Estimator for Induction Motor

Dybkowski

2018

Power Electronics and Drives

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In the paper, the concept of universal speed and flux estimator with additional parameters estimators is presented. Proposed solution is based on the Model Reference Adaptive System (MRAS) type flux and speed estimator and can be used in different industrial systems (especially in the automotive applications). Induction Motor (IM) parameters are estimated using the systems based only on simple simulators and adaptive systems (voltage model and current model). Proposed system was tested in the sensorless induction motor drive with the Direct Field Oriented Control (DFOC) algorithm. Simulation and experimental results are presented in the paper.Currently, the sensorless drives are developed as a post faulted application. They are dedicated for the Fault Tolerant Control (FTC) drives , in particular for the drive resistant for the faults of rotor speed sensor or position sensor. Similar properties are required from these systems, like from the universal estimators. Additionally, simple construction and easy tuning of coefficients are required.This paper describes the universal speed and flux estimator with additional IM parameter estimators for the speed sensorless induction motor drives (using DFOC method). Speed estimator is based on the MRAS CC solution (Orlowska-Kowalska and Dybkowski, 2010). All simulation tests were performed in MATLAB Simulink software. Experimental tests were made on the laboratory set-up with DS1103 card.

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Section: Concept Of the Universal Speed And Flux Estimatormentioning

confidence: 99%

Universal Speed and Flux Estimator for Induction Motor

Dybkowski

2018

Power Electronics and Drives

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“…To find the model parameters for the test rig motor used in this study, a modification of the procedure developed by Rasmussen et al [20] and Wiesing et al [21] is used. The modification consists of supplying different steps to find each operating point, rather than using a single voltage step.…”

Section: Supervisory Levelmentioning

confidence: 99%

Takagi-Sugeno Fuzzy Fault-Tolerant Control of an Induction Motor

Lopez-Toribio

Patton

Daley

2000

Neural Computing & Applications

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This paper demonstrates the application of a new fault-tolerant control scheme for a rail vehicle traction system using digital signal processing hardware and a representative induction motor testrig. The approach presented takes into account the stability and design of non-linear fuzzy inference systems based on Takagi-Sugeno (T-S) fuzzy models. The paper derives the necessary conditions for the assignability of eigenvalues to a region in the splane and the necessary conditions to guarantee the stability of adaptive fuzzy models. The problem is solved via the Linear Matrix Inequalities (LMI) method.

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“…Methods based on a flux reversal when single-phase excitation is used have been proposed by several authors [4]- [6]. In [4], the identification was based on a recursive least-squares algorithm while the magnetizing curve was obtained by integration of the stator voltage data in [5], [6]. In [7], the magnetizing inductance was identified by applying a number of voltage steps.…”

Section: Introductionmentioning

confidence: 99%