Measurement of induction motor parameter identification

Chen, T.C.; Chen, J.S.; Tsai, Chin‐Chun

doi:10.1109/imtc.1991.161597

Cited by 4 publications

(1 citation statement)

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“…Proposition 1: Let • , and be the matrices and vectors defined in Section III-A • , and be the matrices of the polynomial coefficient of and , respectively; hence, the following relation holds: (26) Proof: Consider the problem (27) The extension of (27) to (26) is straightforward. By means of relations and , it is easy to verify that (27) can be rewritten as (28) where .…”

Section: Appendixmentioning

confidence: 99%

Parameter estimation of induction motor at standstill with magnetic flux monitoring

Castaldi

Tilli

2005

IEEE Trans. Contr. Syst. Technol.

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The paper presents a new method for the estimation of the electric parameters of induction motors (IMs). During the identification process the rotor flux is also estimated. The procedure relies on standstill tests performed with a standard drive architecture, hence, it is suitable for self-commissioning drives. The identification scheme is based on the model reference adaptive system (MRAS) approach. A novel parallel adaptive observer (PAO) has been designed, starting from the series-parallel Kreisselmeier observer. The most interesting features of the proposed method are the following: 1) rapidity and accuracy of the identification process; 2) low-computational burden; 3) excellent noise rejection, thanks to the adopted parallel structure; 4) avoidance of incorrect parameter estimation due to magnetic saturation phenomena, thanks to recursive rotor flux monitoring. The performances of the new scheme are shown by means of simulation and experimental tests. The estimation results are validated by comparison with a powerful batch nonlinear least square (NLS) method and by evaluating the steady-state mechanical curve of the IM used in the tests.

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