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Estimation of phase inductance profile in a three-phase 6/4 pole switched reluctance machine

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This paper presents a non-linear inductance profile estimation of a Switched Reluctance Machine (SRM) using real-time applicable modelling techniques. The estimation techniques are based on regression analysis and Adaptive Neuro-Fuzzy Inference System (ANFIS). Mathematical models of phase inductance
L
(
I
,
θ
) using both the techniques have been successfully tested for various values of phase currents (
I
ph

) and rotor positions (
θ
) of a non-linear SRM. It is observed that the proposed techniques are highly suitable for inductance
L
(
I
,
θ
) modelling of SRM, which is found to be in good agreement with the training data used for modelling.

Keywords: non-linear inductance model, regression technique, ANFIS, adaptive neuro-fuzzy inference system, multiple regression, SRM, switched reluctance machine, power electronics

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