Open AccessCurrent sensor fault detection and isolation method for PMSM drives, using average normalised currents
Author(s) -
Khojet El Khil S.,
Jlassi I.,
Estima J.O.,
MrabetBellaaj N.,
Marques Cardoso A.J.
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2016.2198
Subject(s) - fault detection and isolation , robustness (evolution) , current sensor , residual , control theory (sociology) , permanent magnet synchronous motor , inverter , computer science , synchronous motor , engineering , control engineering , magnet , electronic engineering , current (fluid) , voltage , algorithm , artificial intelligence , electrical engineering , actuator , biochemistry , chemistry , control (management) , gene
A new approach for current sensor fault detection and isolation (FDI) for permanent magnet synchronous motor (PMSM) drives is presented. Contrary to the classical approaches for sensors fault diagnosis, based on residual generation through observers or parity equations, the proposed technique uses the average normalised machine‐phase currents. The main advantages of this approach are that it does not need any information about the PMSM or inverter models, and it involves low tuning efforts, that make it suitable for real‐time implementation with good reliability. The good performance and the robustness of the proposed FDI approach are illustrated through experimental results.