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Runtime data‐based characterization and torque estimation of switched reluctance motors
Author(s) -
Kucuk Fuat,
Goto Hiroki,
Guo HaiJiao,
Ichinokura Osamu
Publication year - 2013
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.21852
Subject(s) - switched reluctance motor , torque , estimator , control theory (sociology) , direct torque control , nonlinear system , computer science , computation , control engineering , magnetic reluctance , engineering , control (management) , induction motor , algorithm , artificial intelligence , mathematics , mechanical engineering , statistics , physics , quantum mechanics , voltage , magnet , electrical engineering , thermodynamics
High‐performance control of a switched reluctance (SR) motor strictly requires an accurate nonlinear motor model as well as an appropriate control strategy. Since recent modeling methods are either complex or not accurate enough, this paper focuses on overcoming such drawdacks. An experimental method is proposed to collect useful data for modeling a 6/4 SR motor at running condition. Nonlinear modeling is done by an algorithm, which also enables simple static torque computation. The algorithm presents not only the static torque data but also an estimator model for instantaneous torque estimation during real‐time operation, which is very important for most torque control strategies. The nonlinear model is experimantally tested, and its accuracy verified. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.