By Topic

Parameter identification of induction motors using dynamic encoding algorithm for searches (DEAS)

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jong-Wook Kim ; Electr. Steel Sheet Res. Group, POSCO Tech. Res. Labs., Pohang, South Korea ; Sang Woo Kim

A newly developed optimization algorithm, called the dynamic encoding algorithm for searches (DEAS), is introduced and applied to the parameter identification of an induction motor for vector control and fault detection. Digital simulations are conducted on startup with no load and normal operation with load perturbations. DEAS is compared with the continuous-time prediction error method and the genetic algorithm via identification performance using the startup signals. The capability of onload identification using the proposed technique is also verified with transient signals. Consequently, DEAS is shown to locate more precise parameter values than both the compared methods especially with much faster execution time than the genetical algorithm.

Published in:

Energy Conversion, IEEE Transactions on  (Volume:20 ,  Issue: 1 )