By Topic

Neural network based modeling of audible noise for high frequency injection based position estimation for PM synchronous motors at low and zero speed

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)
Khan, A.A. ; Dept. of Electr. & Comput. Eng., Florida Int. Univ., Miami, FL ; Mohammed, O.

In this paper, the relationship between injected voltages, audible noise and position estimation error is investigated for low speed high frequency injection based position sensorless control of PM synchronous motors. The modeling of noise is done using feed-forward neural network. The model is capable of predicting the audible noise. The proposed model can be used to perform optimization studies for sensitive applications where proper trade off studies between noise and speed/position estimation error is required.

Published in:

Electric Ship Technologies Symposium, 2009. ESTS 2009. IEEE

Date of Conference:

20-22 April 2009