By Topic

Full Load Range Neural Network Efficiency Optimization of an Induction Motor with Vector Control using Discontinuous PWM

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)
Perron, M. ; Dept. of Electr. Eng., Laval Univ., Que. ; Hoang Le-Huy

Model-based efficiency controllers of induction motors (IM) are known to considerably reduce power losses for loads under 0.50 p.u. by correctly setting the flux under rated value. However, for loads higher than 0.5 p.u., their performance is approximately the same as rated flux vector controllers. It has been recently shown that switching losses and harmonic losses reduction for voltage source inverter (VSI) fed IM can be done by using a discontinuous PWM strategy (DPWM). Hence, this paper proposes a full load range efficiency optimization controller by using an artificial neural network (ANN)-based flux optimizer and a DPWM strategy for both low and high loads. The controller is validated by using a simulation model and comparing its performance with a conventional rated flux controller with space vector PWM (SVPWM). Full load range optimization is achieved with a reduction of fundamental losses of 27% at light load and a 47% reduction of switching and time harmonics losses at high load

Published in:

Industrial Electronics, 2006 IEEE International Symposium on  (Volume:1 )

Date of Conference:

9-13 July 2006