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Mathematical Problems in Engineering
Volume 2012, Article ID 790526, 11 pages
Research Article

Electrical Drive Radiated Emissions Estimation in Terms of Input Control Using Extreme Learning Machines

Electronics Department, Polytechnics School, University of Alcalá, Campus Universitario 28871, Alcalá de Henares, Spain

Received 21 September 2012; Revised 9 November 2012; Accepted 9 November 2012

Academic Editor: Wuhong Wang

Copyright © 2012 A. Wefky et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


With the increase of electrical/electronic equipment integration complexity, the electromagnetic compatibility (EMC) becomes one of the key points to be respected in order to meet the constructor standard conformity. Electrical drives are known sources of electromagnetic interferences due to the motor as well as the related power electronics. They are the principal radiated emissions source in automotive applications. This paper shows that there is a direct relationship between the input control voltage and the corresponding level of radiated emissions. It also introduces a novel model using artificial intelligence techniques for estimating the radiated emissions of a DC-motor-based electrical drive in terms of its input voltage. Details of the training and testing of the developed extreme learning machine (ELM) are described. Good agreement between the electrical drive behavior and the developed model is observed.