Electrical Drive Radiated Emissions Estimation in Terms of Input Control Using Extreme Learning Machines. (20th December 2012)

• Record Type: Journal Article
• Authors: Wefky, A.; Espinosa, F.; de Santiago, L.; Revenga, P.; Lázaro, J. L.; Martínez, M.
• Other Names: Wang Wuhong Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2012(2012)
• Publication Date: 2012-12-20
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2012/790526
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : 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.