Title :
Artificial neural network control and energy management in 42 V DC link
Author :
Marie-Francoise, J.N. ; Gualous, H. ; Berthon, A.
Author_Institution :
Lab. of Electr. Eng. & Syst., UFC-UTBM
Abstract :
This paper deals with an experimental realization of a 42 V hybrid power sources for automotive applications. It´s composed by a battery which provides the power in constant mean power and a supercapacitor tank in order to supply power in transient state. Two DC/DC converters are used to adapt voltage and current levels between the 42 V DC link, battery and supercapacitor tank. Voltage is regulated by using artificial neural networks (ANNs)
Keywords :
DC-DC power convertors; automotive engineering; energy management systems; neurocontrollers; supercapacitors; 42 V; DC link energy management; DC-DC converters; artificial neural network control; automotive applications; hybrid power sources; supercapacitor tank; transient state; Artificial neural networks; Automotive applications; Batteries; Control systems; DC-DC power converters; Energy management; Intelligent networks; Power supplies; Supercapacitors; Voltage; Automotive application; DC power supply; Energy storage; Energy system management; Neuronal control;
Conference_Titel :
Power Electronics and Applications, 2005 European Conference on
Conference_Location :
Dresden
Print_ISBN :
90-75815-09-3
DOI :
10.1109/EPE.2005.219615
