A Hybrid Intelligent Control Method in Application of Battery Management System

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 240)

Abstract

This paper presents a hybrid adaptive neuro-fuzzy algorithm in application of battery management system. The proposed system employed the Cuk converter as equalizing circuit, and utilized a hybrid adaptive neuro-fuzzy as control method for the equalizing current. The proposed system has ability for tracking dynamic reactions on battery packs, due to taking advantages of adaptability and learning ability of adaptive neuro-fuzzy algorithm. The current output generated from learning process drives Pulse-Width-Modulation (PWM) signals. This current output is observed and collected for next coming learning process. The feedback line is provided for current output observation. The results demonstrate the proposed scheme has the ability to learn previous stages. Therefore, the proposed system has adaptability to deal with changing of working conditions.

Keywords

Fuzzy logic Adaptive neuro-fuzzy system dc-dc converter Battery equalization 

Notes

Acknowledgment

This work was supported by the development program of local science park funded by the ULSAN Metropolitan City and the MEST (Ministry of Education, Science and Technology).

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Copyright information

© Springer Science+Business Media Dordrecht(Outside the USA) 2013

Authors and Affiliations

  1. 1.School of Electrical and Computer EngineeringUlsan National Institute of Science and TechnologyUlsanSouth Korea

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