A Hybrid Intelligent Control Method in Application of Battery Management System
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.
KeywordsFuzzy logic Adaptive neuro-fuzzy system dc-dc converter Battery equalization
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).
- 1.Park HS, Kim CE, Kim CH, Moon GW, Lee JH (2009) A modularized charge equalizer for an HEV lithium-ion battery string. IEEE Trans Ind Electron 56(2):1464–1476Google Scholar
- 2.Lindemark B (1991) Individual cell voltage equalizers (ICE) for reliable battery performance. In: Proceedings of the 13th Annual International Telecommunications Energy Conference, Kyotopp, pp 196–201Google Scholar
- 3.Moore SW, Schneider PJ (2001) A review of cell equalization methods for lithium-ion and lithium polymer battery systems. In: Proceedings of the SAE 2001 world congress, DetroitGoogle Scholar
- 5.Lee YS, Jao CW (2003) Fuzzy controlled lithium-ion battery equalization with state-of-charge estimator. In: IEEE International Conference on Systems Man Cybernetics, vol 5, pp 4431–4438Google Scholar
- 7.Jang J (1993) ANFIS: adaptive-network-based Fuzzy inference system. IEEE Trans Syst Man Cybern 23(3):665–685Google Scholar