A New Charging Algorithm for Li-Ion Battery Packs Based on Artificial Neural Networks
Faria, J.
; Velho, R. L.
;
Calado, M.R.A.
;
Pombo, J.
;
Fermeiro, J.B.L.
;
Mariano, S.J.P.S.
Batteries Vol. 8, Nº 2, pp. 18 - 18, February, 2022.
ISSN (print):
ISSN (online): 2313-0105
Scimago Journal Ranking: 0,76 (in 2022)
Digital Object Identifier: 10.3390/batteries8020018
Abstract
This paper shows the potential of artificial intelligence (AI) in Li-ion battery charging methods by introducing a new charging algorithm based on artificial neural networks (ANNs).
The proposed charging algorithm is able to find an optimized charging current profile, through ANNs, considering the real-time conditions of the Li-ion batteries. To test and validate the proposed approach, a low-cost battery management system (BMS) was developed, supporting up to 168 cells in
series and n cells in parallel. When compared with the multistage charging algorithm, the proposed charging algorithm revealed a shorter charging time (7.85%) and a smaller temperature increase (32.95%). Thus, the results show that the proposed algorithm based on AI is able to effectively charge and balance batteries and can be regarded as a subject of interest for future research.