Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)

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Evolving Fuzzy System Applied to Battery Charge Capacity Prediction for Fault Prognostics

Authors
Murilo Camargos, Iury Bessa, Luiz A. Q. Cordovil Junior, Pedro Coutinho, Daniel Furtado Leite, Reinaldo Martinez Palhares
Corresponding Author
Murilo Camargos
Available Online 30 August 2021.
DOI
10.2991/asum.k.210827.010How to use a DOI?
Keywords
Data-driven RUL estimation, Fault prognostics, Evolving fuzzy systems, Takagi–Sugeno fuzzy models
Abstract

This paper addresses the use of data-driven evolving techniques applied to fault prognostics in Li-ion batteries. In such problems, accurate predictions of multiple steps ahead are essential for the Remaining Useful Life (RUL) estimation of a given asset. The fault prognostics’ solutions must be able to model the typical nonlinear behavior of the degradation processes of these assets, and be adaptable to each unit’s particularities. In this context, the Evolving Fuzzy Systems (EFSs) are models capable of representing such behaviors, in addition of being able to deal with non-stationary behavior, also present in these problems. Moreover, a methodology to recursively track the model’s estimation error is presented as a way to quantify uncertainties that are propagated in the long-term predictions. The well-established NASA’s Li-ion batteries data set is used to evaluate the models. The experiments indicate that generic EFSs can take advantage of both historical and stream data to estimate the RUL and its uncertainty.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
Series
Atlantis Studies in Uncertainty Modelling
Publication Date
30 August 2021
ISBN
10.2991/asum.k.210827.010
ISSN
2589-6644
DOI
10.2991/asum.k.210827.010How to use a DOI?
Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Murilo Camargos
AU  - Iury Bessa
AU  - Luiz A. Q. Cordovil Junior
AU  - Pedro Coutinho
AU  - Daniel Furtado Leite
AU  - Reinaldo Martinez Palhares
PY  - 2021
DA  - 2021/08/30
TI  - Evolving Fuzzy System Applied to Battery Charge Capacity Prediction for Fault Prognostics
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 71
EP  - 79
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.010
DO  - 10.2991/asum.k.210827.010
ID  - Camargos2021
ER  -