Proceedings of the 4th International Conference on Information Technology and Management Innovation

Gravitational search algorithm with Gaussian process for lithium-ion batteries state of health (SOH) estimation

Authors
Jing Ye, Santong Zhang, Wei Yang
Corresponding Author
Jing Ye
Available Online October 2015.
DOI
10.2991/icitmi-15.2015.203How to use a DOI?
Keywords
Gaussian process regression, gravitational search algorithm optimization, lithium-ion battery, state of health.
Abstract

State of health (SOH) estimation plays a significant role in battery prognostics. In this paper, Gaussian Process Regression (GPR) is used as a data-driven approach to perform SOH estimation, which supports uncertainty representation and management. At present, the hyper- parameters of GPR are optimized by conjugate gradient algorithm. However, the conjugate gradient algorithm has the shortcomings of too strong dependence on initial value and easily falling into local optimum. In order to improve the prediction precision and generalization ability of GPR, we utilized Gravitational Search Algorithm (GSA) replace of conjugate gradient to search the optimal hyper-parameters during the training process automatically then formed the GSA-GPR algorithm. Experimental results confirm that the proposed method can be effectively applied to lithium-ion batteries SOH estimation by quantitative comparison with the standard GPR algorithms, Genetic Algorithm (GA)-GPR and Particle Swarm Optimization (PSO)-GPR algorithms.

Copyright
© 2015, 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
Proceedings of the 4th International Conference on Information Technology and Management Innovation
Series
Advances in Computer Science Research
Publication Date
October 2015
ISBN
978-94-6252-112-4
ISSN
2352-538X
DOI
10.2991/icitmi-15.2015.203How to use a DOI?
Copyright
© 2015, 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

TY  - CONF
AU  - Jing Ye
AU  - Santong Zhang
AU  - Wei Yang
PY  - 2015/10
DA  - 2015/10
TI  - Gravitational search algorithm with Gaussian process for lithium-ion batteries state of health (SOH) estimation
BT  - Proceedings of the 4th International Conference on Information Technology and Management Innovation
PB  - Atlantis Press
SP  - 1203
EP  - 1210
SN  - 2352-538X
UR  - https://doi.org/10.2991/icitmi-15.2015.203
DO  - 10.2991/icitmi-15.2015.203
ID  - Ye2015/10
ER  -