English

State-of-charge Estimation of a Li-ion Battery using Deep Learning and Stochastic Optimization

Signal Processing 2020-11-20 v1 Systems and Control Systems and Control

Abstract

This article presents a novel empirical study for the estimation of the State of Charge (SOC) of a lithium-ion (Li-ion) battery which uses a deep learning model with three hidden layers. We model a series of ten vehicle drive cycles that were applied to a Panasonic 18650PF Li-ion cell. Our results show that the choice of the optimization algorithm affects the model performance. The proposed model was able to achieve an error smaller than 1.0% in all drive cycles.

Keywords

Cite

@article{arxiv.2011.09673,
  title  = {State-of-charge Estimation of a Li-ion Battery using Deep Learning and Stochastic Optimization},
  author = {Alexandre Barbosa de Lima and Maurício B. C. Salles and José Roberto Cardoso},
  journal= {arXiv preprint arXiv:2011.09673},
  year   = {2020}
}

Comments

9 pages, 6 figures. arXiv admin note: substantial text overlap with arXiv:2009.09543