Remaining Useful Life Prediction of Power Lithium-Ion Battery based on Artificial Neural Network Model

DOI

10.2991/mecae-17.2017.70How to use a DOI?

Keywords

Power Lithium-Ion Battery, Remaining Useful Life, Artificial Neural Network Model, Prediction Method.

Abstract

In order to improve the security and reliability of the power lithium batteries, this paper introduced forecast and health management technology of its core content-remaining useful life, established a power lithium battery remaining useful life prediction method, by collecting current, batteries, battery voltage, temperature, battery SOC and SOH etc data, artificial intelligence model based on neural network, training model parameters, the prediction power lithium battery remaining useful life, simulation results show the advances and reliability of this method

Copyright

© 2017, 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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TY  - CONF
AU  - Enguang Hou
AU  - Xin Qiao
AU  - Guangmin Liu
PY  - 2017/03
DA  - 2017/03
TI  - Remaining Useful Life Prediction of Power Lithium-Ion Battery based on Artificial Neural Network Model
BT  - Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)
PB  - Atlantis Press
SP  - 371
EP  - 374
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-17.2017.70
DO  - 10.2991/mecae-17.2017.70
ID  - Hou2017/03
ER  -