The Research of the Detecting System for the Battery Cycle Life of the Train

DOI

10.2991/eeeis-17.2017.19How to use a DOI?

Keywords

Battery management system; artificial neural network; Cycle life; state of charge (SOC)

Abstract

The train storage batteries are mainly providing power for train control system and emergency ventilation system. The performance of the vehicle battery status directly affects the safety of the train. Because the cell of batteries is difference, leading to a sharp drop in battery performance and cycle life shortened. Based on the hardware and software platforms of American national instruments(NI), application of artificial neural network algorithm, researching and developing the online detection system of the train battery life. Implementation on the performance of battery state detection and battery life estimates. When using the system on one storage battery, the result shows that the system has some characteristics of simple operation, accurate testing, stability and friendly interface.

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  - Jian-Gang CAO
AU  - Jian FENG
PY  - 2017/09
DA  - 2017/09
TI  - The Research of the Detecting System for the Battery Cycle Life of the Train
BT  - Proceedings of the 3rd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2017)
PB  - Atlantis Press
SP  - 128
EP  - 133
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-17.2017.19
DO  - 10.2991/eeeis-17.2017.19
ID  - CAO2017/09
ER  -