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/).
Cite this article
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 -