Share Email Print
cover

Proceedings Paper • new

A research on cell inconsistency prediction of power battery using Gaussian process regression
Author(s): Liu Ling; Song Chao; Yong-bo Xie; Wen-ming Wang; Xiong Gang; Li Xi
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Cell inconsistency affect battery life and driving safety. In order to solve the accuracy problem of online prediction of cell inconsistency of power battery, battery characteristic analysis based on of vehicle network big data is proceeded, health indicator(HI), based on the cell terminal voltage difference,is proposed through the degradation model; As the similar distribution of cell terminal voltage difference between battery discharge conditions, the health indicator sequence based on SOC(State of Charge) is constructed, and the next health indicator is predicted by Gaussian process regression. The prediction results show that the method requires less training samples and less hardware resources, and the overall prediction accuracy is not less than 85%, which can meet the practical requirements.

Paper Details

Date Published: 27 November 2019
PDF: 13 pages
Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 1132120 (27 November 2019); doi: 10.1117/12.2542386
Show Author Affiliations
Liu Ling, Tongji Univ. (China)
Song Chao, Hunan CRRC Times Electric Vehicle Co., Ltd. (China)
Yong-bo Xie, Hunan CRRC Times Electric Vehicle Co., Ltd. (China)
Wen-ming Wang, Hunan CRRC Times Electric Vehicle Co., Ltd. (China)
Xiong Gang, Hunan CRRC Times Electric Vehicle Co., Ltd. (China)
Li Xi, Hunan CRRC Times Electric Vehicle Co., Ltd. (China)


Published in SPIE Proceedings Vol. 11321:
2019 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

© SPIE. Terms of Use
Back to Top