Lithium battery SOH estimation through FFNN

The battery health plays a key and decisive role in the use of lithium batteries. In this paper, the battery data detected offline is used to predict SOH through the big data platform algorithm model, in order to acknowledge the current health of the battery. The construction of the learning model i...

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Bibliographic Details
Published in:Journal of physics. Conference series 2022-04, Vol.2260 (1), p.12034
Main Authors: Ye, Zeyu, Liu, Wanbo, Wang, Xuechao, Zhu, Jin, Yin, Jingyuan
Format: Article
Language:English
Subjects:
Algorithms
Big Data
Lithium
Lithium batteries
Physics
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Summary:The battery health plays a key and decisive role in the use of lithium batteries. In this paper, the battery data detected offline is used to predict SOH through the big data platform algorithm model, in order to acknowledge the current health of the battery. The construction of the learning model is carried out through the historical data of 1000 batteries data set, so that the MAE(mean absolute error) is lower than 0.095%.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2260/1/012034