Paper Info
Title
Data-model alliance network for the online multi-step thermal warning of energy storage system based on surface temperature diffusion
Abstract
As an important type of energy storage, battery energy storage systems have been widely used. However, there are frequent cases of battery explosion due to high temperature. To address this issue, researches have been carried out either in the model-driven or the data-driven aspects to predict the temperature of the battery. In this paper, a two-node electrothermal model and a multi-scale long short-term memory network are established formulating a data-model alliance network (DMAN) for surface temperature diffusion. An improved adaptive boosting algorithm is then employed to enhance the bridge of the two models. Integrating a data-model alliance module (DMAM) and multi-step-ahead thermal warning network (MATWN), this DMAN provides an advanced online multi-step-ahead thermal warning structure to achieve early warning of temperature crossing. Experimental results verify the progressiveness of the proposed technique.
Year
DOI
Venue
2022
10.1016/j.patter.2021.100432
Patterns
Keywords
DocType
Volume
thermal warning,data-model alliance network,long short-term memory network
Journal
3
Issue
ISSN
Citations 
2
2666-3899
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Marui Li100.34
Chaoyu Dong200.34
Yunfei Mu352.39
Xiaodan Yu412.39
Qian Xiao543.96
Hong Jie Jia61412.35