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Multi-step ahead thermal warning network for energy storage system based on the core temperature detection
The energy storage system is an important part of the energy system. Lithium-ion batteries have been widely used in energy storage systems because of their high energy density and long life. However, the temperature is still the key factor hindering the further development of lithium-ion battery ene...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319405/ https://www.ncbi.nlm.nih.gov/pubmed/34321501 http://dx.doi.org/10.1038/s41598-021-93801-9 |
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author | Li, Marui Dong, Chaoyu Yu, Xiaodan Xiao, Qian Jia, Hongjie |
author_facet | Li, Marui Dong, Chaoyu Yu, Xiaodan Xiao, Qian Jia, Hongjie |
author_sort | Li, Marui |
collection | PubMed |
description | The energy storage system is an important part of the energy system. Lithium-ion batteries have been widely used in energy storage systems because of their high energy density and long life. However, the temperature is still the key factor hindering the further development of lithium-ion battery energy storage systems. Both low temperature and high temperature will reduce the life and safety of lithium-ion batteries. In actual operation, the core temperature and the surface temperature of the lithium-ion battery energy storage system may have a large temperature difference. However, only the surface temperature of the lithium-ion battery energy storage system can be easily measured. The estimation method of the core temperature, which can better reflect the operation condition of the lithium-ion battery energy storage system, has not been commercialized. To secure the thermal safety of the energy storage system, a multi-step ahead thermal warning network for the energy storage system based on the core temperature detection is developed in this paper. The thermal warning network utilizes the measurement difference and an integrated long and short-term memory network to process the input time series. This thermal early warning network takes the core temperature of the energy storage system as the judgment criterion of early warning and can provide a warning signal in multi-step in advance. This detection network can use real-time measurement to predict whether the core temperature of the lithium-ion battery energy storage system will reach a critical value in the following time window. And the output of the established warning network model directly determines whether or not an early emergency signal should be sent out. In the end, the accuracy and effectiveness of the model are verified by numerous testing. |
format | Online Article Text |
id | pubmed-8319405 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-83194052021-07-29 Multi-step ahead thermal warning network for energy storage system based on the core temperature detection Li, Marui Dong, Chaoyu Yu, Xiaodan Xiao, Qian Jia, Hongjie Sci Rep Article The energy storage system is an important part of the energy system. Lithium-ion batteries have been widely used in energy storage systems because of their high energy density and long life. However, the temperature is still the key factor hindering the further development of lithium-ion battery energy storage systems. Both low temperature and high temperature will reduce the life and safety of lithium-ion batteries. In actual operation, the core temperature and the surface temperature of the lithium-ion battery energy storage system may have a large temperature difference. However, only the surface temperature of the lithium-ion battery energy storage system can be easily measured. The estimation method of the core temperature, which can better reflect the operation condition of the lithium-ion battery energy storage system, has not been commercialized. To secure the thermal safety of the energy storage system, a multi-step ahead thermal warning network for the energy storage system based on the core temperature detection is developed in this paper. The thermal warning network utilizes the measurement difference and an integrated long and short-term memory network to process the input time series. This thermal early warning network takes the core temperature of the energy storage system as the judgment criterion of early warning and can provide a warning signal in multi-step in advance. This detection network can use real-time measurement to predict whether the core temperature of the lithium-ion battery energy storage system will reach a critical value in the following time window. And the output of the established warning network model directly determines whether or not an early emergency signal should be sent out. In the end, the accuracy and effectiveness of the model are verified by numerous testing. Nature Publishing Group UK 2021-07-28 /pmc/articles/PMC8319405/ /pubmed/34321501 http://dx.doi.org/10.1038/s41598-021-93801-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Li, Marui Dong, Chaoyu Yu, Xiaodan Xiao, Qian Jia, Hongjie Multi-step ahead thermal warning network for energy storage system based on the core temperature detection |
title | Multi-step ahead thermal warning network for energy storage system based on the core temperature detection |
title_full | Multi-step ahead thermal warning network for energy storage system based on the core temperature detection |
title_fullStr | Multi-step ahead thermal warning network for energy storage system based on the core temperature detection |
title_full_unstemmed | Multi-step ahead thermal warning network for energy storage system based on the core temperature detection |
title_short | Multi-step ahead thermal warning network for energy storage system based on the core temperature detection |
title_sort | multi-step ahead thermal warning network for energy storage system based on the core temperature detection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319405/ https://www.ncbi.nlm.nih.gov/pubmed/34321501 http://dx.doi.org/10.1038/s41598-021-93801-9 |
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