Predicting Remaining Useful Life of Lithium-Ion Battery Using Extended Belief Rule Base Model

Long Hao Yang; Bei Ya Qian; Chen Xi Huang; Fei Fei Ye; Haibo Hu; Hai Dong Wu

doi:10.1109/ISKE60036.2023.10480946

Predicting Remaining Useful Life of Lithium-Ion Battery Using Extended Belief Rule Base Model

Long Hao Yang
, Bei Ya Qian
, Chen Xi Huang
, Fei Fei Ye
, Haibo Hu
, Hai Dong Wu

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

The development of new energy vehicles is a key factor in the adjustment of China's energy structure and the decrease in carbon emissions. It is a frontier field for China to achieve high-quality development and construct a modern socialist nation fully. However, because lithium-ion battery used in new energy vehicles have a limited lifespan, it is likely to have a very significant security risk when the lithium-ion battery is not replaced in a timely manner. Predicting the lithium-ion battery's remaining useful life (RUL) is crucial for this reason. In order to forecast the RUL while taking health indicators (HI) into account, the extended belief rule base (EBRB) model is introduced in this paper. The EBRB model's capacity to handle complicated modeling issues helps to increase the RUL prediction's accuracy and interpretability. This study is of great significance for promoting the development of new energy vehicles, adjusting China's energy structure, and reducing carbon emissions.

Original language	English
Title of host publication	ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	585-591
Number of pages	7
ISBN (Electronic)	9798350318401
DOIs	https://doi.org/10.1109/ISKE60036.2023.10480946
Publication status	Published - Apr 2024
Event	18th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2023 - Fuzhou, China Duration: 17 Nov 2023 → 19 Nov 2023

Publication series

Name	ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering

Conference

Conference	18th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2023
Country/Territory	China
City	Fuzhou
Period	17/11/23 → 19/11/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

data-driven
extended belief rule base
health indicators
lithium-ion battery
remaining useful life

ASJC Scopus subject areas

Artificial Intelligence
Computational Theory and Mathematics
Computer Science Applications
Computer Vision and Pattern Recognition
Safety, Risk, Reliability and Quality
Computational Mathematics

More information

10.1109/ISKE60036.2023.10480946

Cite this

Yang, L. H., Qian, B. Y., Huang, C. X., Ye, F. F., Hu, H., & Wu, H. D. (2024). Predicting Remaining Useful Life of Lithium-Ion Battery Using Extended Belief Rule Base Model. In ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering (pp. 585-591). Article 198734 (ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISKE60036.2023.10480946

Yang, Long Hao ; Qian, Bei Ya ; Huang, Chen Xi et al. / Predicting Remaining Useful Life of Lithium-Ion Battery Using Extended Belief Rule Base Model. ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering. Institute of Electrical and Electronics Engineers Inc., 2024. pp. 585-591 (ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering).

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abstract = "The development of new energy vehicles is a key factor in the adjustment of China's energy structure and the decrease in carbon emissions. It is a frontier field for China to achieve high-quality development and construct a modern socialist nation fully. However, because lithium-ion battery used in new energy vehicles have a limited lifespan, it is likely to have a very significant security risk when the lithium-ion battery is not replaced in a timely manner. Predicting the lithium-ion battery's remaining useful life (RUL) is crucial for this reason. In order to forecast the RUL while taking health indicators (HI) into account, the extended belief rule base (EBRB) model is introduced in this paper. The EBRB model's capacity to handle complicated modeling issues helps to increase the RUL prediction's accuracy and interpretability. This study is of great significance for promoting the development of new energy vehicles, adjusting China's energy structure, and reducing carbon emissions.",

keywords = "data-driven, extended belief rule base, health indicators, lithium-ion battery, remaining useful life",

author = "Yang, \{Long Hao\} and Qian, \{Bei Ya\} and Huang, \{Chen Xi\} and Ye, \{Fei Fei\} and Haibo Hu and Wu, \{Hai Dong\}",

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year = "2024",

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doi = "10.1109/ISKE60036.2023.10480946",

language = "English",

series = "ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering",

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Yang, LH, Qian, BY, Huang, CX, Ye, FF, Hu, H & Wu, HD 2024, Predicting Remaining Useful Life of Lithium-Ion Battery Using Extended Belief Rule Base Model. in ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering., 198734, ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering, Institute of Electrical and Electronics Engineers Inc., pp. 585-591, 18th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2023, Fuzhou, China, 17/11/23. https://doi.org/10.1109/ISKE60036.2023.10480946

Predicting Remaining Useful Life of Lithium-Ion Battery Using Extended Belief Rule Base Model. / Yang, Long Hao; Qian, Bei Ya; Huang, Chen Xi et al.
ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering. Institute of Electrical and Electronics Engineers Inc., 2024. p. 585-591 198734 (ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AU - Yang, Long Hao

AU - Qian, Bei Ya

AU - Huang, Chen Xi

AU - Ye, Fei Fei

AU - Hu, Haibo

AU - Wu, Hai Dong

PY - 2024/4

Y1 - 2024/4

N2 - The development of new energy vehicles is a key factor in the adjustment of China's energy structure and the decrease in carbon emissions. It is a frontier field for China to achieve high-quality development and construct a modern socialist nation fully. However, because lithium-ion battery used in new energy vehicles have a limited lifespan, it is likely to have a very significant security risk when the lithium-ion battery is not replaced in a timely manner. Predicting the lithium-ion battery's remaining useful life (RUL) is crucial for this reason. In order to forecast the RUL while taking health indicators (HI) into account, the extended belief rule base (EBRB) model is introduced in this paper. The EBRB model's capacity to handle complicated modeling issues helps to increase the RUL prediction's accuracy and interpretability. This study is of great significance for promoting the development of new energy vehicles, adjusting China's energy structure, and reducing carbon emissions.

AB - The development of new energy vehicles is a key factor in the adjustment of China's energy structure and the decrease in carbon emissions. It is a frontier field for China to achieve high-quality development and construct a modern socialist nation fully. However, because lithium-ion battery used in new energy vehicles have a limited lifespan, it is likely to have a very significant security risk when the lithium-ion battery is not replaced in a timely manner. Predicting the lithium-ion battery's remaining useful life (RUL) is crucial for this reason. In order to forecast the RUL while taking health indicators (HI) into account, the extended belief rule base (EBRB) model is introduced in this paper. The EBRB model's capacity to handle complicated modeling issues helps to increase the RUL prediction's accuracy and interpretability. This study is of great significance for promoting the development of new energy vehicles, adjusting China's energy structure, and reducing carbon emissions.

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ER -

Yang LH, Qian BY, Huang CX, Ye FF, Hu H, Wu HD. Predicting Remaining Useful Life of Lithium-Ion Battery Using Extended Belief Rule Base Model. In ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering. Institute of Electrical and Electronics Engineers Inc. 2024. p. 585-591. 198734. (ISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering). doi: 10.1109/ISKE60036.2023.10480946

Predicting Remaining Useful Life of Lithium-Ion Battery Using Extended Belief Rule Base Model

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

More information

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