Joint Estimation of Terminal Voltage and Temperature in Lithium-ion Batteries for Energy Storage

Accurate estimation of lithium-ion battery terminal voltage and temperature is critical to the safe operation of lithiumion batteries. Existing Li-ion battery models cannot consider both accuracy and timeliness. Taking a 280Ah square lithium-ion battery for energy storage as the research object, the article first establishes the thermal circuit-circuit coupling model of the lithium-ion battery; then, according to the experimental data of Hybrid Pulse Power Characterization (HPPC), the least squares algorithm is used to complete the parameter identification of the model. Finally, the model is validated with the experimental data. The results show that the model established in this paper considers both accuracy and timeliness.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/icpea63589.2024.10784755
Citations
1
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.20
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article

Joint Estimation of Terminal Voltage and Temperature in Lithium-ion Batteries for Energy Storage

Fanpeng Zeng, Zhaoyuan Huang, Xianmin Mu
1 citations
Advanced Battery Technologies Research
0.20
article

Joint Estimation of Terminal Voltage and Temperature in Lithium-ion Batteries for Energy Storage

Fanpeng Zeng, Zhaoyuan Huang, Xianmin Mu
article en
1 citations

Abstract

Accurate estimation of lithium-ion battery terminal voltage and temperature is critical to the safe operation of lithiumion batteries. Existing Li-ion battery models cannot consider both accuracy and timeliness. Taking a 280Ah square lithium-ion battery for energy storage as the research object, the article first establishes the thermal circuit-circuit coupling model of the lithium-ion battery; then, according to the experimental data of Hybrid Pulse Power Characterization (HPPC), the least squares algorithm is used to complete the parameter identification of the model. Finally, the model is validated with the experimental data. The results show that the model established in this paper considers both accuracy and timeliness.

Dalian University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 47%
Advanced Battery Technologies Research
0.20
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