Study on the parameter identification of lithium-ion battery model under high-rate pulse discharge conditions

With the rapid development of the new energy sector and lithium-ion (Li-ion) battery technologies, using Li-ion batteries with high energy density and high discharge rate to form the primary energy subsystem can further improve the compactness and miniaturization level of pulsed power systems. In traditional electric power systems, Li-ion batteries normally operate under the discharge condition of low current and long time. However, as the main power source of pulsed power systems, it is required that Li-ion batteries should have the capability for high-rate pulse discharge. To ensure the safe and reliable operation of the battery energy storage system, it is necessary to conduct the parameter identification of the Li-ion battery model to establish an accurate pulse discharge model under such working conditions. This paper focuses on the discharge characteristics of a cylindrical high-rate single Li-ion battery with a capacity of 3 Ah. At a 20 C rate, the discharge data were obtained when the pulse repetition frequency was 10 Hz and the duty cycle was 90%. By using the mathematical expressions of the Thevenin equivalent circuit model, the recursive relationship of the circuit parameters was obtained, and the parameter identification of the battery model was conducted based on the experimental data by using the genetic algorithm. The results show that the fitting accuracy of the parameter identification reaches 0.9995, indicating the high precision of the model for the Li-ion battery. This work provides a significant reference for the modeling and parameter identification of Li-ion batteries under high-rate pulse discharge conditions.

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Publication Details

Journal
AIP Advances
Published
2024-10-01
DOI
https://doi.org/10.1063/5.0232147
Citations
2
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.41
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article

Study on the parameter identification of lithium-ion battery model under high-rate pulse discharge conditions

T Hu, Huibo Zhang, Zenghui Yang, Zicheng Zhang
2 citations
AIP Advances
Advanced Battery Technologies Research
0.41
article

Study on the parameter identification of lithium-ion battery model under high-rate pulse discharge conditions

T Hu, Huibo Zhang, Zenghui Yang, Zicheng Zhang
article en
2 citations

Abstract

With the rapid development of the new energy sector and lithium-ion (Li-ion) battery technologies, using Li-ion batteries with high energy density and high discharge rate to form the primary energy subsystem can further improve the compactness and miniaturization level of pulsed power systems. In traditional electric power systems, Li-ion batteries normally operate under the discharge condition of low current and long time. However, as the main power source of pulsed power systems, it is required that Li-ion batteries should have the capability for high-rate pulse discharge. To ensure the safe and reliable operation of the battery energy storage system, it is necessary to conduct the parameter identification of the Li-ion battery model to establish an accurate pulse discharge model under such working conditions. This paper focuses on the discharge characteristics of a cylindrical high-rate single Li-ion battery with a capacity of 3 Ah. At a 20 C rate, the discharge data were obtained when the pulse repetition frequency was 10 Hz and the duty cycle was 90%. By using the mathematical expressions of the Thevenin equivalent circuit model, the recursive relationship of the circuit parameters was obtained, and the parameter identification of the battery model was conducted based on the experimental data by using the genetic algorithm. The results show that the fitting accuracy of the parameter identification reaches 0.9995, indicating the high precision of the model for the Li-ion battery. This work provides a significant reference for the modeling and parameter identification of Li-ion batteries under high-rate pulse discharge conditions.

AIP AdvancesVol. 14(10)
National University of Defense Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 40%
Advanced Battery Technologies Research
0.41
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Study on the parameter identification of lithium-ion battery model under high-rate pulse discharge conditions — T Hu, Huibo Zhang, et al. · AIP Advances (2024) | TGRS Research Map | TGRS