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<p>Lithium-cobalt oxide has become a new generation of highly promising anode materials for lithium-ion batteries due to its low price, environmental friendliness, high platform voltage, and high theoretical capacity. In this paper, the working characteristics and related parameters of lithium-ion batteries are sorted out, and the influence factors of the decline mechanism of lithium-ion batteries are investigated from the perspective of chemical composition. Regarding the cycle life of lithium-ion battery cathode materials, this paper establishes a cycle life prediction model for lithium-ion batteries based on the LSTM model. It optimizes the hyperparameters of the model using the PSO algorithm. In addition, this paper also prepared lithium cobalt oxide cathode materials and carried out a validation analysis of the factors affecting their electrochemical performance. It is found that the cycle life prediction of lithium-ion battery based on LSTM has an RMSE of 3.27%, and the capacity of lithium cobalt oxide soft pack full battery decays from 249.81mAh to 137.04mAh at 26°C. The cycle life of its lithium cobalt oxide lithium-ion battery is around 250 cycles, and the average decay is 0.445mAh during one charge/discharge. Different charge/discharge cycles and diversity will have a significant effect on the cycle life of lithium-ion battery cathode materials, and it is necessary to pay attention to the parameter changes in the preparation of lithium cobalt oxide cathode materials in order to increase the cycle life of lithium-ion batteries.</p>
</abstract>

Lithium-cobalt oxide has become a new generation of highly promising anode materials for lithium-ion batteries due to its low price, environmental friendliness, high platform voltage, and high theoretical capacity. In this paper, the working characteristics and related parameters of lithium-ion batteries are sorted out, and the influence factors of the decline mechanism of lithium-ion batteries are investigated from the perspective of chemical composition. Regarding the cycle life of lithium-ion battery cathode materials, this paper establishes a cycle life prediction model for lithium-ion batteries based on the LSTM model. It optimizes the hyperparameters of the model using the PSO algorithm. In addition, this paper also prepared lithium cobalt oxide cathode materials and carried out a validation analysis of the factors affecting their electrochemical performance. It is found that the cycle life prediction of lithium-ion battery based on LSTM has an RMSE of 3.27%, and the capacity of lithium cobalt oxide soft pack full battery decays from 249.81mAh to 137.04mAh at 26°C. The cycle life of its lithium cobalt oxide lithium-ion battery is around 250 cycles, and the average decay is 0.445mAh during one charge/discharge. Different charge/discharge cycles and diversity will have a significant effect on the cycle life of lithium-ion battery cathode materials, and it is necessary to pay attention to the parameter changes in the preparation of lithium cobalt oxide cathode materials in order to increase the cycle life of lithium-ion batteries.

Cycle life and influencing factors of cathode materials for lithium-ion batteries--a case study of lithium-cobalt oxides

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Lithium-cobalt oxide has become a new generation of highly promising anode materials for lithium-ion batteries due to its low price, environmental...

Cycle life and influencing factors of cathode materials for lithium-ion batteries--a case study of lithium-cobalt oxides

Pubblicato online: 30 mag 2024

Pagine: -

Ricevuto: 15 feb 2024

Accettato: 27 apr 2024

DOI: https://doi.org/10.2478/amns-2024-1285

Parole chiave
LSTM model, PSO algorithm, Lithium cobalt oxide, Lithium-ion battery, Cathode material

© 2024 Haofang Shou, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Cycle life and influencing factors of cathode materials for lithium-ion batteries--a case study of lithium-cobalt oxides

Pubblicato online: 30 mag 2024

Pagine: -

Ricevuto: 15 feb 2024

Accettato: 27 apr 2024

DOI: https://doi.org/10.2478/amns-2024-1285

Parole chiaveLSTM model, PSO algorithm, Lithium cobalt oxide, Lithium-ion battery, Cathode material

© 2024 Haofang Shou, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
LSTM model, PSO algorithm, Lithium cobalt oxide, Lithium-ion battery, Cathode material