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Calendar Ageing Model for Li-Ion Batteries Using Transfer Learning MethodsBeste instituzio
IkerlanBertsioa
Bertsio argitaratua
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© 2021 by the authors. Licensee MDPISarbidea
Sarbide irekiaArgitaratzailearen bertsioa
https://doi.org/10.3390/wevj12030145Non argitaratua
World Electric Vehicle Journal Vol 12. N. 3. N. artículo. 145, 2021Argitaratzailea
MDPIGako-hitzak
machine learning
transfer learning
lithium-ion batteries
calendar ageing ... [+]
transfer learning
lithium-ion batteries
calendar ageing ... [+]
machine learning
transfer learning
lithium-ion batteries
calendar ageing
artificial neural network [-]
transfer learning
lithium-ion batteries
calendar ageing
artificial neural network [-]
Laburpena
Getting accurate lifetime predictions for a particular cell chemistry remains a challenging process, largely dependent on time and cost-intensive experimental battery testing. This paper proposes a tr ... [+]
Getting accurate lifetime predictions for a particular cell chemistry remains a challenging process, largely dependent on time and cost-intensive experimental battery testing. This paper proposes a transfer learning (TL) method to develop LIB ageing models, which allow for the leveraging of experimental laboratory testing data previously obtained for a different cell technology. The TL method is implemented through Neural Networks models, using LiNiMnCoO2/C laboratory ageing data as a baseline model. The obtained TL model achieves an 1.01% overall error for a broad range of operating conditions, using for retraining only two experimental ageing tests of LiFePO4/C cells. [-]
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