A novel aging modeling approach for second-life lithium-ion batteries
The electric mobility industry is booming. In order to reduce the environmental impact of this boom, there is the potential to reuse the batteries from electric vehicles. However, the technical and economic feasibility of the second-life of lithium-ion batteries remains in question. This is due to t...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad Pública de Navarra |
| Repositorio: | Academica-e. Repositorio Institucional de la Universidad Pública de Navarra |
| OAI Identifier: | oai:academica-e.unavarra.es:2454/54236 |
| Acceso en línea: | https://hdl.handle.net/2454/54236 |
| Access Level: | acceso abierto |
| Palabra clave: | Aging model Battery degradation Energy storage Lithium-ion battery Second-life battery |
| Sumario: | The electric mobility industry is booming. In order to reduce the environmental impact of this boom, there is the potential to reuse the batteries from electric vehicles. However, the technical and economic feasibility of the second-life of lithium-ion batteries remains in question. This is due to the intricate non-linear mechanisms that occur during battery degradation, leading to capacity and power loss. Ongoing research aims to create models that can predict the state of battery degradation. However, most studies have focused on the battery's first life, operating within a limited state of health range and requiring constant monitoring of the battery's exposure conditions. While these models provide satisfactory results for the battery's performance in vehicles, they cannot be directly applied to second-life scenarios. In response to this issue, this article proposes a degradation modeling method for second-life batteries based on identifying and linearizing different degradation trends within the battery. This approach allows the application of the model without prior knowledge of the battery's history. It has been validated for a state of health range of 95% to 20%, through both conventional charge-discharge tests and a real-world scenario involving a smart charging station for urban buses. The results obtained with the developed model are overall satisfactory, achieving a MAPE below 3% for capacity and 1.4% for internal resistance in the real-world scenario. |
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