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Computational Modeling and Design of Lithium Ion Batteries

"Lithium-ion batteries (LIBs) are among the most promising solutions for energy storage. Compared with other resources such as bio-fuel, solar cells, fuel cells or lead acid batteries, rechargeable batteries are more portable and... ver más

31/05/2019

BAUHAUS-UNIVERSITA...

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

BAUHAUSUNIVERSITAET WEIMAR No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2019-05-31 No tenemos la información de la convocatoria

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1 Participantes

BAUHAUS-UNIVERSITAET WEIMAR

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Líder del proyecto

BAUHAUSUNIVERSITAET WEIMAR No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 2M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto "Lithium-ion batteries (LIBs) are among the most promising solutions for energy storage. Compared with other resources such as bio-fuel, solar cells, fuel cells or lead acid batteries, rechargeable batteries are more portable and allow for quick energy storage and release. The higher power and energy density make batteries suitable as the energy resource for most portable elect. devices including future vehicles. Among the rechargeable batteries, LIBs have the most potential because of their quick charging rate and high power and energy density. However, ageing of LIBs and the related capacity and power fade is a major concern. For the improvement and future development of batteries, computational modeling and design is an important complementary part to experimental testing which is expensive, time-consuming and sometimes unfeasible. In this project, the PI proposes to develop, implement, verify and validate a computational multifield and multiscale framework to support the design and optimization of new batteries. The computational framework will support the design and optimization of new anode, separator and cathode materials as well as their structure inside the battery. The measurable outcome of this research will be an open-source software package that can be used to support the design and optimization of LIBs. Within the computational framework, different (mechanical-thermal-electro-chemical) fields will be linked over multiple scales: from fundamental physics to the design of new battery materials. We will quantify uncertainties in order to provide upper and lower bounds of our predictions and use graph-theory, error-estimation and adaptivity to choose the appropriate model and discretization. The computational framework will be verified and validated by comparison to experiments. Finally, multi-objective optimization over multiple scales will provide a new battery prototype that will be manufactured, tested and compared to the computational predictions."

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