A Hybrid Modeling Framework for Membrane Separation Processes: Application to Lithium-Ion Recovery from Batteries

This study proposed a hybrid modeling framework for membrane separation processes where lithium from batteries is recovered. This is a pertinent problem nowadays as lithium batteries are popularized in hybrid and electric vehicles. The hybrid model is based on an artificial intelligence (AI) structu...

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Bibliographic Details
Published in:Processes 2021-11, Vol.9 (11), p.1939
Main Authors: Regufe, Maria João, Santana, Vinicius V., Ferreira, Alexandre F. P., Ribeiro, Ana M., Loureiro, José M., Nogueira, Idelfonso B. R.
Format: Article
Language:English
Subjects:
Artificial intelligence
Batteries
Case studies
Chemical engineering
Chromatography
Differential equations
Electric vehicles
Lithium
Lithium batteries
Lithium ions
Mass transfer
Membrane separation
Membranes
Modelling
Optimization
Ordinary differential equations
Rechargeable batteries
Separation
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Summary:This study proposed a hybrid modeling framework for membrane separation processes where lithium from batteries is recovered. This is a pertinent problem nowadays as lithium batteries are popularized in hybrid and electric vehicles. The hybrid model is based on an artificial intelligence (AI) structure to model the mass transfer resistance of several experimental separations found in the literature. It is also based on a phenomenological model to represent the transient system regime. An optimization framework was designed to perform the AI model training and simultaneously solve the Ordinary Differential Equation (ODE) system representing the phenomenological model. The results demonstrate that the hybrid model can better represent the experimental validation sets than the phenomenological model alone. This strategy opens doors for further investigations of this system.
ISSN:2227-9717
2227-9717
DOI:10.3390/pr9111939