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Computational modeling of Li-ion batteries

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Abstract

This review focuses on energy storage materials modeling, with particular emphasis on Li-ion batteries. Theoretical and computational analyses not only provide a better understanding of the intimate behavior of actual batteries under operational and extreme conditions, but they may tailor new materials and shape new architectures in a complementary way to experimental approaches. Modeling can therefore play a very valuable role in the design and lifetime prediction of energy storage materials and devices. Batteries are inherently multi-scale, in space and time. The macro-structural characteristic lengths (the thickness of a single cell, for instance) are order of magnitudes larger than the particles that form the microstructure of the porous electrodes, which in turn are scale-separated from interface layers at which atomistic intercalations occur. Multi-physics modeling concepts, methodologies, and simulations at different scales, as well as scale transition strategies proposed in the recent literature are here revised. Finally, computational challenges toward the next generation of Li-ion batteries are discussed.

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Acknowledgments

We express our deep gratitude to Prof. B. Scrosati, who inspired us and proposed to write this review. He also revised part of the manuscript. FIB–SEM analyses in Fig. 4 were made in cooperation with J. Pauls, A. Mukasyan, J. Schaefer, and K. Matouš at the University of Notre Dame, USA.

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Authors and Affiliations

  1. Dipartimento di Ingegneria Civile, Architettura, Territorio, Ambiente e di Matematica (DICATAM), Università di Brescia, via Branze 43, 25123, Brescia, Italy

    D. Grazioli, M. Magri & A. Salvadori

  2. Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA, Delft, The Netherlands

    D. Grazioli

  3. Department of Aerospace & Mechanical Engineering, University of Notre Dame, Cushing Hall of Engineering, Notre Dame, IN, 46556, USA

    A. Salvadori

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  1. D. Grazioli
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  2. M. Magri
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  3. A. Salvadori
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Correspondence to A. Salvadori.

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Grazioli, D., Magri, M. & Salvadori, A. Computational modeling of Li-ion batteries. Comput Mech 58, 889–909 (2016). https://doi.org/10.1007/s00466-016-1325-8

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