A physics based reduced order aging model for lithium-ion cells with phase change

The electrochemical model has the potential to provide a robust and accurate battery management system, but is not the preferred choice as it involves solving non-linear, coupled partial differential equations. In the present work, a model order reduction of the complete electrochemical model for a...

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Published inJournal of power sources Vol. 270; pp. 281 - 291
Main Authors Gambhire, Priya, Hariharan, Krishnan S., Khandelwal, Ashish, Kolake, Subramanya Mayya, Yeo, Taejung, Doo, Seokgwang
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 15.12.2014
Elsevier
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Summary:The electrochemical model has the potential to provide a robust and accurate battery management system, but is not the preferred choice as it involves solving non-linear, coupled partial differential equations. In the present work, a model order reduction of the complete electrochemical model for a lithium ion cell with phase change electrodes is carried out. The phase change phenomenon is described using a simple, concentration-dependent diffusivity derived from mixture rules. This reduced order model (ROM) is validated with experimental data from literature. The applicability of the model to capture the atypical behavior of the phase change electrode system is demonstrated. Using the cell response from ROM, charge–discharge asymmetry and path dependence in a lithium iron phosphate (LFP) cell are explored in detail. In addition, side reaction kinetics and solid electrolyte interphase formation are included in the ROM framework to enhance its capability to predict cell aging. The model is used to investigate capacity losses occurring in a phase change electrode cell. Insights from these results are used to suggest cell operating guidelines for maximizing utilization. •Reduced order model for cells with phase change electrodes.•Two phase coexistence described using a concentration dependent diffusivity.•Easy implementation of degradation to study the cycle life.•Model captures experimentally observed signatures of phase transition and aging.
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ISSN:0378-7753
1873-2755
DOI:10.1016/j.jpowsour.2014.07.127