A simplified multi-particle model for lithium ion batteries via a predictor-corrector strategy and quasi-linearization

Xiaoyu Li, Guodong Fan, Giorgio Rizzoni, Marcello Canova, Chunbo Zhu and Guo Wei

Energy, 2016, vol. 116, issue P1, 154-169

Abstract: The design of a simplified yet accurate physics-based battery model enables researchers to accelerate the processes of the battery design, aging analysis and remaining useful life prediction. In order to reduce the computational complexity of the Pseudo Two-Dimensional mathematical model without sacrificing the accuracy, this paper proposes a simplified multi-particle model via a predictor-corrector strategy and quasi-linearization. In this model, a predictor-corrector strategy is used for updating two internal states, especially used for solving the electrolyte concentration approximation to reduce the computational complexity and reserve a high accuracy of the approximation. Quasi-linearization is applied to the approximations of the Butler-Volmer kinetics equation and the pore wall flux distribution to predict the non-uniform electrochemical reaction effects without using any nonlinear iterative solver. Simulation and experimental results show that the isothermal model and the model coupled with thermal behavior are greatly improve the computational efficiency with almost no loss of accuracy.

Keywords: Lithium ion battery; Electrochemical multi-particle model; Model simplification; Predictor-corrector strategy; Quasi-linearization (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:116:y:2016:i:p1:p:154-169

DOI: 10.1016/j.energy.2016.09.099

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