Derivation and tuning of a solvable and compact differential–algebraic equations model for LiFePO₄–graphite Li–ion batteries

TY - JOUR

T1 - Derivation and tuning of a solvable and compact differential–algebraic equations model for LiFePO4–graphite Li–ion batteries

AU - Lee, C. W.

AU - Hong, Y.

AU - Hayrapetyan, M.

AU - Yang, X. G.

AU - Xi, Z.

N1 - Funding Information: Fig. 10 Progression of the profile of Li–ion concentration in electrolyte over the cell thickness during 0.5 C discharge. (Color figure online) Fig. 11 Progression of the profile of bulk Li–ion concentration in solid-phase over the cell thickness during 0.5 C discharge. (Color figure online) Acknowledgements The authors gratefully acknowledge the funding for this research from Ford Motor Company. Publisher Copyright: © 2018, Springer Science+Business Media B.V., part of Springer Nature.

PY - 2018/3/1

Y1 - 2018/3/1

N2 - Abstract: This paper presents a procedure for deriving and tuning a solvable and compact differential–algebraic equation (DAE) model for the LiFePO4–graphite lithium–ion battery cell. A reduced order model can drastically decrease the simulation time with a minimal loss of the prediction accuracy for the lithium–ion battery. This paper proposes a method based on a linear DAE theory for choosing a Galerkin formulation that will produce a solvable ROM from the original higher-order model of the lithium–ion battery cell. Moreover, a systematic tuning of the model parameters using the sensitivity study and the genetic algorithm is demonstrated by exploiting the computational efficiency of the simplified model. When coupled with the model for describing the hysteresis of the battery cell, the tuned model, consisting of 26 DAEs, shows a good agreement with the experimental data from a LiFePO4–graphite battery cell at rates up to 4 C. Graphical Abstract: [Figure not available: see fulltext.].

AB - Abstract: This paper presents a procedure for deriving and tuning a solvable and compact differential–algebraic equation (DAE) model for the LiFePO4–graphite lithium–ion battery cell. A reduced order model can drastically decrease the simulation time with a minimal loss of the prediction accuracy for the lithium–ion battery. This paper proposes a method based on a linear DAE theory for choosing a Galerkin formulation that will produce a solvable ROM from the original higher-order model of the lithium–ion battery cell. Moreover, a systematic tuning of the model parameters using the sensitivity study and the genetic algorithm is demonstrated by exploiting the computational efficiency of the simplified model. When coupled with the model for describing the hysteresis of the battery cell, the tuned model, consisting of 26 DAEs, shows a good agreement with the experimental data from a LiFePO4–graphite battery cell at rates up to 4 C. Graphical Abstract: [Figure not available: see fulltext.].

KW - Genetic algorithm

KW - Li–ion battery

KW - Reduced-order model

KW - Solvability

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U2 - https://doi.org/10.1007/s10800-018-1164-8

DO - https://doi.org/10.1007/s10800-018-1164-8

M3 - Article

SN - 0021-891X

VL - 48

SP - 365

EP - 377

JO - Journal of Applied Electrochemistry

JF - Journal of Applied Electrochemistry

IS - 3

ER -