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

C. W. Lee, Y. Hong, M. Hayrapetyan, X. G. Yang, Z. Xi

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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.].

Original languageEnglish (US)
Pages (from-to)365-377
Number of pages13
JournalJournal of Applied Electrochemistry
Volume48
Issue number3
DOIs
StatePublished - Mar 1 2018

Fingerprint

Tuning
ROM
Computational efficiency
Linear equations
Hysteresis
Genetic algorithms

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Electrochemistry
  • Materials Chemistry

Keywords

  • Genetic algorithm
  • Li–ion battery
  • Reduced-order model
  • Solvability

Cite this

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title = "Derivation and tuning of a solvable and compact differential–algebraic equations model for LiFePO4–graphite Li–ion batteries",
abstract = "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.].",
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Derivation and tuning of a solvable and compact differential–algebraic equations model for LiFePO4–graphite Li–ion batteries. / Lee, C. W.; Hong, Y.; Hayrapetyan, M.; Yang, X. G.; Xi, Z.

In: Journal of Applied Electrochemistry, Vol. 48, No. 3, 01.03.2018, p. 365-377.

Research output: Contribution to journalArticle

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.

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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.].

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