A computationally efficient implementation of a full and reduced-order electrochemistry-based model for Li-Ion batteries

L. Xia, E. Najafi, Z. Li, H.J. Bergveld, M.C.F. Donkers

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)
175 Downloads (Pure)

Abstract

Lithium-ion batteries are commonly employed in various applications owing to high energy density and long service life. Lithium-ion battery models are used for analysing batteries and enabling power control in applications. The Doyle-Fuller-Newman (DFN) model is a popular electrochemistry-based lithium-ion battery model which represents solid-state and electrolyte diffusion dynamics and accurately predicts the current/voltage response using a set of nonlinear partial differential equations. However, implementation of the full DFN model requires significant computation time. This paper proposes a computationally efficient implementation of the full DFN battery model, which is convenient for real-time applications. The proposed implementation is based on applying model order reduction to a spatial and temporal discretisation of the governing model equations. For model order reduction, we apply proper orthogonal decomposition and discrete empirical interpolation method, which leads to a set of reduced order nonlinear algebraic equations. These equations are solved using a particular numerical scheme, based on a damped Newton’s method. In a simulation study, the computational efficiency of the proposed implementation is shown and the resulting accuracy is presented.
Original languageEnglish
Pages (from-to)1285-1296
Number of pages12
JournalApplied Energy
Volume208
DOIs
Publication statusPublished - 15 Dec 2017

Keywords

  • Electrochemistry-based model
  • Lithium-ion batteries
  • Model order reduction
  • Partial differential equations
  • Proper orthogonal decomposition

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