Computational efficiency of solving the DFN battery model using descriptor form with Legendre polynomials and Galerkin projections

Michelle A. Kehs, Michael D. Beeney, Hosam K. Fathy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations


This paper evaluates the collective impact of three computational strategies from the literature applied to the Doyle-Fuller-Newman (DFN) lithium-ion battery model, a physics-based model valid for high current rates. The first strategy used is efficient model reformulation, where spatial basis functions are used to represent the distribution of lithium ions and potentials within the battery. The second strategy is quasi-linearization, which is used to lessen the computational burden associated with the nonlinearities of the Butler-Volmer equation. Finally, the combination of the first two strategies furnishes a descriptor-form DAE model of the battery at every integration time step. This paper evaluates the accuracy of these combined methods by evaluating the number of basis functions needed for accurate representation and by evaluating the consistency of the constraint equations when the full model is assembled. The combined methods lead to low computation time with accurate simulations 3-4 times faster than real time on a laptop computer.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Print)9781479932726
StatePublished - Jan 1 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2014 American Control Conference, ACC 2014
Country/TerritoryUnited States
CityPortland, OR

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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