Fisher identifiability analysis for a periodically-excited equivalent-circuit lithium-ion battery model

Aabhas Sharma, Hosam K. Fathy

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

39 Scopus citations


This paper uses Fisher information to quantify the identifiability of internal resistance and charge capacity for a first-order nonlinear equivalent-circuit model of a lithium-ion battery undergoing periodic cycling. The paper derives analytic Cramér-Rao bounds on the variances with which a maximum-likelihood estimator can determine these parameters in the presence of white and Gaussian voltage measurement noise. This mathematical analysis shows that the challenge of battery parameter identifiability, already recognized in the literature for higher-order electrochemical battery models, is fundamentally present even for much simpler equivalent circuit models. The analysis also quantifies the degree to which the sensitivity of battery open-circuit voltage with respect to state of charge affects parameter identifiability. The paper serves as a first-cut analysis of the accuracy with which one can determine two battery state-of-health metrics - namely, power and capacity fade - from periodic cycling tests.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
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


Dive into the research topics of 'Fisher identifiability analysis for a periodically-excited equivalent-circuit lithium-ion battery model'. Together they form a unique fingerprint.

Cite this