Lifetime estimation technique for lead-acid batteries

David C.C. Freitas, Marcos B. Ketzer, Marcos R.A. Morais, Antonio M.N. Lima

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations


Battery mathematical models can be employed to predict its behavior under various charging and discharging conditions, and in some applications, they are key elements for the successes of the design. In this paper, it is analyzed a lead-acid battery model for voltage and lifetime estimation. The chosen model synthesis is based on an electrical equivalent circuit, and has the features that allow it to be used in the calculation of the remaining capacity. The lifetime model employs an adaptive update mechanism during the simulation such that the battery performance is reduced depending on the operating conditions. This paper objective is to generalize the analyzed mathematical system to be used in any lead-acid battery. Both the model and the estimation algorithm are evaluated with two batteries with same voltage and nominal capacity. The generalization of equation is made by the addition of three new parameters to minimize an objective function based on the least squares error. The study is based on a specific scenario that makes the battery reached the end of its lifetime. With the addition of new parameters, the RMS error between real capacity and calculated capacity are evaluated.

Original languageEnglish
Title of host publicationProceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society
PublisherIEEE Computer Society
Number of pages6
ISBN (Electronic)9781509034741
StatePublished - 21 Dec 2016
Externally publishedYes
Event42nd Conference of the Industrial Electronics Society, IECON 2016 - Florence, Italy
Duration: 24 Oct 201627 Oct 2016

Publication series

NameIECON Proceedings (Industrial Electronics Conference)


Conference42nd Conference of the Industrial Electronics Society, IECON 2016


Dive into the research topics of 'Lifetime estimation technique for lead-acid batteries'. Together they form a unique fingerprint.

Cite this