Annual Conference of the Prognostics and Health Management Society, 2009

Modeling Li-ion battery capacity depletion in a particle filtering framework

Bhaskar Saha1 , Kai Goebel1
1Mission Critical Technologies, Inc. (NASA ARC), 2041 Rosecrans Avenue, Suite 220, El Segundo, CA 90245
2NASA Ames Research Center, Moffett Field, CA 95134, USA


This paper presents an empirical model to describe battery behavior during individual discharge cycles as well as over its cycle life. The basis for the form of the model has been linked to the internal processes of the battery and validated using experimental data. Subsequently, the model has been used in a Particle Filtering framework to make predictions of remaining useful life for individual discharge cycles as well as for cycle life. The prediction performance was found to be satisfactory as measured by performance metrics customized for prognostics. The work presented here provides initial steps towards a comprehensive health management solution for energy storage devices

This article is available online here and to CALCE Consortium Members for personal review.

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