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
Abstract:
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