Modeling Li-ion Battery Capacity Depletion in a Particle Filtering Framework

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Published Mar 26, 2021
Bhaskar Saha Kai Goebel

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.

How to Cite

Saha, B. ., & Goebel, K. . (2021). Modeling Li-ion Battery Capacity Depletion in a Particle Filtering Framework. Annual Conference of the PHM Society, 1(1). Retrieved from http://www.papers.phmsociety.org/index.php/phmconf/article/view/1614
Abstract 2169 | PDF Downloads 825

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Keywords

accelerated testing, batteries, health algorithms, battery power management, lithium-ion batteries, particle filtering, physics of failure, remaining useful life (RUL), state of charge estimation

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Section
Technical Research Papers

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