Particle-Filtering-Based State-of-Health Estimation and End-of-Life Prognosis for Lithium-Ion Batteries at Operation Temperature

We present the implementation of a particle-filtering-based framework that estimates the State-of-Health (SOH) and predicts the End-of-Life (EOL) of Lithium-Ion batteries, efficiently incorporating variations of ambient temperature in the analysis. The proposed approach uses an empirical state-space...

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Bibliographic Details

Main Author:	Pola, Daniel (author)
Other Authors:	Guajardo, Felipe (author), Jofré, Esteban (author), L. Quintero, Vanessa (author), Perez, Aramis (author), Acuña, David (author), Orchard, Marcos (author)
Format:	article
Language:	English
Published:	2016
Subjects:	State of Health Estimation Battery Remaining Useful Life temperature Lithium-ion battery particle filtering
Online Access:	http://ridda2.utp.ac.pa/handle/123456789/6155
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