Ageing estimation of lithium ion (Li-Ion) batteries is a key point for their massive application in the market. In this work, different Machine Learning (ML) techniques were applied and compared to evaluate the State of Health (SoH) of a cobalt based Li-Ion battery, cycled under a stationary application profile. Experimental results show that ML can be profitably used for SoH estimation.

A machine learning approach for evaluation of battery state of health

Campobello G.;Segreto A.;Donato N.
2020-01-01

Abstract

Ageing estimation of lithium ion (Li-Ion) batteries is a key point for their massive application in the market. In this work, different Machine Learning (ML) techniques were applied and compared to evaluate the State of Health (SoH) of a cobalt based Li-Ion battery, cycled under a stationary application profile. Experimental results show that ML can be profitably used for SoH estimation.
2020
978-92-990084-7-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3182006
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