A machine learning approach for evaluation of battery state of health

Davide Aloisio, Giuseppe Campobello, Salvatore Gianluca Leonardi, Francesco Sergi, Giovanni Brunaccini, Marco Ferraro, Vincenzo Antonucci, Antonino Segreto, Nicola Donato

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.

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IMEKO-TC4-2020-25.pdf

DOI

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IMEKO TC

TC4 - Measurement of Electrical Quantities

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