📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

FIRG025 - State of Health and Lifetime Prediction of Lithium-ion Batteries Using Self-learning Incremental Models (2022)

First Author: Camargos M

Attributed to: The Faraday Institution funded by ISCF

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.36001/phme.2022.v7i1.3323

Publication URI: http://dx.doi.org/10.36001/phme.2022.v7i1.3323

Type: Journal Article/Review

Parent Publication: PHM Society European Conference

Issue: 1