Multivariable Fractional Polynomials for lithium-ion batteries degradation models under dynamic conditions-Reference-Cited by-同舟云学术

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Multivariable Fractional Polynomials for lithium-ion batteries degradation models under dynamic conditions

Published:2022-08 Issue: Volume:52 Page:104903
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Bertinelli Salucci Clara,Bakdi Azzeddine,Glad Ingrid Kristine,Vanem Erik,De Bin Riccardo

Funder

Norges Forskningsråd

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Reference66 articles.

1. Greenhouse gas emissions associated with road transport projects: current status, benchmarking, and assessment tools;Albuquerque;Transp. Res. Procedia,2020

2. Modeling li-ion battery capacity depletion in a particle filtering framework;Saha,2009

3. Adaptive prognosis of Lithium-ion batteries based on the combination of particle filters and radial basis function neural networks;Sbarufatti;J. Power Sources,2017

4. Critical review of state of health estimation methods of Li-ion batteries for real applications;Berecibar;Renew. Sustain. Energy Rev.,2016

5. A review of battery state of health estimation methods: hybrid electric vehicle challenges;Noura;World Electr. Veh. J.,2020

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3. Experimental Validation of Electrothermal and Aging Parameter Identification for Lithium-Ion Batteries;Energies;2024-05-08

4. Similarity based remaining useful life prediction based on Gaussian Process with active learning;Reliability Engineering & System Safety;2023-10

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