Training Gaussian process regression through data augmentation for battery SOC estimation-Reference-Cited by-同舟云学术

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Training Gaussian process regression through data augmentation for battery SOC estimation

Published:2024-09 Issue: Volume:98 Page:113073
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Santoni Francesco^ORCID,De Angelis Alessio,Moschitta Antonio,Carbone Paolo

Publisher

Elsevier BV

Reference23 articles.

1. Machine learning applied to electrified vehicle battery state of charge and state of health estimation: State-of-the-art;Vidal;IEEE Access,2020

2. A comprehensive review of state of charge estimation in lithium-ion batteries used in electric vehicles;Selvaraj;J. Energy Storage,2023

3. Machine learning pipeline for battery state-of-health estimation;Roman;Nat. Mach. Intell.,2021

4. Developing a real-time data-driven battery health diagnosis method, using time and frequency domain condition indicators;Khaleghi;Appl. Energy,2019

5. Performance analysis and SOH (state of health) evaluation of lithium polymer batteries through electrochemical impedance spectroscopy;Galeotti;Energy,2015

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