State of health estimation for lithium-ion batteries based on current interrupt method and genetic algorithm optimized back propagation neural network-Reference-Cited by-同舟云学术

State of health estimation for lithium-ion batteries based on current interrupt method and genetic algorithm optimized back propagation neural network

Published:2024-01 Issue: Volume:591 Page:233842
ISSN:0378-7753
Container-title:Journal of Power Sources
language:en
Short-container-title:Journal of Power Sources

Author:

Sun Jinghua^ORCID,Kainz Josef

Publisher

Elsevier BV

Subject

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

Reference48 articles.

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3. State of health estimation for lithium-ion batteries based on the constant current–constant voltage charging curve;Xiao;Electronics,2020

4. Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: recent advances and perspectives;Xiong;Renew. Sustain. Energy Rev.,2020

5. UV-cured self-healing gel polymer electrolyte toward safer room temperature lithium metal batteries;Siccardi;Electrochim. Acta,2022

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1. Domain generalization-based state-of-health estimation of lithium-ion batteries;Journal of Power Sources;2024-08

2. An improved forgetting factor recursive least square and extended particle filtering algorithm for accurate lithium-ion battery state of energy estimation;Ionics;2024-07-19

3. State of Health Estimation for Lithium-Ion Battery Based on Sample Transfer Learning under Current Pulse Test;Batteries;2024-05-02

4. Energy Balance Control of Multi Group Lithium Ion Batteries Under Internet of Things Technology;IEEE Access;2024