Battery SOH estimation and RUL prediction framework based on variable forgetting factor online sequential extreme learning machine and particle filter-Reference-Cited by-同舟云学术

Battery SOH estimation and RUL prediction framework based on variable forgetting factor online sequential extreme learning machine and particle filter

Published:2023-08 Issue: Volume:65 Page:107322
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Duan Wenxian,Song Shixin,Xiao Feng,Chen Yuan,Peng Silun,Song Chuanxue

Publisher

Elsevier BV

Subject

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

Reference58 articles.

1. A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: challenges and recommendations;Hannan;Renew. Sustain. Energy Rev.,2017

2. Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries;Shrivastava;Renew. Sustain. Energy Rev.,2019

3. Evaluation and observability analysis of an improved reduced-order electrochemical model for lithium-ion battery;Wu;Electrochim. Acta,2021

4. Online state-of-health estimation of lithium-ion battery based on dynamic parameter identification at multi timescale and support vector regression;Tan;J. Power Sources,2021

5. A new lithium-ion battery SOH estimation method based on an indirect enhanced health indicator and support vector regression in PHMs;Liu;Energies (Basel),2020

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