A method for state-of-charge estimation of lithium-ion batteries based on PSO-LSTM-Reference-Cited by-同舟云学术

A method for state-of-charge estimation of lithium-ion batteries based on PSO-LSTM

Published:2021-11 Issue: Volume:234 Page:121236
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Ren Xiaoqing,Liu Shulin^ORCID,Yu Xiaodong,Dong Xia

Funder

Natural Science Foundation of Shandong Province

Publisher

Elsevier BV

Subject

General Energy,Pollution,Mechanical Engineering,Building and Construction,Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Civil and Structural Engineering

Reference26 articles.

1. State of charge estimation for lithium-ion battery based on an Intelligent Adaptive Extended Kalman Filter with improved noise estimator;Sun;Energy,2020

2. Innovative lumped-battery model for state of charge estimation of lithium-ion batteries under various ambient temperatures;Seo;Energy,2021

3. A state-of-charge estimation method of the power lithium-ion battery in complex conditions based on adaptive square root extended Kalman filter;Jiang;Energy,2021

4. A new state of charge estimation method for lithium-ion battery based on the fractional order model;Liu;IEEE Access,2019

5. An adaptive square root unscented kalman filter approach for state of charge estimation of lithium-ion batteries;Liu;Energies,2017

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