State of charge estimation under different temperatures using unscented Kalman filter algorithm based on fractional-order model with multi-innovation-Reference-Cited by-同舟云学术

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State of charge estimation under different temperatures using unscented Kalman filter algorithm based on fractional-order model with multi-innovation

Published:2022-12 Issue: Volume:56 Page:106101
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Xu Yonghong,Zhang Hongguang,Zhang Jian,Yang Fubin,Tong Liang,Yan Dong,Yang Hailong,Wang Yan

Funder

Tianjin University

Natural Science Foundation of Beijing Municipality

State Key Laboratory of Engines

Publisher

Elsevier BV

Subject

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

Reference55 articles.

1. Multi-objective optimization of a novel combined cooling, dehumidification and power system using improved M-PSO algorithm;Chang;Energy,2022

2. Experimental investigation of pneumatic motor for transport application;Xu;Renew. Energy,2021

3. Rational design and engineering of one-dimensional hollow nanostructures for efficient electrochemical energy storage;Fang;Angew. Chem. Int. Ed.,2021

4. Review of electric vehicle energy storage and management system: standards, issues, and challenges;Hasan;J. Energy Storage,2021

5. Towards long lifetime battery: AI-based manufacturing and management;Liu;IEEE/CAA J. Autom. Sin.,2022

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Joint estimation of State of Charge (SOC) and State of Health (SOH) for lithium ion batteries using Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Long Sort Term Memory Network (LSTM) models;International Journal of Electrochemical Science;2024-09

2. State of charge estimation for lithium-ion batteries based on power model of ohmic resistance and modified multi-innovation unscented Kalman filtering;Journal of Energy Storage;2024-09

3. Improved adaptive feedback particle swarm optimization-multi-innovation singular decomposition unscented Kalman filtering for high accurate state of charge estimation of lithium-ion batteries in energy storage systems;Ionics;2024-07-10

4. State-of-charge estimation for supercapacitors based on salp swarm algorithm-optimized high and low degree cubature Kalman filters considering temperature uncertainty;Electrochimica Acta;2024-05

5. A fractional order model of auxiliary power batteries suitable for hydrogen fuel cell hybrid systems heavy-duty trucks;International Journal of Hydrogen Energy;2024-04

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