State of charge estimation of lithium-ion batteries using a grey extended Kalman filter and a novel open-circuit voltage model-Reference-Cited by-同舟云学术

State of charge estimation of lithium-ion batteries using a grey extended Kalman filter and a novel open-circuit voltage model

Published:2017-11 Issue: Volume:138 Page:764-775
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Pan Haihong,Lü Zhiqiang,Lin Weilong,Li Junzi,Chen Lin^ORCID

Funder

National Natural Science Foundation of China

Guangxi Key Laboratory of Manufacturing System & Advanced Manufacturing Technology

Innovation Project of Guangxi Graduate Education

Guangxi Natural Science Foundation

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. Modeling and state-of-charge prediction of lithium-ion battery and ultracapacitor hybrids with a co-estimator;Wang;Energy,2017

2. A method for SOC estimation based on simplified mechanistic model for LiFePO4 battery;Li;Energy,2016

3. An on-line estimation of battery pack parameters and state-of-charge using dual filters based on pack model;Zhang;Energy,2016

4. A combination Kalman filter approach for State of Charge estimation of lithium-ion battery considering model uncertainty;Li;Energy,2016

5. Analysis of thermal aging paths for large-format LiFePO4/graphite battery;Shi;Electrochim Acta,2016

Cited by 96 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. Holistic Testing and Characterization of Commercial 18650 Lithium-Ion Cells;Batteries;2024-07-11

2. A novel suppressing Kalman filter divergence method for the state of charge estimation of lithium-ion batteries under complex conditions;Journal of Energy Storage;2024-06

3. Estimation of SOC in Lithium-Iron-Phosphate Batteries Using an Adaptive Sliding Mode Observer with Simplified Hysteresis Model during Electric Vehicle Duty Cycles;Batteries;2024-04-30

4. Examining the influence of sampling frequency on state-of-charge estimation accuracy using long short-term memory models;Electrical Engineering;2024-04-16

5. A strong robust state-of-charge estimation method based on the gas-liquid dynamics model;Green Energy and Intelligent Transportation;2024-03