State of charge estimation for a parallel battery pack jointly by fuzzy-PI model regulator and adaptive unscented Kalman filter-Reference-Cited by-同舟云学术

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State of charge estimation for a parallel battery pack jointly by fuzzy-PI model regulator and adaptive unscented Kalman filter

Published:2024-04 Issue: Volume:360 Page:122807
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Peng Simin,Miao Yifan,Xiong Rui,Bai Jiawei,Cheng Mengzeng,Pecht Michael

Funder

Natural Science Foundation of Beijing Municipality

National Key Research and Development Program of China

Qinglan Project of Jiangsu Province of China

Yancheng Institute of Technology

Publisher

Elsevier BV

Reference46 articles.

1. Online health prognosis for lithium-ion batteries under dynamic discharge conditions over wide temperature range;Liu;eTransportation,2023

2. Method of site selection and capacity setting for battery energy storage system in distribution networks with renewable energy sources;Peng;Energies,2023

3. Overview of state of power prediction methods for lithium-ion batteries;Peng;Chin J Mech Eng,2022

4. Estimation of state-of-charge and state-of-power capability of lithium-ion battery considering varying health conditions;Sun;J Power Sources,2014

5. State of charge estimation of lithium-ion batteries based on double-coefficient tracking improved square-root unscented Kalman filter;Peng;Batteries,2023

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