State of charge estimation for lithium-ion batteries based on power model of ohmic resistance and modified multi-innovation unscented Kalman filtering-Reference-Cited by-同舟云学术

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State of charge estimation for lithium-ion batteries based on power model of ohmic resistance and modified multi-innovation unscented Kalman filtering

Published:2024-09 Issue: Volume:98 Page:113099
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Li Zuxin^ORCID,Shen Shengyu^ORCID,Cai Zhiduan^ORCID,Liu Zhitao,Gu Weimin,Dong Wusong

Funder

Zhejiang Province Public Welfare Technology Application Research Project

Publisher

Elsevier BV

Reference49 articles.

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

2. Digital twin and cloud-side-end collaboration for intelligent battery management system;Wang;J. Manuf. Syst.,2022

3. Co-estimation of state of charge and state of health for lithium-ion batteries based on fractional-order model with multi-innovations unscented Kalman filter method;Ma;J. Energy Storage,2022

4. The capacity decay mechanism of the 100 after high-temperature storage;Liu;J. Power Sources,2023

5. Co-estimation of the model parameter and state of charge for retired lithium-ion batteries over a wide temperature range and battery degradation scope;Xiong;Renew. Energy,2023

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