State of health prediction for lithium‐ion batteries with a novel online sequential extreme learning machine method-Reference-Cited by-同舟云学术

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State of health prediction for lithium‐ion batteries with a novel online sequential extreme learning machine method

Published:2020-09-14 Issue:2 Volume:45 Page:2383-2397
ISSN:0363-907X
Container-title:International Journal of Energy Research
language:en
Short-container-title:Int J Energy Res

Author:

Tian Huixin¹²,Qin Pengliang¹²^ORCID

Affiliation:

1. School of Electrical Engineering & Automation Tiangong University Tianjin China

2. Key Laboratory of Advanced Electrical Engineering and Energy Technology Tiangong University Tianjin China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.5934

Reference35 articles.

1. Uneven temperature and voltage distributions due to rapid discharge rates and different boundary conditions for series-connected LiFePO 4 batteries

2. A study of external surface pressure effects on the properties for lithium‐ion pouch cells

3. A review on lithium-ion battery ageing mechanisms and estimations for automotive applications

4. A review of the state of health for lithium-ion batteries: Research status and suggestions

5. Remaining useful life prediction of lithium-ion battery based on improved cuckoo search particle filter and a novel state of charge estimation method

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1. Enhancing data-driven-based state of health estimation for diverse battery applications through effective feature construction;Energy;2024-11

2. Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions;Journal of Energy Storage;2024-09

3. A new online SOC estimation method using broad learning system and adaptive unscented Kalman filtering algorithm;Energy;2024-08

4. Analysis of State-of-Health Estimation Approaches and Constraints for Lithium-Ion Batteries in Electric Vehicles;International Journal of Energy Research;2024-05-03

5. A review of machine learning state-of-charge and state-of-health estimation algorithms for lithium-ion batteries;Energy Reports;2023-12

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