A novel classification method of commercial lithium-ion battery cells based on fast and economic detection of self-discharge rate-Reference-Cited by-同舟云学术

A novel classification method of commercial lithium-ion battery cells based on fast and economic detection of self-discharge rate

Published:2020-12 Issue: Volume:478 Page:229039
ISSN:0378-7753
Container-title:Journal of Power Sources
language:en
Short-container-title:Journal of Power Sources

Author:

Zheng Yuejiu,Wu Hang,Yi Wei,Lai Xin,Dai Haifeng,Han Xuebing,Ouyang Minggao

Funder

National Natural Science Foundation of China

International Science & Technology Cooperation of China

Shanghai Science and Technology Development Fund

Publisher

Elsevier BV

Subject

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

Reference37 articles.

1. A review of current automotive battery technology and future prospects

2. ANFIS (adaptive neuro-fuzzy inference system) based online SOC (State of Charge) correction considering cell divergence for the EV (electric vehicle) traction batteries

3. Online cell SOC estimation of Li-ion battery packs using a dual time-scale Kalman filtering for EV applications

4. A graphical model for evaluating the status of series-connected lithium-ion battery pack

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