A deep belief network approach to remaining capacity estimation for lithium-ion batteries based on charging process features

2022 ◽  
Vol 48 ◽  
pp. 103825
Author(s):  
Mengda Cao ◽  
Tao Zhang ◽  
Jia Wang ◽  
Yajie Liu
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Deep Belief Network ◽  
Network Approach ◽  
Capacity Estimation ◽  
Belief Network ◽  
Remaining Capacity

Screening of retired lithium-ion batteries using incremental capacity charging curve based residual capacity estimation method for facilitating sustainable circular lithium-ion battery system

2021 ◽  
pp. 1-16
Author(s):  
Honglei Li ◽  
Liang Cong ◽  
Huazheng Ma ◽  
Weiwei Liu ◽  
Yelin Deng ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Estimation Method ◽  
Lithium Ion ◽  
Capacity Fade ◽  
Characteristic Parameters ◽  
Capacity Estimation ◽  
Capacity Curve ◽  
Residual Capacity ◽  
Remaining Capacity ◽  
Incremental Capacity

Abstract The rapidly growing deployment of lithium-ion batteries in electric vehicles is associated with a great waste of natural resource and environmental pollution caused by manufacturing and disposal. Repurposing the retired lithium-ion batteries can extend their useful life, creating environmental and economic benefits. However, the residual capacity of retired lithium-ion batteries is unknown and can be drastically different owing to various working history and calendar life. The main objective of this paper is to develop a fast and accurate capacity estimation method to classify the retired batteries by the remaining capacity. The hybrid technique of adaptive genetic algorithm and back propagation neural network is developed to estimate battery remaining capacity using the training set comprised of the selected characteristic parameters of incremental capacity curve of battery charging. Also, the paper investigated the correlation between characteristic parameters with capacity fade. The results show that capacity estimation errors of the proposed neural network are within 3%. Peak intensity of the incremental capacity curve has strong correlation with capacity fade. The findings also show that the translation of peak of the incremental capacity curve is strongly related with internal resistance.

scholarly journals Remaining capacity estimation of lithium-ion batteries based on the constant voltage charging profile

PLoS ONE ◽  
2018 ◽  
Vol 13 (7) ◽  
pp. e0200169 ◽  
Author(s):  
Zengkai Wang ◽  
Shengkui Zeng ◽  
Jianbin Guo ◽  
Taichun Qin
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Constant Voltage ◽  
Capacity Estimation ◽  
Remaining Capacity

scholarly journals Online capacity estimation of lithium-ion batteries with deep long short-term memory networks

2021 ◽  
Vol 482 ◽  
pp. 228863
Author(s):  
Weihan Li ◽  
Neil Sengupta ◽  
Philipp Dechent ◽  
David Howey ◽  
Anuradha Annaswamy ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Short Term Memory ◽  
Lithium Ion ◽  
Capacity Estimation ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory

A sequential capacity estimation for the lithium-ion batteries combining incremental capacity curve and discrete Arrhenius fading model

2021 ◽  
Vol 484 ◽  
pp. 229248
Author(s):  
Tao Sun ◽  
Bowen Xu ◽  
Yifan Cui ◽  
Xuning Feng ◽  
Xuebing Han ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Capacity Estimation ◽  
Capacity Curve ◽  
Incremental Capacity

Incremental capacity analysis and differential voltage analysis based state of charge and capacity estimation for lithium-ion batteries

Energy ◽  
2018 ◽  
Vol 150 ◽  
pp. 759-769 ◽  
Author(s):  
Linfeng Zheng ◽  
Jianguo Zhu ◽  
Dylan Dah-Chuan Lu ◽  
Guoxiu Wang ◽  
Tingting He
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
State Of Charge ◽  
Capacity Analysis ◽  
Capacity Estimation ◽  
Differential Voltage ◽  
Incremental Capacity

Composite Deep Belief Network approach for enhanced Antepartum foetal electrocardiogram signal

2020 ◽  
Vol 59 ◽  
pp. 198-203
Author(s):  
D.J. Jagannath ◽  
D. Raveena Judie Dolly ◽  
J. Dinesh Peter
Keyword(s):  
Deep Belief Network ◽  
Network Approach ◽  
Belief Network ◽  
Electrocardiogram Signal
Sign in / Sign up

Export Citation Format

Share Document