Li-Ion Batteries Parameter Estimation With Tiny Neural Networks Embedded on Intelligent IoT Microcontrollers

IEEE Access ◽

10.1109/access.2020.3007046 ◽

2020 ◽

Vol 8 ◽

pp. 122135-122146

Author(s):

Giulia Crocioni ◽

Danilo Pau ◽

Jean-Michel Delorme ◽

Giambattista Gruosso

Keyword(s):

Neural Networks ◽

Parameter Estimation ◽

Li Ion Batteries ◽

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Estimation of thermal effect of different busbars materials on prismatic Li-ion batteries based on artificial neural networks

Journal of Energy Storage ◽

10.1016/j.est.2021.102543 ◽

2021 ◽

Vol 38 ◽

pp. 102543

Author(s):

Ozge Yetik ◽

Tahir Hikmet Karakoc

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Thermal Effect ◽

Li Ion Batteries ◽

Li Ion ◽

Artificial Neural

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Robust state-of-charge estimation of Li-ion batteries based on multichannel convolutional and bidirectional recurrent neural networks

Applied Soft Computing ◽

10.1016/j.asoc.2021.108401 ◽

2022 ◽

pp. 108401

Author(s):

Chong Bian ◽

Shunkun Yang ◽

Jie Liu ◽

Enrico Zio

Keyword(s):

Neural Networks ◽

Recurrent Neural Networks ◽

State Of Charge ◽

Li Ion Batteries ◽

Li Ion ◽

State Of Charge Estimation

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Real-Time Prediction of Anode Potential in Li-Ion Batteries Using Long Short-Term Neural Networks for Lithium Plating Prevention

Journal of The Electrochemical Society ◽

10.1149/2.0621910jes ◽

2019 ◽

Vol 166 (10) ◽

pp. A1893-A1904 ◽

Author(s):

Xianke Lin

Keyword(s):

Neural Networks ◽

Real Time ◽

Anode Potential ◽

Li Ion Batteries ◽

Time Prediction ◽

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A coupled design optimization methodology for Li-ion batteries in electric vehicle applications based on FEM and neural networks

2014 International Symposium on Power Electronics, Electrical Drives, Automation and Motion ◽

10.1109/speedam.2014.6872017 ◽

2014 ◽

Author(s):

F. Bonanno ◽

G. Capizzi ◽

S. Coco ◽

A. Laudani ◽

G. Lo Sciuto

Keyword(s):

Neural Networks ◽

Design Optimization ◽

Electric Vehicle ◽

Li Ion Batteries ◽

Li Ion ◽

Optimization Methodology

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Behavior and state-of-health monitoring of Li-ion batteries using impedance spectroscopy and recurrent neural networks

International Journal of Electrical Power & Energy Systems ◽

10.1016/j.ijepes.2012.04.050 ◽

2012 ◽

Vol 42 (1) ◽

pp. 487-494 ◽

Author(s):

Akram Eddahech ◽

Olivier Briat ◽

Nicolas Bertrand ◽

Jean-Yves Delétage ◽

Jean-Michel Vinassa

Keyword(s):

Neural Networks ◽

Impedance Spectroscopy ◽

Health Monitoring ◽

Recurrent Neural Networks ◽

State Of Health ◽

Li Ion Batteries ◽

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Neural Networks for State-of-Charge Estimation of Li-ion Batteries

2021 18th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) ◽

10.1109/ecti-con51831.2021.9454856 ◽

2021 ◽

Author(s):

Shixi Hou ◽

Yuzhuang Qian ◽

Zhouhe Zhang ◽

Jienan Han

Keyword(s):

Neural Networks ◽

State Of Charge ◽

Li Ion Batteries ◽

Li Ion ◽

State Of Charge Estimation

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A parameter estimation method for a simplified electrochemical model for Li-ion batteries

Electrochimica Acta ◽

10.1016/j.electacta.2018.04.098 ◽

2018 ◽

Vol 275 ◽

pp. 50-58 ◽

Author(s):

Junfu Li ◽

Lixin Wang ◽

Chao Lyu ◽

Enhui Liu ◽

Yinjiao Xing ◽

...

Keyword(s):

Parameter Estimation ◽

Estimation Method ◽

Li Ion Batteries ◽

Parameter Estimation Method ◽

Li Ion ◽

Electrochemical Model

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Li-ion Batteries Parameter Estimation Using Converter Excitation and Fusion Methods

2019 IEEE Energy Conversion Congress and Exposition (ECCE) ◽

10.1109/ecce.2019.8912968 ◽

2019 ◽

Author(s):

Irene Pelaez ◽

Pablo Garcia ◽

Geber Villa ◽

Sara Saheed

Keyword(s):

Parameter Estimation ◽

Li Ion Batteries ◽

Fusion Methods ◽

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Li-Ion Batteries Releasable Capacity Estimation with Neural Networks on Intelligent IoT Microcontrollers

2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON) ◽

10.1109/melecon48756.2020.9140634 ◽

2020 ◽

Author(s):

Giulia Crocioni ◽

Danilo Pau ◽

Giambattista Gruosso

Keyword(s):

Neural Networks ◽

Li Ion Batteries ◽

Capacity Estimation ◽

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State-of-Charge Estimation of Li-ion Batteries Based on A Hybrid Model Using Nonlinear Autoregressive Exogenous Neural Networks

2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) ◽

10.1109/appeec.2018.8566627 ◽

2018 ◽

Author(s):

Yuxiang Zhang ◽

Chunyu Zhao ◽

Senlin Zhu

Keyword(s):

Neural Networks ◽

Hybrid Model ◽

State Of Charge ◽

Li Ion Batteries ◽

Li Ion ◽

Nonlinear Autoregressive ◽

State Of Charge Estimation

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