Performance of Adaptive Neuro-Fuzzy Inference System State-of-Charge Estimation of Lithium-Ion Batteries for Electric Ship-Reference-Cited by-同舟云学术

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Performance of Adaptive Neuro-Fuzzy Inference System State-of-Charge Estimation of Lithium-Ion Batteries for Electric Ship

Published:2023-06-23 Issue: Volume: Page:205-209
ISSN:
Container-title:2023 8th International Conference on Computational Intelligence and Applications (ICCIA)
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Author:

Marisno Denny¹,Chin Cheng Siong¹,Shan Chunlai²,See Simon³

Affiliation:

1. Newcastle University in Singapore,Faculty of Science, Agriculture, and Engineering,Singapore

2. Northwest Institute of Mechanical and Electrical Engineering,Simulation & Test Technology Department,Xianyang,China

3. Shanghai Jiao Tong University 800 Dongchuan RD. Minhang District,Department of Computer Science and Engineering,Shanghai,China,200240

Funder

Newcastle University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10387742/10387799/10387800.pdf?arnumber=10387800

Reference13 articles.

1. Hardware-in-the-loop Implementation of ANFIS based Adaptive SoC Estimation of Lithium-ion Battery for Hybrid Vehicle Applications

2. A Comprehensive Review of Available Battery Datasets, RUL Prediction Approaches, and Advanced Battery Management

3. SoC Estimation of Lithium Ion Battery Using Combined Coulomb Counting and Fuzzy Logic Method

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

5. A State-of-Health Estimation Method of Lithium-ion Batteries using ICA and SVM

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