Self-Adaptive Neural Network-Based Fractional-Order Nonlinear Observer Design for State of Charge Estimation of Lithium-Ion Batteries
Author:
Affiliation:
1. School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, Victoria, Australia
2. School of Electrical Engineering and Automation, Anhui University, Hefei, Anhui, China
Funder
Australian government
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/3516/4785241/10285124.pdf?arnumber=10285124
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
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3. Lithium-ion battery parameter estimation based on variational and logistic map cuckoo search algorithm;Electrical Engineering;2024-07-13
4. State-of-charge estimator design and experimental verification for a lithium-titanate battery cell;Clean Technologies and Environmental Policy;2024-05-17
5. Managing the surge: A comprehensive review of the entire disposal framework for retired lithium-ion batteries from electric vehicles;Journal of Energy Chemistry;2024-05
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