A novel non-experiment-based reconstruction method for the relationship between open-circuit-voltage and state-of-charge/state-of-energy of lithium-ion battery-Reference-Cited by-同舟云学术

A novel non-experiment-based reconstruction method for the relationship between open-circuit-voltage and state-of-charge/state-of-energy of lithium-ion battery

Published:2022-01 Issue: Volume:403 Page:139637
ISSN:0013-4686
Container-title:Electrochimica Acta
language:en
Short-container-title:Electrochimica Acta

Author:

Zhang Shuzhi,Zhang Xiongwen

Publisher

Elsevier BV

Subject

Electrochemistry,General Chemical Engineering

Reference40 articles.

1. Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries;Shrivastava;Renew. Sustain. Energy Rev.,2019

2. State estimation for advanced battery management: key challenges and future trends;Hu;Renew. Sustain. Energy Rev.,2019

3. An improved adaptive unscented Kalman filtering for state of charge online estimation of lithium-ion battery;Zhang;J. Energy Storage,2020

4. An online model-based method for state of energy estimation of lithium-ion batteries using dual filters;Dong;J. Power Sources,2016

5. Advanced battery management strategies for a sustainable energy future: multilayer design concepts and research trends;Dai;Renew. Sustain. Energy Rev.,2021

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