Co-estimation of lithium-ion battery state of charge and state of temperature based on a hybrid electrochemical-thermal-neural-network model-Reference-Cited by-同舟云学术

Co-estimation of lithium-ion battery state of charge and state of temperature based on a hybrid electrochemical-thermal-neural-network model

Published:2020-04 Issue: Volume:455 Page:227935
ISSN:0378-7753
Container-title:Journal of Power Sources
language:en
Short-container-title:Journal of Power Sources

Author:

Feng Fei,Teng Sangli,Liu Kailong,Xie Jiale,Xie Yi,Liu Bo,Li Kexin

Funder

NSF of China

Chinese Postdoctoral Science Foundation

Special Foundation of Chongqing Postdoctoral Science

Chongqing special project of basic research and frontier exploration – postdoctoral science fund

Chongqing entrepreneurship and innovation support fund for returned overseas students

Chongqing technological innovation and application development - Major theme projects

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Physical and Theoretical Chemistry,Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Reference56 articles.

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3. Gaussian process regression with automatic relevance determination Kernel for calendar aging prediction of lithium-ion batteries;Liu;IEEE Transactions on Industrial Informatics,2019

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

5. Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries;Zheng;Appl. Energy,2016

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