A novel streamlined particle‐unscented Kalman filtering method for the available energy prediction of lithium‐ion batteries considering the time‐varying temperature‐current influence-Reference-Cited by-同舟云学术

A novel streamlined particle‐unscented Kalman filtering method for the available energy prediction of lithium‐ion batteries considering the time‐varying temperature‐current influence

Published:2021-07-04 Issue:12 Volume:45 Page:17858-17877
ISSN:0363-907X
Container-title:International Journal of Energy Research
language:en
Short-container-title:Int J Energy Res

Author:

Zhang Liang¹²^ORCID,Wang Shunli¹³^ORCID,Zou Chuanyun¹,Fan Yongcun¹,Jin Siyu³,Fernandez Carlos⁴

Affiliation:

1. School of Information Engineering & Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Southwest University of Science and Technology Mianyang China

2. School of Mechanical and Electrical Engineering Mianyang Teachers' College Mianyang China

3. Department of Energy Technology Aalborg University Aalborg East Denmark

4. School of Pharmacy and Life Sciences Robert Gordon University Aberdeen UK

Funder

China Scholarship Council

National Natural Science Foundation of China

Publisher

Wiley

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.6930

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5. SOC estimation of lead carbon batteries based on the operating conditions of an energy storage system in a microgrid system;Chen YY;Energies,2020