Model‐based state of X estimation of lithium‐ion battery for electric vehicle applications-Reference-Cited by-同舟云学术

Model‐based state of X estimation of lithium‐ion battery for electric vehicle applications

Published:2022-03-28 Issue:8 Volume:46 Page:10704-10723
ISSN:0363-907X
Container-title:International Journal of Energy Research
language:en
Short-container-title:Intl J of Energy Research

Author:

Shrivastava Prashant¹^ORCID,Soon Tey Kok¹^ORCID,Idris Mohd Yamani Idna Bin¹^ORCID,Mekhilef Saad²³^ORCID,Adnan Syed Bahari Ramadzan Syed⁴^ORCID

Affiliation:

1. Department of Computer System and Technology, Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia

2. School of Science, Computing and Engineering Technologies Swinburne University of Technology Hawthorn Victoria Australia

3. Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering University of Malaya Kuala Lumpur Malaysia

4. Centre for Foundation Studies in Science University of Malaya Kuala Lumpur Malaysia

Publisher

Hindawi Limited

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.7874

Reference43 articles.

1. A review on the key issues for lithium-ion battery management in electric vehicles

2. Implementation for a cloud battery management system based on the CHAIN framework

3. State of charge estimation of a Li‐ion battery based on extended Kalman filtering and sensor bias

4. A framework for state-of-charge and remaining discharge time prediction using unscented particle filter

5. A novel Gaussian model based battery state estimation approach: State-of-Energy

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