A review of expert hybrid and co-estimation techniques for SOH and RUL estimation in battery management system with electric vehicle application-Reference-Cited by-同舟云学术

A review of expert hybrid and co-estimation techniques for SOH and RUL estimation in battery management system with electric vehicle application

Published:2024-07 Issue: Volume:246 Page:123123
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Alsuwian Turki,Ansari Shaheer^ORCID,Ammirrul Atiqi Mohd Zainuri Muhammad,Ayob Afida^ORCID,Hussain Aini,Hossain Lipu M.S.,Alhawari Adam R.H.,Almawgani A.H.M.,Almasabi Saleh^ORCID,Taher Hindi Ayman

Funder

Najran University

Universiti Kebangsaan Malaysia

Publisher

Elsevier BV

Reference122 articles.

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2. Jellyfish optimized recurrent neural network for state of health estimation of lithium-ion batteries;Ansari;Expert Systems with Applications,2024

3. Particle swarm optimized data-driven model for remaining useful life prediction of lithium-ion batteries by systematic sampling;Ansari;Journal of Energy Storage,2022

4. Remaining useful life prediction for lithium-ion battery storage system: A comprehensive review of methods, key factors, issues and future outlook;Ansari;Energy Reports,2022

5. Multi-channel profile based artificial neural network approach for remaining useful life prediction of electric vehicle lithium-ion batteries;Ansari;Energies,2021

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