Hybrid and combined states estimation approaches for lithium-ion battery management system: Advancement, challenges and future directions

Hossain Lipu, M.S. and Abd Rahman, M.S. and Mansor, M. and Ansari, S. and Meraj, S.T. and Hannan, M.A. (2024) Hybrid and combined states estimation approaches for lithium-ion battery management system: Advancement, challenges and future directions. Journal of Energy Storage, 92.

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Abstract

Battery management system plays a crucial role in enhancing the performance and effectiveness of electric vehicles. The accurate state estimation in terms of state of charge, state of health, state of energy, state of power, and remaining useful life of battery management system is essential to manage and optimize the performance of electric vehicles. Recently, hybrid and combined states estimations of lithium-ion battery management system have received huge attention due to their excellent accuracy and resilience in a variety of environmental settings. Nevertheless, the deployment of hybrid and co-estimation of various states for lithium-ion battery management system in EVs are still limited. Hence, the novel innovation of this review is to provide an in-depth analysis of hybrid approaches with an emphasis on state-of-the-art approaches, executions, accuracy, advantages, drawbacks, and contributions. Moreover, this review explores the several co-estimation methods concerning framework, execution aspects, issues, and performance assessment. Furthermore, the study investigates various key challenges and limitations of hybrid and combined states estimation of battery management system. Finally, prospects and research opportunities are offered to support electric vehicle engineers and the automotive industry in developing a reliable and accurate state of charge, state of health, state of energy and state of power, the remaining useful life estimation technique using a hybrid and co-estimation approach that will create a pathway to reduce global carbon emissions towards meeting sustainable development goals. © 2024

Item Type: Article
Additional Information: cited By 0
Uncontrolled Keywords: Automotive industry; Charging (batteries); Electric vehicles; Information management; Ions; Lithium-ion batteries; Sustainable development; Vehicle performance, Co-estimation; Combined states estimation; Data driven; Energy; Estimation approaches; Hybrid approach; Hybrid states estimation; Model-based OPC; Performance; States of charges, Battery management systems
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 04 Jun 2024 14:19
Last Modified: 04 Jun 2024 14:19
URI: https://khub.utp.edu.my/scholars/id/eprint/19587

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