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

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 mana...

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Main Authors: Hossain Lipu M.S., Abd Rahman M.S., Mansor M., Ansari S., Meraj S.T., Hannan M.A.
Other Authors: 58562396100
Format: Review
Published: Elsevier Ltd 2025
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Summary: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