Bhushan, Neha and Mekhilef, Saad and Tey, Kok Soon and Shaaban, Mohamed and Seyedmahmoudian, Mehdi and Stojcevski, Alex (2022) Overview of model- and non-model-based online battery management systems for electric vehicle applications: A comprehensive review of experimental and simulation studies. Sustainability, 14 (23). ISSN 2071-1050, DOI https://doi.org/10.3390/su142315912.
Full text not available from this repository.Abstract
The online battery management system (BMS) is very critical for the safe and reliable operation of electric vehicles (EVs) and renewable energy storage applications. The primary responsibility of BMS is data assembly, state monitoring, state management, state safety, charging control, thermal management, and information management. The algorithm and control development for smooth and cost-effective functioning of online BMS is challenging research. The complexity, stability, cost, robustness, computational cost, and accuracy of BMS for Li-ion batteries (LiBs) can be enhanced through the development of algorithms. The model-based and non-model-based data-driven methods are the most suitable for developing algorithms and control for online BMS than other methods present in the literatures. The performance analysis of algorithms under different current, thermal, and load conditions have been investigated. The objective of this review is to advance the experimental design and control for online BMS. The comprehensive overview of present techniques, core issues, technical challenges, emerging trends, and future research opportunities for next-generation BMS is covered in this paper with experimental and simulation analysis.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | lithium-ion battery; battery management system (BMS); electrical vehicle (EV); battery charging; battery modeling; states estimation and fault diagnosis |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Computer Science & Information Technology Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms Koh Ai Peng |
| Date Deposited: | 06 Nov 2024 08:54 |
| Last Modified: | 06 Nov 2024 08:54 |
| URI: | http://eprints.um.edu.my/id/eprint/46127 |
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