The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.
State-of-the-Art and Energy Management System of Lithium-Ion Batteries in Electric Vehicle Applications: Issues and Recommendations
Open accessAbstract
A variety of rechargeable batteries are now available in world markets for powering electric vehicles (EVs). The lithium-ion (Li-ion) battery is considered the best among all battery types and cells because of its superior characteristics and performance. The positive environmental impacts and recycling potential of lithium batteries have influenced the development of new research for improving Li-ion battery technologies. However, the cost reduction, safe operation, and mitigation of negative ecological impacts are now a common concern for advancement. This paper provides a comprehensive study on the state of the art of Li-ion batteries including the fundamentals, structures, and overall performance evaluations of different types of lithium batteries. A study on a battery management system for Li-ion battery storage in EV applications is demonstrated, which includes a cell condition monitoring, charge, and discharge control, states estimation, protection and equalization, temperature control and heat management, battery fault diagnosis, and assessment aimed at enhancing the overall performance of the system. It is observed that the Li-ion batteries are becoming very popular in vehicle applications due to price reductions and lightweight with high power density. However, the management of the charging and discharging processes, CO2 and greenhouse gases emissions, health effects, and recycling and refurbishing processes have still not been resolved satisfactorily. Consequently, this review focuses on the many factors, challenges, and problems and provides recommendations for sustainable battery manufacturing for future EVs. This review will hopefully lead to increasing efforts toward the development of an advanced Li-ion battery in terms of economics, longevity, specific power, energy density, safety, and performance in vehicle applications.
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Cites
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A review on the key issues for lithium-ion battery management in electric vehicles
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Self-citationReview of energy system flexibility measures to enable high levels of variable renewable electricity
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Critical review of state of health estimation methods of Li-ion batteries for real applications
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“, 20%-90%, can be accomplished by using a battery management system (BMS) [67], [99], [100].”
Review of energy storage systems for electric vehicle applications: Issues and challenges
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Self-citationCritical Review on the Battery State of Charge Estimation Methods for Electric Vehicles
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Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles
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(2010) · Cited by 909
Cited by
Commercialization of Lithium Battery Technologies for Electric Vehicles
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Current Li-Ion Battery Technologies in Electric Vehicles and Opportunities for Advancements
Miao, Y., Hynan, P., von Jouanne, A., & Yokochi, A. (2019) · Energies · doi:10.3390/en12061074 · Cited by 874
Lipu, M. S. H., Hannan, M. A., Hussain, A., Hoque, M. M., Ker, P. J., Saad, M. H. M., & Ayob, A. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.09.065 · Cited by 755
Self-citationGlobal Trends in High-Power On-Board Chargers for Electric Vehicles
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Nyamathulla, S., & Dhanamjayulu, C. (2024) · Journal of Energy Storage · doi:10.1016/j.est.2024.111179 · Cited by 518
Metadata
- Authors
- Hannan, M. A., Hoque, M. M., Hussain, A., Yusof, Y., & Ker, P. J.
- Venue
- IEEE Access
- Published
- 2018
- Volume
- 6
- Pages
- 19362-19378
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2792524465
- Cited by
- 988
- References
- 85
- FWCI
- 40.20
- Type
- journal article
- Language
- en
- Open access
- gold
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- Hannan, M. A., Hoque, M. M., Hussain, A., Yusof, Y., & Ker, P. J. (2018). State-of-the-Art and Energy Management System of Lithium-Ion Batteries in Electric Vehicle Applications: Issues and Recommendations. IEEE Access. https://doi.org/10.1109/access.2018.2817655
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
