The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles
Abstract
With the rapidly evolving technology of the smart grid and electric vehicles (EVs), the battery has emerged as the most prominent energy storage device, attracting a significant amount of attention. The very recent discussions about the performance of lithium-ion (Li-ion) batteries in the Boeing 787 have confirmed so far that, while battery technology is growing very quickly, developing cells with higher power and energy densities, it is equally important to improve the performance of the battery management system (BMS) to make the battery a safe, reliable, and cost-efficient solution. The specific characteristics and needs of the smart grid and EVs, such as deep charge/discharge protection and accurate state-of-charge (SOC) and state-of-health (SOH) estimation, intensify the need for a more efficient BMS. The BMS should contain accurate algorithms to measure and estimate the functional status of the battery and, at the same time, be equipped with state-of-the-art mechanisms to protect the battery from hazardous and inefficient operating conditions.
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Cites
Ageing mechanisms in lithium-ion batteries
Vetter, J., Novák, P., Wagner, M. R., Veit, C., Möller, K.-C., Besenhard, J. O., Winter, M., Wohlfahrt-Mehrens, M., Vogler, C., & Hammouche, A. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2005.01.006 · Cited by 3,987
Accurate electrical battery model capable of predicting runtime and I-V performance
Chen, M., & Rincon-Mora, G. A. (2006) · IEEE Transactions on Energy Conversion · doi:10.1109/tec.2006.874229 · Cited by 2,427
Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs
Plett, G. L. (2004) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.02.032 · Cited by 1,923
Khaligh, A., & Li, Z. (2010) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2010.2047877 · Cited by 1,817
Ng, K. S., Moo, C.-S., Chen, Y.-P., & Hsieh, Y.-C. (2009) · Applied Energy · doi:10.1016/j.apenergy.2008.11.021 · Cited by 1,636
Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs
Plett, G. L. (2004) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.02.031 · Cited by 1,385
Modeling and Simulation of Lithium-Ion Batteries from a Systems Engineering Perspective
Northrop, P. W. C., De, S., Braatz, R. D., Ramadesigan, V., Northrop, P. W. C., Santhanagopalan, S., & Subramaniana, V. R. (2011) · Cited by 748
Zhang, Z., & Chow, M.-Y. (2012) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2188912 · Cited by 698
Self-citationBattery balancing methods: A comprehensive review
Cao, J., Schofield, N., & Emadi, A. (2008) · 2008 IEEE Vehicle Power and Propulsion Conference · doi:10.1109/vppc.2008.4677669 · Cited by 658
Ecker, M., Gerschler, J. B., Vogel, J., Käbitz, S., Hust, F., Dechent, P., & Sauer, D. U. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.05.012 · Cited by 642
Cited by
Wang, Y., Tian, J., Sun, Z., Wang, L., Xu, R., Li, M., & Chen, Z. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.110015 · Cited by 1,377
Review of energy storage systems for electric vehicle applications: Issues and challenges
Hannan, M. A., Hoque, M. M., Mohamed, A., & Ayob, A. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.11.171 · Cited by 1,050
Hannan, M. A., Hoque, M. M., Hussain, A., Yusof, Y., & Ker, P. J. (2018) · IEEE Access · doi:10.1109/access.2018.2817655 · Cited by 988
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
Flexer, V., Baspineiro, C. F., & Galli, C. I. (2018) · Science of the Total Environment · doi:10.1016/j.scitotenv.2018.05.223 · Cited by 768
Metadata
- Authors
- Rahimi-Eichi, H., Ojha, U., Baronti, F., & Chow, M.-Y.
- Venue
- IEEE Industrial Electronics Magazine
- Published
- 2013-06
- Volume
- 7
- Issue
- 2
- Pages
- 4-16
- ISSN
- 1932-4529 (ISSN-L)
- 1941-0115
- OpenAlex
- W2098841048
- Cited by
- 960
- References
- 31
- FWCI
- 72.08
- Type
- journal article
- Language
- en
- Open access
- closed
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- Rahimi-Eichi, H., Ojha, U., Baronti, F., & Chow, M.-Y. (2013). Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles. IEEE Industrial Electronics Magazine. https://doi.org/10.1109/mie.2013.2250351
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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.
