The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
An analytical model for predicting the remaining battery capacity of lithium-ion batteries
Abstract
Predicting the residual energy of the battery source that powers a portable electronic device is imperative in designing and applying an effective dynamic power management policy for the device. This paper starts up by showing that a 30% error in predicting the battery capacity of a lithium-ion battery can result in up to 20% performance degradation for a dynamic voltage and frequency scaling algorithm. Next, this paper presents a closed form analytical expression for predicting the remaining capacity of a lithium-ion battery. The proposed high-level model, which relies on online current and voltage measurements, correctly accounts for the temperature and cycle aging effects. The accuracy of the high-level model is validated by comparing it with DUALFOIL simulation results, demonstrating a maximum of 5% error between simulated and predicted data.
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Citations
Cites
Modeling of Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell
Doyle, M., Fuller, T. F., & Newman, J. (1993) · Journal of The Electrochemical Society · doi:10.1149/1.2221597 · Cited by 4,328 · cited 4×
“There already exist tools that allow for detailed analysis of the battery at the microscopic scale [5, 8].”
BackgroundMethodInfluentialSimulation and Optimization of the Dual Lithium Ion Insertion Cell
Fuller, T. F., Doyle, M., & Newman, J. (1994) · Journal of The Electrochemical Society · doi:10.1149/1.2054684 · Cited by 2,057
Capacity Fade Mechanisms and Side Reactions in Lithium‐Ion Batteries
Arora, P., White, R. E., & Doyle, M. (1998) · Journal of The Electrochemical Society · doi:10.1149/1.1838857 · Cited by 1,408 · cited 2×
“In [ 23 ], the growth of the film is related to the rate of the side reaction by”
BackgroundHuet, F. (1998) · Journal of Power Sources · doi:10.1016/s0378-7753(97)02665-7 · Cited by 593
Cited by
Modeling of the Cost of EV Battery Wear Due to V2G Application in Power Systems
Zhou, C., Qian, K., Allan, M., & Zhou, W. (2011) · IEEE Transactions on Energy Conversion · doi:10.1109/tec.2011.2159977 · Cited by 495
Farmann, A., Waag, W., Marongiu, A., & Sauer, D. U. (2015) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.01.129 · Cited by 472
Jayasekara, N., Masoum, M. A. S., & Wolfs, P. J. (2016) · IEEE Transactions on Sustainable Energy · doi:10.1109/tste.2015.2487360 · Cited by 260
Time-Domain Parameter Extraction Method for Thévenin-Equivalent Circuit Battery Models
Hentunen, A., Lehmuspelto, T., & Suomela, J. (2014) · IEEE Transactions on Energy Conversion · doi:10.1109/tec.2014.2318205 · Cited by 245
Metadata
- Authors
- Rong, P., & Pedram, M.
- Venue
- IEEE Transactions on Very Large Scale Integration (VLSI) Systems
- Published
- 2006-05
- Volume
- 14
- Issue
- 5
- Pages
- 441-451
- ISSN
- 1063-8210 (ISSN-L)
- 1557-9999
- OpenAlex
- W2135337656
- Cited by
- 321
- References
- 4
- FWCI
- 19.66
- Type
- journal article
- Language
- en
- Open access
- closed
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- Rong, P., & Pedram, M. (2006). An analytical model for predicting the remaining battery capacity of lithium-ion batteries. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. https://doi.org/10.1109/tvlsi.2006.876094
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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