The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Lithium-Ion Battery State of Charge and Critical Surface Charge Estimation Using an Electrochemical Model-Based Extended Kalman Filter
Abstract
This paper presents a numerical calculation of the evolution of the spatially resolved solid concentration in the two electrodes of a lithium-ion cell. The microscopic solid concentration is driven by the macroscopic Butler–Volmer current density distribution, which is consequently driven by the applied current through the boundary conditions. The resulting, mostly causal, implementation of the algebraic differential equations that describe the battery electrochemical principles, even after assuming fixed electrolyte concentration, is of high order and complexity and is denoted as the full order model. The full order model is compared with the results in the works of Smith and Wang (2006, “Solid-State Diffusion Limitations on Pulse Operation of a Lithium-Ion Cell for Hybrid Electric Vehicles,” J. Power Sources, 161, pp. 628–639) and Wang et al. (2007 “Control oriented 1D Electrochemical Model of Lithium Ion Battery,” Energy Convers. Manage., 48, pp. 2565–2578) and creates our baseline model, which will be further simplified for charge estimation. We then propose a low order extended Kalman filter for the estimation of the average-electrode charge similarly to the single-particle charge estimation in the work of White and Santhanagopalan (2006, “Online Estimation of the State of Charge of a Lithium Ion Cell,” J. Power Sources, 161, pp. 1346–1355) with the following two substantial enhancements. First, we estimate the average-electrode, or single-particle, solid-electrolyte surface concentration, called critical surface charge in addition to the more traditional bulk concentration called state of charge. Moreover, we avoid the weakly observable conditions associated with estimating both electrode concentrations by recognizing that the measured cell voltage depends on the difference, and not the absolute value, of the two electrode open circuit voltages. The estimation results of the reduced, single, averaged electrode model are compared with the full order model simulation.
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Citations
Cites
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Doyle, M., Fuller, T. F., & Newman, J. (1993) · Journal of The Electrochemical Society · doi:10.1149/1.2221597 · Cited by 4,328
Nonlinear controllability and observability
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Ramadass, P., Haran, B., Gomadam, P. M., White, R., & Popov, B. N. (2004) · Journal of The Electrochemical Society · doi:10.1149/1.1634273 · Cited by 794
Determination of state-of-charge and state-of-health of batteries by fuzzy logic methodology
Salkind, A. J., Fennie, C., Singh, P., Atwater, T., & Reisner, D. E. (1999) · Journal of Power Sources · doi:10.1016/s0378-7753(99)00079-8 · Cited by 457
Control oriented 1D electrochemical model of lithium ion battery
Smith, K. A., Rahn, C. D., & Wang, C.-Y. (2007) · Energy Conversion and Management · doi:10.1016/j.enconman.2007.03.015 · Cited by 445
Smith, K., & Wang, C.-Y. (2006) · Journal of Power Sources · doi:10.1016/j.jpowsour.2006.03.050 · Cited by 373
Micro‐Macroscopic Coupled Modeling of Batteries and Fuel Cells: I. Model Development
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Online estimation of the state of charge of a lithium ion cell
Santhanagopalan, S., & White, R. E. (2006) · Journal of Power Sources · doi:10.1016/j.jpowsour.2006.04.146 · Cited by 279
Cited by
He, H., Xiong, R., & Fan, J. (2011) · Energies · doi:10.3390/en4040582 · Cited by 1,180
Waag, W., Fleischer, C., & Sauer, D. U. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.02.064 · Cited by 1,059
Zheng, F., Xing, Y., Jiang, J., Sun, B., Kim, J., & Pecht, M. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.09.010 · Cited by 574
Hu, X., Cao, D., & Egardt, B. (2018) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2017.2675920 · Cited by 205
Liu, B., Tang, X., & Gao, F. (2020) · Electrochimica Acta · doi:10.1016/j.electacta.2020.136098 · Cited by 199
Metadata
- Authors
- Di Domenico, D., Stefanopoulou, A., & Fiengo, G.
- Venue
- Journal of Dynamic Systems, Measurement, and Control
- Publisher
- ASME International
- Published
- 2010-10-29
- Volume
- 132
- Issue
- 6
- ISSN
- 0022-0434 (ISSN-L)
- 1528-9028
- OpenAlex
- W2089280577
- Cited by
- 401
- References
- 20
- FWCI
- 30.36
- Type
- journal article
- Language
- en
- Open access
- closed
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- Di Domenico, D., Stefanopoulou, A., & Fiengo, G. (2010). Lithium-Ion Battery State of Charge and Critical Surface Charge Estimation Using an Electrochemical Model-Based Extended Kalman Filter. Journal of Dynamic Systems, Measurement, and Control. https://doi.org/10.1115/1.4002475
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