Kalman Filter SoC estimation for Li-Ion batteries
Abstract
State-of-Charge (SoC) estimation is a key factor for correct and safe battery management, particularly for the development of the Battery Management System (BMS) [1]. The paper deals with this problem for the currently most promising technology in the battery filed: Lithium-Ion batteries. An electric model of the cell is identified and verified, in order to apply Kalman Filter Theory and design an algorithm for estimating SoC. Particularly the aim of the algorithm is to reject measurement noise and parametric uncertainties and be applicable to different cells of the same manufacturer and technology. In this purpose, design criterions that speed up the convergence time or make the estimation robust to noise measurements are presented. Results on two different cells of the same manufacturer and typology are shown, focusing on the different behaviors of the estimation due to different design choices.
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Filter-based SOC estimation techniques use mathematical filters to process noisy sensor data and provide an accurate estimate of SOC.
“Filter-based SOC estimation techniques use mathematical filters to process noisy sensor data and provide an accurate estimate of SOC [55].”
From Review Paper for SOC Estimation Techniques: Challenges and Future Areas for Improvement (2024) · cites this paper as [55]
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- Authors
- Spagnol, P., Rossi, S., & Savaresi, S. M.
- Affiliations
- Politecnico di Milano (IT)
- Venue
- 2011 IEEE International Conference on Control Applications (CCA)
- Publisher
- IEEE
- Published
- 2011-09
- Pages
- 587-592
- ISSN
- 1085-1992 (ISSN-L)
- OpenAlex
- W2102886344
- Cited by
- 91
- References
- 9
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 14 · 2023: 10 · 2022: 8 · 2021: 7 · 2020: 4 · 2019: 7 · 2018: 7 · 2017: 4 · 2016: 6 · 2015: 7 · 2014: 1 · 2013: 4 · 2012: 1
- FWCI
- 3.02
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- The proceedings of the IEEE Conference on Control Applications/The proceedings of the ... IEEE Conference on Control Applications (publishedVersion)
- Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Keywords
- state of charge estimation, lithium-ion batteries, Kalman filter, battery management systems, battery cell modeling, parameter uncertainty, robust estimation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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