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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.28901 |
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| _version_ | 1866914609612455936 |
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| author | Sovljanski, Vladimir Paolone, Mario |
| author_facet | Sovljanski, Vladimir Paolone, Mario |
| contents | This paper investigates the identification of observable low-frequency (LF) parameters of battery cell's equivalent circuit models (ECMs) using time-domain voltage and current measurements sampled at low frequency by built-in battery management systems (BMS) during operation. Accurate estimation of such parameters is challenging due to measurement resolution available in practical settings. To address this, a modeling and identification framework is proposed in which fractional constant phase element (CPE), commonly used to model LF diffusion phenomena of battery cells, is approximated in the time domain using a high-order RC network with a recursive definition. The parameter estimation problem is formulated as a constrained, non-convex least-squares problem in a discretized state-space representation. To improve robustness, parameter initialization strategies, bounds, and a procedure for selecting the number of RC branches are rigorously derived. The method is evaluated in a numerical study based on a power system application where the battery under the study provides primary frequency control to the grid. Under noise levels representative of typical BMS measurements, the proposed approach achieves, from time-domain measurements, accurate LF parameter estimation (including the CPE), with average errors below 1 %. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_28901 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Identifiability of Low Frequency Li-ion Battery Parameters in Time Domain Sovljanski, Vladimir Paolone, Mario Systems and Control This paper investigates the identification of observable low-frequency (LF) parameters of battery cell's equivalent circuit models (ECMs) using time-domain voltage and current measurements sampled at low frequency by built-in battery management systems (BMS) during operation. Accurate estimation of such parameters is challenging due to measurement resolution available in practical settings. To address this, a modeling and identification framework is proposed in which fractional constant phase element (CPE), commonly used to model LF diffusion phenomena of battery cells, is approximated in the time domain using a high-order RC network with a recursive definition. The parameter estimation problem is formulated as a constrained, non-convex least-squares problem in a discretized state-space representation. To improve robustness, parameter initialization strategies, bounds, and a procedure for selecting the number of RC branches are rigorously derived. The method is evaluated in a numerical study based on a power system application where the battery under the study provides primary frequency control to the grid. Under noise levels representative of typical BMS measurements, the proposed approach achieves, from time-domain measurements, accurate LF parameter estimation (including the CPE), with average errors below 1 %. |
| title | Identifiability of Low Frequency Li-ion Battery Parameters in Time Domain |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2605.28901 |