Real-Time State of Power Estimation of a Lithium-Ion Battery Using Novel Battery Observation Model and the Recursive LS Filter

The state of power (SOP) refers to the maximum available power from a battery. The SOP is a function of the open circuit voltage and internal resistance of the battery, both of which change with the state of charge (SOC). As such, the SOP is a more informative metric of battery state than the SOC and is crucial for the continued operation of an electric vehicle. The existing approaches employ non-linear system identification techniques that are sensitive to changes in temperature and SOC. In this paper, a novel approach is proposed to estimate the state of power in real-time. The proposed approach does not require non-linear approaches for both system identification and filtering. Instead, a linear least squares estimation technique is utilized to estimate the parameters needed for SOP computation. The proposed approach utilizes a robust linear approach to account for the change in OCV in the observation window. The SOP estimates computed through the proposed approach are tested using realistic battery data collected at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$25^{\circ}$</tex> C.

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Published
2025-06-20
DOI
https://doi.org/10.1109/isie62713.2025.11124690
Citations
4
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
2.73
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article

Real-Time State of Power Estimation of a Lithium-Ion Battery Using Novel Battery Observation Model and the Recursive LS Filter

Prarthana Pillai, Krishna R. Pattipati, Balakumar Balasingam
4 citations
Advanced Battery Technologies Research
2.73
article

Real-Time State of Power Estimation of a Lithium-Ion Battery Using Novel Battery Observation Model and the Recursive LS Filter

Prarthana Pillai, Krishna R. Pattipati, Balakumar Balasingam
article en
4 citations

Abstract

The state of power (SOP) refers to the maximum available power from a battery. The SOP is a function of the open circuit voltage and internal resistance of the battery, both of which change with the state of charge (SOC). As such, the SOP is a more informative metric of battery state than the SOC and is crucial for the continued operation of an electric vehicle. The existing approaches employ non-linear system identification techniques that are sensitive to changes in temperature and SOC. In this paper, a novel approach is proposed to estimate the state of power in real-time. The proposed approach does not require non-linear approaches for both system identification and filtering. Instead, a linear least squares estimation technique is utilized to estimate the parameters needed for SOP computation. The proposed approach utilizes a robust linear approach to account for the change in OCV in the observation window. The SOP estimates computed through the proposed approach are tested using realistic battery data collected at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$25^{\circ}$</tex> C.

University of Connecticut (US), University of Windsor (CA)
Affordable and clean energy
Openalex Percentile: Top 9%
Advanced Battery Technologies Research
2.73
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