New EIS-based method could improve state-of-charge estimation for LiFePO4 batteries

Researchers have investigated a practical method for estimating the state of charge of lithium iron phosphate batteries using electrochemical impedance spectroscopy reconstructed from short-period sine-wave current pulses. The approach is designed to address a persistent challenge in LiFePO4, or LFP, cells: their flat open-circuit voltage curve, which makes conventional voltage-based state-of-charge estimation difficult.

Accurate state-of-charge, or SOC, estimation is essential for battery management systems. In electric vehicles and energy storage systems, the SOC estimate helps determine available energy, charging strategy, operating limits, and user-facing range or runtime information. If SOC is inaccurate, a battery system may be operated too conservatively or too aggressively, reducing performance, reliability, and safety margins.

LFP batteries are attractive because of their safety, cycle life, and growing use in transportation and storage applications. However, they pose a special estimation challenge. Their open-circuit voltage, or OCV, changes only slightly over a wide SOC range, which means voltage alone may not provide enough information to distinguish one SOC level from another. This flat OCV-SOC relationship makes robust initialization and calibration especially important.

The new study explores electrochemical impedance spectroscopy, or EIS, as an alternative source of SOC information. EIS can reveal how a cell responds to small current perturbations across different frequencies, providing information about internal electrochemical behavior that may not be visible from voltage alone. According to the article, recent studies suggest that EIS offers a promising route for SOC estimation in LFP cells, but practical implementation remains important because conventional EIS measurements can require specialized equipment.

To address this, the researchers characterize the EIS of LFP cells across a broad frequency range from 0.01 Hz to 1000 Hz and across the full SOC range from 0 to 1. They find that the EIS magnitude and phase at 0.01 Hz exhibit the highest signal-to-noise ratio and select those values as features for SOC estimation. This frequency-specific result is useful because it narrows the information needed for estimation, rather than requiring a full impedance spectrum during operation.

The study then develops and validates an EIS identification algorithm to reconstruct EIS at 0.01 Hz using short-duration sinusoidal current pulses. The method uses Fourier series expansion to approximate the voltage response to small sine-wave current perturbations. By reconstructing the impedance information from current and voltage signal data, the approach aims to make EIS-based SOC estimation more practical and less dependent on costly laboratory equipment.

After reconstructing the EIS information, the algorithm estimates SOC by mapping the reconstructed EIS to experimental EIS data. The authors validate the approach using sine-wave currents with different amplitudes, including 0.05 A and 0.1 A, and under different cell operation modes, including discharge and charge. The results demonstrate rapid and accurate initialization of LFP cell SOC using the proposed estimation algorithm.

For battery management systems, this kind of method could be valuable because it connects electrochemical insight with practical signal measurement. Instead of relying only on an OCV reading that may be ambiguous in LFP cells, the battery system could use short sine-wave perturbations and the resulting voltage response to infer SOC more reliably. That may be especially useful during initialization, when an accurate starting SOC is needed before the system can track charge movement over time.

Further validation will still be needed across broader cell formats, aging states, temperatures, and real-world operating profiles. Even so, the study offers a strong indication that short-period sine-wave pulses can support practical EIS reconstruction and SOC estimation for LFP batteries. As LFP chemistry becomes more common in transportation and energy systems, methods that improve SOC accuracy without costly equipment may become increasingly important for reliable battery management.

Reference
Author:
Yizhao Gao, Simona Onori

Title of original paper:
Advancing LiFePO4 battery SOC estimation: Electrochemical impedance spectroscopy with short-period sine-wave pulses

Article link:
https://www.sciencedirect.com/science/article/pii/S2773153725001367

Journal:
Green Energy and Intelligent Transportation

DOI:
10.1016/j.geits.2025.100386

Affiliations:

Department of Energy Science and Engineering, Stanford University, Stanford, CA, 94305, USA