A generalized form for frequency-response modeling of battery energy storage systems

The increasing reliance on rechargeable batteries necessitates advanced diagnostic tools. This thesis identifies and validates a generalized 14 parameter distributed equivalent circuit model (dECM) capable of describing the electrochemical impedance behavior of three commercial battery chemistries: a 1.5 Ah lithium-ion (LiFePO4), a 5 Ah lithium-ion (NMC811), and a 1.5 Ah sodium-ion (NaFePO4) cell. An extensive experimental protocol was executed, subjecting the cells to conditions including temperatures from −20°C to +60°C, states of charge from 0-100%, aging up to 280 cycles, and mechanical damage (indentation and bending). Through a systematic evaluation of fourteen candidate models, a single dECM, Model M11, was validated for both LFP and NMC811 cells, consistently achieving a goodness of fit (χ2) below 1.8×10−4 and parameter relative standard deviations below 20%. The robustness of this model provides strong evidence that a common, physics-informed framework can capture the fundamental electrochemical processes in different Li-ion systems. For the Na-ion batteries, this work established critical benchmarks, showing its impedance at 0% SOC is an order of magnitude higher than Li-ion and that its slower dynamics necessitate a six hour rest period for stable measurement. Mechanical failure analysis revealed its primary failure mode is separator breach, causing an internal short circuit at an indentation depth of 5.9-7.3 mm, preceding the point of maximum mechanical load, which consistently occurs around 7.3 mm. Analysis of the model parameters reveals specific trends indicative of the battery’s state, such as a consistent increase in charge transfer resistance with cycle aging and a sharp decrease in inductance at the onset of mechanical damage. These relationships can be integrated into advanced battery management systems to enable real time monitoring of both long term degradation for state of health estimation and issues related to cell safety.

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Publication Details

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TUScholarShare (Temple University)
Published
2025-12-01
Primary Topic
Advanced Battery Technologies Research
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article

A generalized form for frequency-response modeling of battery energy storage systems

Alexa Shaw
TUScholarShare (Temple University)
Advanced Battery Technologies Research
article

A generalized form for frequency-response modeling of battery energy storage systems

Alexa Shaw
article en

Abstract

The increasing reliance on rechargeable batteries necessitates advanced diagnostic tools. This thesis identifies and validates a generalized 14 parameter distributed equivalent circuit model (dECM) capable of describing the electrochemical impedance behavior of three commercial battery chemistries: a 1.5 Ah lithium-ion (LiFePO4), a 5 Ah lithium-ion (NMC811), and a 1.5 Ah sodium-ion (NaFePO4) cell. An extensive experimental protocol was executed, subjecting the cells to conditions including temperatures from −20°C to +60°C, states of charge from 0-100%, aging up to 280 cycles, and mechanical damage (indentation and bending). Through a systematic evaluation of fourteen candidate models, a single dECM, Model M11, was validated for both LFP and NMC811 cells, consistently achieving a goodness of fit (χ2) below 1.8×10−4 and parameter relative standard deviations below 20%. The robustness of this model provides strong evidence that a common, physics-informed framework can capture the fundamental electrochemical processes in different Li-ion systems. For the Na-ion batteries, this work established critical benchmarks, showing its impedance at 0% SOC is an order of magnitude higher than Li-ion and that its slower dynamics necessitate a six hour rest period for stable measurement. Mechanical failure analysis revealed its primary failure mode is separator breach, causing an internal short circuit at an indentation depth of 5.9-7.3 mm, preceding the point of maximum mechanical load, which consistently occurs around 7.3 mm. Analysis of the model parameters reveals specific trends indicative of the battery’s state, such as a consistent increase in charge transfer resistance with cycle aging and a sharp decrease in inductance at the onset of mechanical damage. These relationships can be integrated into advanced battery management systems to enable real time monitoring of both long term degradation for state of health estimation and issues related to cell safety.

TUScholarShare (Temple University)
Affordable and clean energy
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Advanced Battery Technologies Research
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