<p>Low-order equivalent circuit models (ECMs) are widely used in battery management systems (BMSs) because they balance accuracy with computational efficiency. Here we present a harmonised electro–thermal benchmark to evaluate voltage accuracy, heat-generation consistency, and temperature prediction under both constant-current and dynamic loading conditions. Three low-order model structures are assessed: the internal-resistance (Rint) model, the first-order Thevenin (1RC) model, and a compact hybrid electro–thermal 1RC model that incorporates bounded electrical adaptation and a two-node thermal network. Model parameters are identified using standard open-circuit-voltage and pulse-based experiments, while thermal parameters are obtained independently from heating–cooling tests and held fixed during validation. Performance is evaluated using commercial 18650 lithium-ion cells across ambient temperatures of 0<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(^{\circ }\)</EquationSource> </InlineEquation>C,25<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(^{\circ }\)</EquationSource> </InlineEquation>C and 40<InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(^{\circ }\)</EquationSource> </InlineEquation>C under both laboratory and drive-cycle-inspired load profiles. The results show that increasing electrical model fidelity substantially improves voltage tracking under dynamic conditions and leads to more consistent heat-generation pathways when coupled to a fixed thermal model. Under the strict hold-out profile inspired by the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) at 25<InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(^{\circ }\)</EquationSource> </InlineEquation>C, the hybrid electro–thermal 1RC model delivers a voltage root mean square error (RMSE) of <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\mathbf {28\pm 5}\)</EquationSource> </InlineEquation> mV, a surface-temperature RMSE of <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(\mathbf {1.2\pm 0.3}\)</EquationSource> </InlineEquation> <InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(^{\circ }\)</EquationSource> </InlineEquation>C, and a heat-generation consistency mismatch of <InlineEquation ID="IEq8"> <EquationSource Format="TEX">\(\varvec{\varepsilon _Q=1.8\pm 0.4\%}\)</EquationSource> </InlineEquation> (mean ± SD across <InlineEquation ID="IEq9"> <EquationSource Format="TEX">\(n=3\)</EquationSource> </InlineEquation> cells). These results provide quantitative guidance for selecting compact electro–thermal battery models for real-time applications under dynamic operation.</p>

Electro–thermal benchmarking of low-order lithium-ion battery equivalent circuit models under constant-current and dynamic loading

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2026年7月1日

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Smaranika Mishra,
Sarat Chandra Swain,
Zefree Lazarus Mayaluri,
Prabodh Kumar Sahoo,
Aswini Kumar Samantaray

摘要

Low-order equivalent circuit models (ECMs) are widely used in battery management systems (BMSs) because they balance accuracy with computational efficiency. Here we present a harmonised electro–thermal benchmark to evaluate voltage accuracy, heat-generation consistency, and temperature prediction under both constant-current and dynamic loading conditions. Three low-order model structures are assessed: the internal-resistance (Rint) model, the first-order Thevenin (1RC) model, and a compact hybrid electro–thermal 1RC model that incorporates bounded electrical adaptation and a two-node thermal network. Model parameters are identified using standard open-circuit-voltage and pulse-based experiments, while thermal parameters are obtained independently from heating–cooling tests and held fixed during validation. Performance is evaluated using commercial 18650 lithium-ion cells across ambient temperatures of 0 \(^{\circ }\) C,25 \(^{\circ }\) C and 40 \(^{\circ }\) C under both laboratory and drive-cycle-inspired load profiles. The results show that increasing electrical model fidelity substantially improves voltage tracking under dynamic conditions and leads to more consistent heat-generation pathways when coupled to a fixed thermal model. Under the strict hold-out profile inspired by the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) at 25 \(^{\circ }\) C, the hybrid electro–thermal 1RC model delivers a voltage root mean square error (RMSE) of \(\mathbf {28\pm 5}\) mV, a surface-temperature RMSE of \(\mathbf {1.2\pm 0.3}\) \(^{\circ }\) C, and a heat-generation consistency mismatch of \(\varvec{\varepsilon _Q=1.8\pm 0.4\%}\) (mean ± SD across \(n=3\) cells). These results provide quantitative guidance for selecting compact electro–thermal battery models for real-time applications under dynamic operation.