A Reduced-Order Model of Lithium–Sulfur Battery Discharge
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| Publicado en: | Batteries vol. 11, no. 1 (2025), p. 15 |
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| Autor principal: | |
| Otros Autores: | |
| Publicado: |
MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2313-0105 | ||
| 024 | 7 | |a 10.3390/batteries11010015 |2 doi | |
| 035 | |a 3159404353 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Haddad, Noushin | |
| 245 | 1 | |a A Reduced-Order Model of Lithium–Sulfur Battery Discharge | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This paper examines the problem of modeling lithium–sulfur (Li-S) battery discharge dynamics. The importance of this problem stems from the attractive specific energy levels achievable by Li-S batteries, which can be particularly appealing for applications such as aviation electrification. Previous research presents different Li-S battery models, including “zero-dimensional” models that neglect diffusion while using the laws of electrochemistry to represent reduction–oxidation (redox) rates. Zero-dimensional models typically succeed in capturing key features of Li-S battery discharge, including the high plateau, low plateau, and dip point visible in the discharge curves of certain Li-S battery chemistries. However, these models’ use of one state variable to represent the mass of each active species tends to furnish high-order models, with many state variables. This increases the computational complexity of model-based estimation and optimal control. The main contribution of this paper is to develop low-order state-space model of Li-S battery discharge. Specifically, the paper starts with a seventh-order zero-dimensional model of Li-S discharge dynamics, analyzes its discharge behavior, constructs phenomenological second- and third-order models capable of replicating this behavior, and parameterizes these models. The proposed models succeed in capturing battery discharge behavior accurately over a wide range of discharge rates. To the best of our knowledge, these are two of the simplest published models capable of doing so. | |
| 653 | |a Discharge | ||
| 653 | |a Simulation | ||
| 653 | |a Accuracy | ||
| 653 | |a Electrolytes | ||
| 653 | |a Physics | ||
| 653 | |a Reduced order models | ||
| 653 | |a Specific energy | ||
| 653 | |a Electrodes | ||
| 653 | |a Oxidation | ||
| 653 | |a State space models | ||
| 653 | |a State variable | ||
| 653 | |a Variables | ||
| 653 | |a Sulfur | ||
| 653 | |a Diffusion rate | ||
| 653 | |a Batteries | ||
| 653 | |a Electrochemistry | ||
| 653 | |a Optimal control | ||
| 653 | |a Dimensional analysis | ||
| 653 | |a Lithium sulfur batteries | ||
| 653 | |a Lithium | ||
| 653 | |a Composite materials | ||
| 653 | |a Energy levels | ||
| 700 | 1 | |a Fathy, Hosam K | |
| 773 | 0 | |t Batteries |g vol. 11, no. 1 (2025), p. 15 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3159404353/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3159404353/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3159404353/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |