Reduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery

Battery energy storage systems are essential for stabilizing the intermittent power generation of renewable energy (RE) technologies. Their integration into RE systems is typically studied using energy systems modeling software that utilize either idealized models or complex models that require expe...

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Autores principales:	Michael T. Castro, Joey D. Ocon
Formato:	article
Lenguaje:	EN
Publicado:	AIDIC Servizi S.r.l. 2021
Materias:	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895
Acceso en línea:	https://doaj.org/article/543ec63b204e49dab5dec2e11a0543db
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spelling	oai:doaj.org-article:543ec63b204e49dab5dec2e11a0543db2021-11-15T21:48:47ZReduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery10.3303/CET21880372283-9216https://doaj.org/article/543ec63b204e49dab5dec2e11a0543db2021-11-01T00:00:00Zhttps://www.cetjournal.it/index.php/cet/article/view/11830https://doaj.org/toc/2283-9216Battery energy storage systems are essential for stabilizing the intermittent power generation of renewable energy (RE) technologies. Their integration into RE systems is typically studied using energy systems modeling software that utilize either idealized models or complex models that require experimental data. Reduced order modeling offers minimal experimental costs through the use of a multiphysics model in lieu of experimental battery data. In this work, a previously reported multiphysics model of a lithium ion lithium iron phosphate (Li ion LFP) battery was simulated in COMSOL Multiphysics® and reduced into an equivalent circuit model (ECM). The reduced order ECM was then implemented as a battery systems model in an energy systems modeling tool to perform RE-based hybridization studies. Techno economic case studies were conducted on RE based systems powering a household and an off grid island to validate the reduced order ECM with the idealized battery model with HOMER Pro. Optimal component sizes computed using the two software generally showed good agreement and deviations were attributed to electrical losses. The state of charge (SOC) vs. time graphs generated by the two software had an average root mean square error of 0.00173 SOC units across the different case studies. Discrepancies were observed during rapid charging or high SOC values, which were characteristic of the reduced order ECM. This model reduction framework can be applied to other energy storage and conversion technologies, such as other Li ion chemistries, fuel cells, and supercapacitors, to generate chemistry specific models for energy systems research.Michael T. CastroJoey D. OconAIDIC Servizi S.r.l.articleChemical engineeringTP155-156Computer engineering. Computer hardwareTK7885-7895ENChemical Engineering Transactions, Vol 88 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895
spellingShingle	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895 Michael T. Castro Joey D. Ocon Reduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery
description	Battery energy storage systems are essential for stabilizing the intermittent power generation of renewable energy (RE) technologies. Their integration into RE systems is typically studied using energy systems modeling software that utilize either idealized models or complex models that require experimental data. Reduced order modeling offers minimal experimental costs through the use of a multiphysics model in lieu of experimental battery data. In this work, a previously reported multiphysics model of a lithium ion lithium iron phosphate (Li ion LFP) battery was simulated in COMSOL Multiphysics® and reduced into an equivalent circuit model (ECM). The reduced order ECM was then implemented as a battery systems model in an energy systems modeling tool to perform RE-based hybridization studies. Techno economic case studies were conducted on RE based systems powering a household and an off grid island to validate the reduced order ECM with the idealized battery model with HOMER Pro. Optimal component sizes computed using the two software generally showed good agreement and deviations were attributed to electrical losses. The state of charge (SOC) vs. time graphs generated by the two software had an average root mean square error of 0.00173 SOC units across the different case studies. Discrepancies were observed during rapid charging or high SOC values, which were characteristic of the reduced order ECM. This model reduction framework can be applied to other energy storage and conversion technologies, such as other Li ion chemistries, fuel cells, and supercapacitors, to generate chemistry specific models for energy systems research.
format	article
author	Michael T. Castro Joey D. Ocon
author_facet	Michael T. Castro Joey D. Ocon
author_sort	Michael T. Castro
title	Reduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery
title_short	Reduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery
title_full	Reduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery
title_fullStr	Reduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery
title_full_unstemmed	Reduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery
title_sort	reduced-order modeling of a lithium-ion lithium iron phosphate battery
publisher	AIDIC Servizi S.r.l.
publishDate	2021
url	https://doaj.org/article/543ec63b204e49dab5dec2e11a0543db
work_keys_str_mv	AT michaeltcastro reducedordermodelingofalithiumionlithiumironphosphatebattery AT joeydocon reducedordermodelingofalithiumionlithiumironphosphatebattery
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Reduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery

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