001026448 001__ 1026448 001026448 005__ 20250204113855.0 001026448 0247_ $$2doi$$a10.1016/j.electacta.2024.144360 001026448 0247_ $$2ISSN$$a0013-4686 001026448 0247_ $$2ISSN$$a1873-3859 001026448 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-03397 001026448 0247_ $$2WOS$$aWOS:001240580700001 001026448 037__ $$aFZJ-2024-03397 001026448 082__ $$a540 001026448 1001_ $$0P:(DE-Juel1)190784$$aAli, Haider Adel$$b0$$eFirst author 001026448 245__ $$aA comparison between physics-based Li-ion battery models 001026448 260__ $$aNew York, NY [u.a.]$$bElsevier$$c2024 001026448 3367_ $$2DRIVER$$aarticle 001026448 3367_ $$2DataCite$$aOutput Types/Journal article 001026448 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1719814552_15364 001026448 3367_ $$2BibTeX$$aARTICLE 001026448 3367_ $$2ORCID$$aJOURNAL_ARTICLE 001026448 3367_ $$00$$2EndNote$$aJournal Article 001026448 520__ $$aPhysics-based electrochemical battery models, such as the Doyle-Fuller-Newman (DFN) model, are valuable tools for simulating Li-ion battery behavior and understanding internal battery processes. However, the complexity and computational demands of such models limit their applicability for battery management systems and long-term aging simulations. Reduced-order models (ROMs), such as the Extended Single Particle Model (ESPM), Single Particle Model (SPM) and Polynomial and Padé approximations, here all referred to as simplifications, lead to faster computational speeds. Choosing the appropriate simplification method for a specific cell type and operating condition is a challenge. This study investigates the simulation accuracy and calculation speed of various simplifications for high-energy (HE) and high-power (HP) batteries at different current loading conditions and compares those to the full-order DFN model. The results indicate that among the ROMs, the ESPM consistently offers the best combination of high computational speed and relatively good accuracy in most conditions in comparison to the full-order DFN model. Among the approximations, higher-order polynomial approximation, third and fourth-order Padé approximation perform the best in terms of accuracy. The higher-order polynomial approximation shows an advantage in terms of computing speed, while the fourth-order Padé approximation achieves the highest overall accuracy among the different approximations. 001026448 536__ $$0G:(DE-HGF)POF4-1223$$a1223 - Batteries in Application (POF4-122)$$cPOF4-122$$fPOF IV$$x0 001026448 536__ $$0G:(DE-Juel1)BMBF-03SF0628$$aLLEC::VxG - Integration von "Vehicle-to-grid" (BMBF-03SF0628)$$cBMBF-03SF0628$$x1 001026448 536__ $$0G:(BMBF)13XP0530B$$aBMBF 13XP0530B - ALIBES: Aluminium-Ionen Batterie für Stationäre Energiespeicher (13XP0530B)$$c13XP0530B$$x2 001026448 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de 001026448 7001_ $$0P:(DE-Juel1)176196$$aRaijmakers, Luc$$b1$$eCorresponding author 001026448 7001_ $$0P:(DE-Juel1)186070$$aChayambuka, Kudakwashe$$b2 001026448 7001_ $$0P:(DE-Juel1)173719$$aDanilov, Dmitri$$b3 001026448 7001_ $$0P:(DE-Juel1)165918$$aNotten, Peter H. 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