001053944 001__ 1053944
001053944 005__ 20260206202203.0
001053944 037__ $$aFZJ-2026-01621
001053944 041__ $$aEnglish
001053944 1001_ $$0P:(DE-Juel1)190784$$aAli, Haider Adel$$b0$$ufzj
001053944 245__ $$aPhysics-based Electrochemical Modelling of Li-ion Batteries$$f - 2026-01-28
001053944 260__ $$c2026
001053944 300__ $$a162
001053944 3367_ $$2DataCite$$aOutput Types/Dissertation
001053944 3367_ $$2ORCID$$aDISSERTATION
001053944 3367_ $$2BibTeX$$aPHDTHESIS
001053944 3367_ $$02$$2EndNote$$aThesis
001053944 3367_ $$0PUB:(DE-HGF)11$$2PUB:(DE-HGF)$$aDissertation / PhD Thesis$$bphd$$mphd$$s1770375253_9946
001053944 3367_ $$2DRIVER$$adoctoralThesis
001053944 502__ $$aDissertation, RWTH Aachen, 2026$$bDissertation$$cRWTH Aachen$$d2026$$o2026-01-28
001053944 520__ $$aPhysics-based battery models with the Doyle-Fuller-Newman (DFN) model has been regarding as the very powerful model to simulate the Li-ion batteries behaviour with good accuracy. However, the high computational demand and parameterization are the two main challenges have been the main obstacle for the model have limited it use in applications. In this thesis, a comparison of various simplifications of the DFN model has been conducted to compared to improve the simulation speed while maintaining good accuracy, the thesis also propose a guideline on how the select the optimum model simplification. Furthermore, in this thesis, the multiple-particle DFN (MP-DFN) model is introduced, which incorporates particle size distributions for improving simulation accuracy while maintaining low computational demand.A full parameterization framework have been developed, including full cell teardown. In addition, comparison and analysis are introduced on how to determine the solid-phase diffusion coefficient (D_"s" ) and the reaction-rate constant (k_"0" ). The result shows that the combination of the galvanostatic intermittent titration techniques (GITT) combined with DFN model is the most accuracy approach. Furthermore, a parameterization of the cell without cell tear-down is conducted by collecting data from the electric vehicles, while charging and driving. The combination of sensitivity analysis and optimization shows that RMSE below 8 mV is achieved.Finally, simulation are conducted to improve the charging speed in the EV, compared with conventional constant current-constant voltage (CC-CV) protocol. A control-based charging protocol that employs physics-based models proposed in the thesis, demonstrates a 32 % faster charging speed compared to the standard CC-CV protocol from a state of charge (SoC) of 5 % to 80 %, while keeping the anode potential within safe limits to prevent Li-plating
001053944 536__ $$0G:(DE-HGF)POF4-1223$$a1223 - Batteries in Application (POF4-122)$$cPOF4-122$$fPOF IV$$x0
001053944 536__ $$0G:(DE-Juel1)HITEC-20170406$$aHITEC - Helmholtz Interdisciplinary Doctoral Training in Energy and Climate Research (HITEC) (HITEC-20170406)$$cHITEC-20170406$$x1
001053944 909CO $$ooai:juser.fz-juelich.de:1053944$$pVDB
001053944 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)190784$$aForschungszentrum Jülich$$b0$$kFZJ
001053944 9101_ $$0I:(DE-588b)36225-6$$6P:(DE-Juel1)190784$$aRWTH Aachen$$b0$$kRWTH
001053944 9131_ $$0G:(DE-HGF)POF4-122$$1G:(DE-HGF)POF4-120$$2G:(DE-HGF)POF4-100$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-1223$$aDE-HGF$$bForschungsbereich Energie$$lMaterialien und Technologien für die Energiewende (MTET)$$vElektrochemische Energiespeicherung$$x0
001053944 9141_ $$y2026
001053944 920__ $$lyes
001053944 9201_ $$0I:(DE-Juel1)IET-1-20110218$$kIET-1$$lGrundlagen der Elektrochemie$$x0
001053944 980__ $$aphd
001053944 980__ $$aVDB
001053944 980__ $$aI:(DE-Juel1)IET-1-20110218
001053944 980__ $$aUNRESTRICTED