Publication | Open Access
Digitalization Platform for Sustainable Battery Cell Production: Coupling of Process, Production, and Product Models
13
Citations
66
References
2022
Year
EngineeringEnergy ConversionHome Energy StorageDigitalization PlatformAdvanced Energy TechnologyParameter InterdependenciesSustainable TechnologyMaterials ScienceElectrical EngineeringBattery Electrode MaterialsProduct ModelsLithium-ion BatteriesMechanical BatteriesLithium-ion BatteryEnergy StorageSolid-state BatteryElectrochemistryElectric BatteryEnergy ManagementSustainable EnergyLi-ion Battery MaterialsBattery ConfigurationElectrochemical Energy StorageBatteriesAnode MaterialsTechnologyCoating SuspensionSustainable Production
Lithium‐ion batteries are used in a wide range of applications, with the electromobility sector being the main contributor to the increasing demand predicted for the next decade. Although batteries play an important role in decarbonizing the transportation sector, their production includes energy‐intensive processes that hinder a more sustainable production. Moreover, the production processes are characterized by a manifold of parameters leading to complex cause–effect relations along the process chain which influences the battery cell quality. Therefore, a sustainable future for battery production and the electromobility sector depends on the environmentally and economically efficient production of high‐performance batteries. Against this background, this work presents a digitalization platform based on the coupling of mechanistic models to digitally reproduce the battery cell production and provide a deeper understanding of the interdependencies on the process, production, and product levels. In addition to a description of the individual models contained in the platform, this work demonstrates their coupling on a use case to study the effects of different solids contents of the coating suspension. Besides providing a multilevel assessment of the parameter interdependencies, considering quality, environmental and economic aspects, the presented framework contributes to knowledge‐based decision support and improvement of production and battery cell performance.
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