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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Thiede, Sebastian
University of Twente
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (12/12 displayed)
- 2022Integration of Energy Oriented Manufacturing Simulation into the Life Cycle Evaluation of Lightweight Body Partscitations
- 2021Machine learning and simulation-based surrogate modeling for improved process chain operationcitations
- 2021Modeling energy and resource use in additive manufacturing of automotive series parts with multi-jet fusion and selective laser sinteringcitations
- 2020Modeling the Impact of Manufacturing Uncertainties on Lithium-Ion Batteriescitations
- 2020Industrie 4.0 in der Galvanotechnik
- 2020Root Cause Analysis in Lithium-Ion Battery Production with FMEA-Based Large-Scale Bayesian Network
- 2020Integrated computational product and production engineering for multi-material lightweight structurescitations
- 2020Agent-Based Simulation Approach for Occupational Safety and Health Planningcitations
- 2020Model-based analysis, control and dosing of electroplating electrolytescitations
- 2019Modelling the Impact of Manufacturing Uncertainties on Lithium-Ion Batteriescitations
- 2012A hierarchical evaluation scheme for industrial process chainscitations
- 2011Synergies from process and energy oriented process chain simulation - A case study from the aluminium die casting industrycitations
Places of action
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article
Modeling the Impact of Manufacturing Uncertainties on Lithium-Ion Batteries
Abstract
This paper describes and analyzes the propagation of uncertainties from the lithium-ion battery electrode manufacturing process to the structural electrode parameters and the resulting varying electrochemical performance. It uses a multi-level model approach, consisting of a process chain simulation and a battery cell simulation. The approach enables to analyze the influence of tolerances in the manufacturing process on the process parameters and to study the process-structure-property relationship. The impact of uncertainties and their propagation and effect is illustrated by a case study with four plausible manufacturing scenarios. The results of the case study reveal that uncertainties in the coating process lead to high deviations in the thickness and mass loading from nominal values. In contrast, uncertainties in the calendering process lead to broad distributions of porosity. Deviations of the thickness and mass loading have the highest impact on the performance. The energy density is less sensitive against porosity and tortuosity as the performance is limited by theoretical capacity. The latter is impacted only by mass loading. Furthermore, it is shown that the shape of the distribution of the electrochemical performance due to parameter variation aids to identify, whether the mean manufacturing parameters are close to an overall performance optimum.