Design and validation of a CFD model for energy-efficient Ni-Co-Mn cathode calcination process
This study describes the development and validation of a computational fluid dynamics model for calcination of lithium-ion battery cathode materials within a roller hearth kiln. The primary objective is to quantitatively predict and optimize energy consumption in high-temperature solid-state synthes...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-10-01
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| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25011414 |
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| Summary: | This study describes the development and validation of a computational fluid dynamics model for calcination of lithium-ion battery cathode materials within a roller hearth kiln. The primary objective is to quantitatively predict and optimize energy consumption in high-temperature solid-state synthesis processes. The model incorporates three essential sub-models to reflect complex physical and chemical phenomena during calcination: a heater control algorithm replicating nonlinear thermal response of industrial heaters with less than five percent deviation from experimental measurements, a data transfer method effectively simulating continuous material movement without computational mesh deformation to maintain numerical stability, and a dehydration reaction kinetics model addressing significant endothermic behavior arising from lithium hydroxide precursors during thermal treatment. Validation demonstrates strong agreement between simulation results and experimental observations, confirming accurate representation of coupled heat transfer, material transport, and chemical reaction phenomena occurring simultaneously. The proposed approach provides precise control over internal thermal conditions and heat flow dynamics, establishing a reliable computational platform for enhancing energy efficiency and ensuring uniform calcination quality in cathode material production. This method contributes valuable insights into sustainable process design and optimization and has potential applicability for real-time process control in industrial-scale manufacturing environments. |
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| ISSN: | 2214-157X |