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Thermal Modeling of Large Format Prismatic Lithium-Ion Cell A Comparative Study Mahindra University
- Format:
- Book
- Conference/Event
- Author/Creator:
- M, Abhishek, author.
- Conference Name:
- 11th SAEINDIA International Mobility Conference (SIIMC 2024) (2024-12-11 : New Delhi, India)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2024
- Summary:
- Lithium-ion batteries are one of the prominent energy storage devices that can store electrical energy in the form of chemical energy and release it as required. During their operation, Lithium-ion batteries generate heat that needs to be removed to ensure their optimum performance and safety. A prior knowledge of heat generation rates can help design efficient thermal management systems. Numerical models are quite successful in estimating the heat generation inside Lithium-ion cells. In the present study, a computational fluid dynamics (CFD) model is developed to estimate the heat generation and temperature distribution within a 30 Ah Prismatic Lithium-ion cell using two modelling approaches namely, the Newman, Tiedemann, Gu, and Kim (NTGK) model and the Pseudo 2-Dimensional (P2D) model. The NTGK model, known for its robust representation of electrochemical and thermal aspects is evaluated against the P2D model while providing a detailed explanation of the battery's internal states and interactions. Both models are implemented to simulate the thermal behavior under varying operating conditions such as different discharge rates (2C, 5C) at Tamb=25°C, and coolant flow (natural and forced convection). The results indicate that the computationally less intensive NTGK model provides a reasonable approximation of temperature distribution and thermal gradients, making it suitable for real-time applications and large-scale simulations. Conversely, the computationally expensive P2D model offers more precise insights into the internal thermal and potential hotspots, necessary for advanced design and optimization. This comparative analysis highlights the tradeoff between model complexity and accuracy associated with these modelling approaches and guides towards the selection of appropriate thermal management strategies for battery cooling applications
- Notes:
- Vendor supplied data
- Publisher Number:
- 2024-28-0144
- Access Restriction:
- Restricted for use by site license
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