A simplified approach to modelling temperature rises in battery cells and modules
A simplified approach to modelling temperature rises in battery cells and modules
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DOI：
10.1016/j.applthermaleng.2022.118357
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发表时间：
2022-03
影响因子：
6.4
通讯作者：
C. Rouge;D. Carolan;A. Fergusson
中科院分区：
文献类型：
--
作者：
C. Rouge;D. Carolan;A. Fergusson
建立了一个分析模型来预测电池单元或组件在一定冷却制度下的最大温升。这种新的分析模型结合了细观力学模型来计算电池的有效导热系数，并求解了热方程。边界条件、几何参数和材料性质在典型范围内变化。在稳态条件下，对各种配置的电池温度场进行了预测，分析模型与数值模拟结果吻合很好。该解析解可作为一种快速、可靠的工具来估算电池与其热管理系统之间的热传递。将分析模型的结果与人工神经网络估计的结果进行比较，发现其性能与数据驱动方法相同或更好。对解析预测的感兴趣温度进行了实验验证，显示出非常好的一致性。实验结果揭示了从高效能量转换的角度对良好的热管理解决方案的需求。
An analytical model to predict the maximum temperature rise in a battery cell or module given a certain cooling regime was developed. The novel analytical model combines a micromechanical model, to compute the effective thermal conductivity of the cells, with a solution of the heat equation. The boundary conditions, geometric parameters and material properties were varied in representative ranges. The temperature fields across the battery were predicted with a very good agreement between the analytical model and the numerical simulations, for a wide variety of configurations under steady-state conditions. The analytical solution can be used as a fast and reliable tool to estimate the heat transfer between the cells and their thermal management system. The results from the analytical model were compared to those estimated by an Artificial Neural Network and found to be equal or better in performance than a data-driven approach. An experimental validation of the analytically predicted temperatures of interest showed a very good agreement. The experimental results reveal the requirement for good thermal management solutions from an efficient energy conversion point of view.