Data-Driven Safety Envelope of Lithium-Ion Batteries for Electric Vehicles
Data-Driven Safety Envelope of Lithium-Ion Batteries for Electric Vehicles
复制标题
电动汽车锂离子电池的数据驱动安全范围
DOI：
10.1016/j.joule.2019.07.026
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发表时间：
2019-11-20
期刊：
影响因子：
39.8
通讯作者：
Wierzbicki, Tomasz
中科院分区：
文献类型：
--
作者：
Li, Wei;Zhu, Juner;Wierzbicki, Tomasz
在电动汽车的事故场景中，电池组可能会发生灾难性的损坏，导致电气短路，热失控，并可能发生火灾和爆炸。因此，重要的是要调查的条件范围下，每个单独的电池的安全运行得到充分控制，被称为“安全信封”的最大挑战，开发这样的安全信封在于获取一个大型数据库的电池故障测试。在这项研究中，我们克服了这一挑战，建立了一个高精度的详细计算模型的锂离子袋电池，其中所有的组成材料的特点是校准良好的本构模型。模拟一个大型矩阵的极端机械载荷条件，并使用机器学习算法获得数据驱动的安全包络线。这项工作是将数值数据生成与数据驱动建模相结合来预测储能系统安全性的示范。
In the accident scenarios of electric vehicles, the battery pack can be damaged catastrophically, resulting in the electric short circuit, thermal runaway, and possible fire and explosion. Therefore, it is important to investigate the range of conditions under which the safe operation of each individual cell is adequately controlled, known as the "safety envelope" The biggest challenge of developing such a safety envelope lies in the acquisition of a large data bank of battery failure tests. In this study, we overcome the challenge by establishing a high-accuracy detailed computational model of lithium-ion pouch cells, in which all the component materials are characterized by well-calibrated constitutive models. A large matrix of extreme mechanical loading conditions is simulated, and a data-driven safety envelope is obtained using the machine learning algorithm. This work is a demonstration of combining numerical data generation with data-driven modeling to predict the safety of energy storage systems.