Experimental and Simulation-Based Characterization of Thermal Runaway in Lithium-Ion Batteries Using Altair SimLab®

热失控 锂(药物) 表征(材料科学) 热的 离子 材料科学 航空航天工程 核工程 物理 纳米技术 工程类 电池(电) 热力学 功率(物理) 内分泌学 量子力学 医学
作者
Luca Giuliano,Luigi Scrimieri,Simone Reitano,Davide Berti Polato,Alessandro Ferraris,Andrew Comerford,Saakaar Bhatnagar
出处
期刊:SAE technical paper series 卷期号:1
标识
DOI:10.4271/2025-01-8146
摘要

<div class="section abstract"><div class="htmlview paragraph">Thermal runaway is a critical phenomenon in lithium batteries, characterized by a self-sustaining process due to internal chemical reactions, that is triggered once a certain temperature is reached within the cell. This event is often caused by overheating due to charge and discharge cycles and can lead to fires or explosions, posing a significant safety threat. The aim of this study is to induce thermal runaway on single cells in different ways to characterize the phenomenon and validate the simulation models present in Altair SimLab®.</div><div class="htmlview paragraph">The work was conducted in several key phases. Initially, an experimental test was performed in a calorimeter (EV ARC HWS test) to collect temperature data of the Molicel 21700 P45B cell during thermal runaway under adiabatic conditions. These data were used for a simulation on a single cell, allowing a detailed comparison with the experimental results. Subsequently, a test was conducted on a single cell under operational conditions, overheated using a heat pad powered at a constant power (non-adiabatic conditions), with temperature monitoring through three thermocouples placed on the cell. For this scenario as well, a simulation was performed on a single cell, replicating the effect of the heat pad with a heat source on the surface.</div><div class="htmlview paragraph">This work, carried out in collaboration between Altair Inc and BeonD S.r.l, demonstrates that accurate simulation of thermal runaway allows the prediction of the phenomenon's onset based on the operational conditions of the battery pack. Such predictions are crucial for designing more effective thermal management systems and improving the safety and reliability of lithium batteries.</div></div>
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