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Titel:

CFP2022-1140

Modelling inhomogeneous degradation in lithium-ion batteries: the effect of thermal gradients
Lecture
Pack design & thermal management
Lifetime

Abstract
Understanding degradation is critical to unlock the true potential of lithium-ion batteries. Poorly understood degradation leads to reduced energy/power density through over-engineering, and increased safety risks and failure rates. Thermal management is key to minimizing battery degradation. Yet, previous experimental results have shown the effect of different thermal management strategies on degradation is still not fully understood.
In this work a 3 dimensional distributed electrical-thermal model including inho-mogeneous degradation is used to explore the effects of thermal gradients on degrada-tion for the first time. An equivalent circuit network (ECN) model (as shown in Fig. 1(a)) is used which can simulate thousands of cycles per day on a normal desktop computer. The model is capable of reproducing previously published experimental data showing differences in the rate of degradation when surface cooling compared to tab cooling for pouch cells (results shown in Fig. 1(b-c)). The model shows that there is significant positive feedback which significantly accelerates battery degradation, if there are significant thermal gradients within the active region of the cell, and if the dominant degradation mechanism is a function of current in addition to temperature. Most cells suffer from internal thermal gradients during operation, and many degradation mecha-nisms are a function of current, suggesting these effects cannot and should not be ig-nored, and lumped models will have a high risk of significant underfitting. The findings should be of immediate interest to anyone attempting to model degradation in lithi-um-ion batteries, in addition to cell and battery pack designers.
Keywords: Lithium-ion battery; Non-uniform degradation; Thermal management; Elec-tro-thermal-degradation model

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Autor

Unternehmen/Institut

Co-Autoren

Cheng Zhang, Yan Zhao, Gregory J. Offer and Monica Marinescu

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