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Physics-Based Thermal Degradation Modelling of Lithium-Ion Batteries

基于物理的锂离子电池热降解建模

基本信息

批准号：
2490791
负责人：
金额：
--
依托单位：
Newcastle University
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2490791
关键词：
Physics Based Thermal Degradation Modelling

项目摘要

Lithium ion Battery (LiB) modelling has come a long way since its early days yet more work needs to be done. The regular operating principles of a fresh LiB are quite well understood, however, the same cannot be said about the modelling of aged cells. Some models have been developed in recent years to predict the degradation of LiB's, many of which empirical and hence have a very limited applicability range.It is not well understood how the LiB will behave in a 2nd life application as the battery goes through many complex processes over its lifetime which will fundamentally change its operating principles. For example, if the battery is charged with a 1C rate when it is new, the temperature difference over its surface might only be a few degrees, later, once the battery was used for some time, this temperature gradient will change due to the formation and break down of certain materials in the battery. This change in expected operating temperature might lead to formation of new compounds which may not have formed in the normal temperature range or uneven degradation which can cause a variety of other problems.My research will focus on modelling not just the standard operating behaviour of a LiB but also how the battery degrades. Another pressing issue for people who want to work with 2nd life LiB's is knowing what state it is at. In order to understand the state of a LiB many tests must be carried out to measure such lumped parameters as state of charge (SoC), internal impedance, available capacity and so on. The problem here is that the parameters are lumped and these measurements cannot yield distributed parameters which are crucial to the understanding of degradation as mentioned above. A promising alternative to this is thermal imaging. It may be possible to correlate the state of the battery by running a current through the battery and measuring the corresponding temperature profiles.This research can aid in better understanding of how lithium-ion batteries degrade, yield simpler ways to determine if a battery is usable in 2nd life applications and for how long as well as assist in developing more rapid charging methods for Electric vehicles (EV's) since currently, fast charging can causes significantly accelerated degradation of EV batteries.Considering all of the above, the main objectives for my project are:* Study lithium-ion batteries and understand the fundamentals* Develop Physics based thermal degradation model of a lithium-ion battery cell* Investigate 2nd life behaviour of a lithium-ion battery* Investigate fast charging and thermal degradation impact* Investigate how different geometry batteries degrade, e.g. pouch/cylindrical cells

锂离子电池 (LiB) 建模自早期以来已经取得了长足的进步，但还需要做更多的工作。新鲜锂电池的常规工作原理已广为人知，但对于老化电池的建模却并非如此。近年来开发了一些模型来预测锂电池的退化，其中许多模型是经验性的，因此适用范围非常有限。目前还不清楚锂电池在第二次寿命应用中的表现，因为电池在其使用寿命期间会经历许多复杂的过程，这将从根本上改变其工作原理。例如，如果电池在新的时候以1C的速率充电，其表面的温差可能只有几度，而当电池使用一段时间后，这个温度梯度会因为电池中某些材料的形成和分解而发生变化。预期工作温度的这种变化可能会导致在正常温度范围内可能不会形成的新化合物的形成，或者不均匀的降解，从而导致各种其他问题。我的研究不仅集中于对锂电池的标准操作行为进行建模，还集中于对电池如何降解进行建模。对于想要使用第二生命 LiB 的人来说，另一个紧迫的问题是了解它处于什么状态。为了了解 LiB 的状态，必须进行许多测试来测量充电状态 (SoC)、内部阻抗、可用容量等集总参数。这里的问题是参数是集中的，这些测量不能产生分布式参数，而分布式参数对于理解如上所述的退化至关重要。热成像是一个有前途的替代方案。通过在电池中流过电流并测量相应的温度曲线，可以将电池的状态关联起来。这项研究可以帮助更好地了解锂离子电池如何退化，提供更简单的方法来确定电池在第二次寿命应用中是否可用以及可以使用多长时间，并协助开发更快速的电动汽车（EV）充电方法，因为目前快速充电会导致电动汽车的退化显着加速考虑到上述所有因素，我的项目的主要目标是：* 研究锂离子电池并了解基本原理* 开发基于物理的锂离子电池热降解模型* 研究锂离子电池的第二次寿命行为* 研究快速充电和热降解影响* 研究不同几何形状的电池如何降解，例如袋状/圆柱形电池