报告人:林学磊
报告地点:腾讯会议ID:810-9813-0565
报告时间:2026年04月21日星期二16:00-16:45
邀请人:吴树林
报告摘要:
Predicting lithium-ion battery degradation is worth billions to the global automotive, aviation and energy storage industries, to improve performance and safety and reduce warranty liabilities. However, very few published models of battery degradation explicitly consider the interactions between more than two degradation mechanisms, and none do so within a single electrode. In this paper, the first published attempt to directly couple more than two degradation mechanisms in the negative electrode is reported. The results are used to map different pathways through the complicated path dependent and non-linear degradation space. Four degradation mechanisms are coupled in PyBaMM, an open source modelling environment uniquely developed to allow new physics to be implemented and explored quickly and easily. Crucially it is possible to see ‘inside the model and observe the consequences of the different patterns of degradation, such as loss of lithium inventory and loss of active material. For the same cell, five different pathways that can result in end-of-life have already been found, depending on how the cell is used. Such information would enable a product designer to either extend life or predict life based upon the usage pattern. However, parameterization of the degradation models remains as a major challenge, and requires the attention of the international battery community.
主讲人简介:
林学磊,哈尔滨工业大学(深圳)副教授、主要从事数值线性代数方面的研究,包括偏微分方程数值解,结构线性系统的快速迭代法。已在 SIAM J. Matrix Anal. Appl., SIAM J. Sci. Comput., BIT., SIAM J. Numer. Anal., J. Comput. Phys., 等刊物以第一作者/通讯身份发表论文20余篇;担任美国《数学评论》评论员,多个期刊审稿人;主持国家级研究项目2项,省部级项目1项,市级项目1项;曾在“第九届世界华人数学家大会“上,获博士论文奖;在“第14届东亚工业与应用数学学会年会”上获得学生论文奖。