电池(电)
灵敏度(控制系统)
锂(药物)
计算机科学
电解质
锂离子电池
估计理论
相关性(法律)
算法
化学
电极
电子工程
物理
热力学
功率(物理)
工程类
内分泌学
物理化学
法学
医学
政治学
作者
Thomas Grandjean,Liuying Li,Maria Ximena Odio,Widanalage Dhammika Widanage
标识
DOI:10.1109/vppc46532.2019.8952455
摘要
The importance of global sensitivity analysis (GSA) has been well established in many scientific areas. However, despite its critical role in evaluating a model's plausibility and relevance, most lithium ion battery models are published without any sensitivity analysis. In order to improve the lifetime performance of battery packs, researchers are investigating the application of physics based electrochemical models, such as the single particle model with electrolyte (SPMe). This is a challenging research area from both the parameter estimation and modelling perspective. One key challenge is the number of unknown parameters: the SPMe contains 31 parameters, many of which are themselves non-linear functions of other parameters. As such, relatively few authors have tackled this parameter estimation problem. This is exacerbated because there are no GSAs of the SPMe which have been published previously. This article addresses this gap in the literature and identifies the most sensitive parameter, preventing time being wasted on refining parameters which the output is insensitive to.
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