Time‐dependent global sensitivity analysis with active subspaces for a lithium ion battery model

Statistical Analysis and Data Mining

Constantine, Paul G.¹  Doostan, Alireza² 

[1] University of Colorado Department of Computer Science Boulder Colorado;University of Colorado Smead Aerospace Engineering Sciences Department Boulder Colorado

关键词: computer experiments;    sufficient dimension reduction;    uncertainty quantification;   

DOI  :  10.1002/sam.11347

学科分类：社会科学、人文和艺术（综合）

来源: John Wiley & Sons, Inc.

【 摘 要 】

Renewable energy researchers use computer simulation to aid the design of lithium ion storage devices. The underlying models contain several physical input parameters that affect model predictions. Effective design and analysis must understand the sensitivity of model predictions to changes in model parameters, but global sensitivity analyses become increasingly challenging as the number of input parameters increases. Active subspaces are part of an emerging set of tools for discovering and exploiting low-dimensional structures in the map from high-dimensional inputs to model outputs. We extend linear and quadratic model-based heuristics for active subspace discovery to time-dependent processes and apply the resulting technique to a lithium ion battery model. The results reveal low-dimensional structure and sensitivity metrics that a designer may exploit to study the relationship between parameters and predictions.

【 授权许可】

Unknown