基于Kriging响应面法的电动汽车电池组结构响应预测与质量优化研究

Deepak Sreedhar Kanakandath, Sankha Subhra Jana, Arunkumar Ramakrishnan
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引用次数: 0

摘要

电动汽车电池组在道路荷载作用下的结构响应是决定其正常运行性能和寿命的重要因素。本文利用试验设计(DOE)运行数据集建立了kriging响应面模型,用于预测电池组的结构响应和整体模态频率指标。利用该响应面模型(RSM),我们可以快速优化电池组的结构响应设计,并实现显著的质量降低。该方法减少了电池组设计初期设计优化的周转时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Using Kriging Response Surface Method for EV Battery Pack Structural Response Prediction and Mass Optimization
Structural response of battery packs in electric vehicles when subjected to road loads is an important factor that decides its performance and life during normal operation. In this paper a kriging response surface model is built using a Design of Experiment (DOE) run dataset to predict structural response and global modal frequency metrics of the battery pack. Using this Response Surface Model (RSM), we can rapidly optimize the battery pack design with respect to structural response and achieve significant mass reduction. This method reduces turnaround times for design optimization in early stages of battery pack design.
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