Discovering Effective Factors for Big Data-Based Fuel Cell Durability

2022-01-0684

03/29/2022

Features
Event
WCX SAE World Congress Experience
Authors Abstract
Content
As data emerges as the most valuable resource in the world, the evolution of the related data industry is progressing faster. In this study, we tried to discover effective factors for fuel cell durability by using big data analysis techniques with accumulated vehicle actual road data (de-identified Blue Link Data). Basic analysis is performed assuming factors that are expected to have a significant impact on the fuel cell durability performance, and durability factor modeling according to the clustering between driving patterns and durability performance is used to determine. Now can see the change in durability performance. By analyzing the correlation between each driving pattern and durability performance, it is possible to know the weight of the effective factor affecting the durability. If the effective factor with high weight is improved in the actual vehicle unit, the durability performance is expected to increase, and the effect will be verified through real road operation.
Meta TagsDetails
DOI
https://doi.org/10.4271/2022-01-0684
Pages
8
Citation
Jin, Y., "Discovering Effective Factors for Big Data-Based Fuel Cell Durability," SAE Technical Paper 2022-01-0684, 2022, https://doi.org/10.4271/2022-01-0684.
Additional Details
Publisher
Published
Mar 29, 2022
Product Code
2022-01-0684
Content Type
Technical Paper
Language
English