Data Analysis, Modeling, and Predictability of Automotive Events

2018-01-0094

04/03/2018

Features
Event
WCX World Congress Experience
Authors Abstract
Content
It is important to quantitatively characterize the automotive events in order to not only accurately interpret their past but also to reliably predict and forecast their short-term, medium-term, and even long-term future. In this paper, several automotive industry related events, i.e. vehicle safety, vehicle weight/HP ratio, the emissions of CO2, HC, CO, and NOx, are analyzed to find their general trends. Exponential and power law functions are used to empirically fit and quantitatively characterize these data with an emphasis on the two functions’ effectiveness in predictability. Finally, three empirical emission laws based on the historical HC, CO, and NOx data are proposed and the impact of these laws on emission control is discussed.
Meta TagsDetails
DOI
https://doi.org/10.4271/2018-01-0094
Pages
9
Citation
Wei, Z., Luo, L., and Kotrba, A., "Data Analysis, Modeling, and Predictability of Automotive Events," SAE Technical Paper 2018-01-0094, 2018, https://doi.org/10.4271/2018-01-0094.
Additional Details
Publisher
Published
Apr 3, 2018
Product Code
2018-01-0094
Content Type
Technical Paper
Language
English