Prediction of Hybrid Electric Bus Speed Using Deep Learning Method

2020-01-1187

04/14/2020

Authors
Abstract
Content
The recent development pace of the automotive technology is so rapid worldwide. Especially in a green car, hybrid electric vehicles (HEVs) have been studied a lot due to their significant effects on the urban driving. In the vehicle energy management strategy study, the driving speed is assumed to be known in advance, however the speed is not given in a real world. Accordingly, the prediction of vehicle speed is very important. In this study, we study the prediction methodology for the speed prediction using deep learning. Based on the vehicle driving speed data, the supervised deep learning has been used and the speed prediction accuracy using deep learning shows accurate results comparing to the actual speed. The supervised deep learning is used which is suitable for driving cycle database. As a result, the speed prediction after few seconds is feasible.
Meta TagsDetails
DOI
https://doi.org/10.4271/2020-01-1187
Pages
5
Citation
Hwang, G., Lee, S., Min, K., Park, J. et al., "Prediction of Hybrid Electric Bus Speed Using Deep Learning Method," SAE Technical Paper 2020-01-1187, 2020, https://doi.org/10.4271/2020-01-1187.
Additional Details
Publisher
Published
Apr 14, 2020
Product Code
2020-01-1187
Content Type
Technical Paper
Language
English