Conference
Energy Consumption Uncertainty Model For Battery-Electric Buses in Transit
Abstract
This study develops a Deep Learning Neural Network (DLNN) model to predict the consumed energy (EC) of Battery Electric Buses (BEBs) based on bus, route, driver aggressiveness, and environmental parameters. An ADVISOR simulation tool is utilized to estimate EC for 10,800 operation scenarios resulted from a fractional-factorial design. The scenarios are used in a DLNN model with a goodness-of-fit of 0.993. The results show that road gradient …
Authors
Abdelaty H; Mohamed M
Volume
00
Pagination
pp. 1-5
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
June 25, 2021
DOI
10.1109/itec51675.2021.9490103
Name of conference
2021 IEEE Transportation Electrification Conference & Expo (ITEC)