Transitioning Transit : Modeling the Electrification of an Intracity Bus System
Name
sreenath-ragini06-sm-tpp-2022.pdf
Description
Thesis PDF
Size
5 MB
Format
Adobe PDF
Checksum (MD5)
e4e61a786b03bc200fda8723044bac83
Author(s)
Sreenath, Ragini
Advisor(s)
Gençer, Emre
Date Issued
February 2022
Publisher
Massachusetts Institute of Technology
Abstract
In the past few years, there has been a significant push towards the electrification of transportation as an important climate change mitigation strategy, especially given that transportation contributes to over 15 % of greenhouse gas emissions. While a lot of the present research is focused around the electrification of the private vehicle fleet, another segment of transportation that merits attention is public transit. In many developing countries, public transit buses while being a popular mode of commute, are also hugely responsible for air pollution. This includes particulate matter pollution that poses very significant health risks. However, there are challenges that limit the adoption of electric buses, including limited driving range, high battery costs and most importantly, developing charging infrastructure best suited to meet travel needs. This thesis seeks to begin addressing these challenges by developing a transit bus electrification model that can calculate the energy needs of a city bus system with minimal operational data and uses the network properties of the system to identify an optimal cost solution for operating an electric bus fleet. It also seeks to understand the factors that drive this transition. The model is applied to the city of Delhi’s transportation system, which further highlights the importance of making route-specific decisions when transitioning to electric buses. The model developed in this thesis may enable policymakers and transit authorities to make informed, data-driven decisions, as they proceed to electrify their public transportation systems.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
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