Title

When to go electric? A parallel bus fleet replacement study

Document Type

Journal Article

Publication Date

2019

Subject Area

place - north america, mode - bus, technology - alternative fuels, technology - emissions, infrastructure - fleet management, infrastructure - vehicle

Keywords

Parallel fleet replacement, Optimization, Mixed-integer program, GHG emission, Transit Bus

Abstract

United States in 2017 emitted about 14.36% of the total global Greenhouse Gas (GHG), 27% of which comes from the transportation sector. In order to address some of these emission sources, alternative fuel technology vehicles are becoming more progressive and market ready. Transit agencies are making an effort to reduce their carbon footprint by adopting these technologies. The overarching objective of this paper is to aid transit agencies make more informed decisions regarding the process of replacing a diesel fleet with alternative-technology buses to minimize GHG emissions. This study investigates the complete course of fleet replacement using a deterministic mixed integer programming. Bus fleet replacement is optimized by minimizing the Life Cycle Cost (LCC) of owning and operating a fleet of buses and required infrastructures while reducing GHG emission simultaneously. Buses operated by Connecticut Department of Transportation (CTDOT) were used as a case-study. Results also show a significant reduction in both cost and emission for optimized replacement schedule vs the unoptimized one. Results also show that a fleet consisting of 79% Battery Electric Bus and 21% Diesel Hybrid Bus yields the least cost solution which conforms to the other operational and environmental constraints. This study also includes various sensitivity tests, that illustrates that although the magnitude of the results may vary depending on the input data, the direction remains the same. The problem formulated in this study can help any transit agencies determine the most optimized solution to their fleet replacement problem under customizable constraints or desired set of outcomes.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Transportation Research Part D Home Page:

http://www.sciencedirect.com/science/journal/13619209

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