Access Type

Open Access Dissertation

Date of Award

January 2020

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Industrial and Manufacturing Engineering

First Advisor

Saravanan Venkatachalam

Abstract

Logistic and transportation (L&T) activities become a significant contributor to social and economic advances throughout the modern world Road L&T activities are responsible for a large percentage of CO2 emissions, with more than 24% of the total emission, which mostly caused by fossil fuel vehicles. Researchers, governments, and automotive companies put extensive effort to incorporate new solutions and innovations into the L&T system. As a result, Electric Vehicles (EVs) are introduced and universally accepted as one of the solutions to environmental issues. Subsequently, L&T companies are encouraged to adopt fleets of EVs. Integrating the EVs into the logistic and transportation systems introduces new challenges from strategic, planning, and operational perspectives.

At the strategical level, one of the main challenges to be addressed to expand the EV charging infrastructures is the location of charging stations. Due to the longer charging time in EVs compared to the conventional vehicles, the parking locations can be considered as the candidate locations for installing charging stations. Another essential factor that should be considered in designing the Electric Vehicle Charging Station (EVCS) network is the size or capacity of charging stations. EV drivers' arrival times in a community vary depending on various factors such as the purpose of the trip, time of the day, and day of the week. So, the capacity of stations and the number of chargers significantly affect the accessibility and utilization of charging stations. Also, the EVCSs can be equipped by distinct types of chargers, which are different in terms of installation cost, charging time, and charging price. City planners and EVCS owners can make low-risk and high-utilization investment decisions by considering EV users charging pattern and their willingness to pay for different charger types.

At the operational level, managing a fleet of electric vehicles can offer several incentives to the L&T companies. EVs can be equipped with autonomous driving technologies to facilitate online decision making, on-board computation, and connectivity. Energy-efficient routing decisions for a fleet of autonomous electric vehicles (AEV) can significantly improve the asset utilization and vehicles’ battery life. However, employing AEVs also comes with new challenges. Two of the main operational challenges for AEVs in transport applications is their limited range and the availability of charging stations. Effective routing strategies for an AEV fleet require solving the vehicle routing problem (VRP) while considering additional constraints related to the limited range and number of charging stations.

In this dissertation, we develop models and algorithms to address the challenges in integrating the EVs into the logistic and transportation systems.

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