Date of Award

12-2017

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Engineering and Sciences

First Advisor

Aldo Fabregas Ariza

Second Advisor

Troy Nguyen

Third Advisor

Luis Daniel Otero

Fourth Advisor

Muzaffar Shaikh

Abstract

In line with the spate of technological advances, the transportation industry has also witnessed an increase in the adoption of Electric Vehicles (E.Vs). However, there has been and are still some underlying negating factors to the wide spread acceptance of these electric vehicles; one of note is the unavailability and inaccessibility of adequate charging infrastructure, long charging times, limited driving ranges, costs of the vehicles etc. These and many more characteristics lead to a trend popularly known as “range anxiety”. One of the major strengths of electric vehicles are their ability to be powered by electric energy via stored chemical energy in rechargeable batteries. Some electric vehicles run solely on batteries (Battery Electric Vehicle – BEVs), while others are a hybrid of the electric vehicles and the internal combustion engines (Plug-in Hybrid Electric Vehicles –PHEVs, and Hybrid Electric Vehicles – HEVs). However, since these electric vehicles lean towards reducing atmospheric pollution (Carbon monoxide, hydrocarbons etc.) caused by internal combustion engines, it also follows that the means of recharging these electric vehicles should also be geared towards reducing pollution to some degree. Hence, the concept of renewable energy sources powered recharging stations. However, before a lot of resources are committed into building such an infrastructure, a model should be designed and developed which will take into account certain key factors such as storage capacity, type and size of the renewable sources, charger characteristics, facility layout, policies and other identified stakeholders requirements which are evaluated and used in trade-off and decision analysis. However, the status-quo involves around a document-centric methodology of system development. This methodology carries with it challenging characteristics such as poor communication of data between and within interested parties, inability to contain complexities inherent in today’s projects, stored data becoming prone to damage as a result of storage or usage and sometimes, inaccessibility of data. In line with current systems engineering practice, we propose a model-centric approach of the system development life-cycle, which will negate some of the drawbacks of the document-centric approach. In this work, a two-level approach is proposed: First, the model based systems engineering (MBSE) framework approach is implemented utilizing the systems modeling language (SysML) to formulate and display different views and architecture of the system in question. The objectives of this MBSE approach in addition to offering different views of the model are also to aid in real-time communication and collaboration of designs which links to understanding change configurations and impact, requirements verification, and traceability. In the second approach, a discrete-event simulation (Arena) tool is used as the reference simulation and optimization tool for the model’s architectural analysis. The discrete-event simulation (DES) models a hypothetical renewable energy powered charging and swapping station with the objective of maximizing the electric vehicle’s throughput (amount of EVs successfully recharging and swapping batteries in the facility). Certain constraints such as the allowable area for the renewable energy generation, operating budget, amount of energy to purchase from the main grid etc., are included to account for a realistic adaptation of the facility, which is in line with the concept of the renewable energy sources powered recharging stations previously mentioned.

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