Date of Award

2019

Degree Type

Thesis

Degree Name

Master of Science in Systems Engineering

Department

Mechanical, Industrial and Systems Engineering

First Advisor

Gretchen A. Macht

Abstract

Battery Electric vehicles (BEVs) have significantly increased in their importance based on their market share proportion on the national and regional stage, from 14,650 units sold in the US in 2012 to up to 105,000 units. The general energy consumption of electric vehicles (EVs) in practice has so far been little researched. The aim of this work is to create an understanding of the discharge behavior of electric vehicles as a function of different road types in order to derive, for example, the economic efficiency and the utility value of EVs. A regression model is used to describe this effect by also taking into account different factors, i.e., ambient temperature, initial state of charge (SOC), individual driver behavior, and the different road types. The tests were conducted in a 2017 Volkswagen eGolf along a predefined route in southern Rhode Island.

A clear consumption pattern can be derived from the vehicle data, where BEVs consume the least amount of energy on road types with medium speed and a high flow rate of traffic (Minor Arterials and Other Principal Arterials), while on roads with a higher average speed (i.e., Interstate and Freeways/ Expressways) the energy consumption rate was significantly higher. Additionally, an increased energy consumption on minor road classes (i.e., Collector and Local roads) was experimentally verified.

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