Date of Award

2023

Degree Type

Thesis

Degree Name

Master of Science in Systems Engineering

Department

Mechanical, Industrial and Systems Engineering

First Advisor

Gretchen A. Macht

Abstract

The increasing affordability of electric vehicles (EVs) and the introduction of zero emission regulations have increased EV purchases. Consequently, the EV infrastructure must be developed to meet this rapidly rising demand. This need is particularly crucial in disadvantaged communities (DACs), as projections indicate that by 2030, over one-quarter of new EV owners will come from these communities. However, studies have revealed an unequal distribution of charging stations between DACs and non-disadvantaged communities (non-DACs), with a higher concentration in non-DACs. While governments have made efforts to expand charging stations through funding programs, a universal approach may not effectively address this issue across different communities. Instead, a more effective strategy involves analyzing charging behaviors among charging infrastructure users to develop tailored approaches for installing charging stations strategically.

This study aims to identify differences and similarities within and between DACs and non-DACs based on utilization patterns, and race/ethnicity to provide detailed insights into the communities' characteristics. The analysis employed the Gaussian Mixture Model (GMM) to cluster 19 markets within each DAC and non-DAC category across the U.S., considering various EV infrastructure utilization patterns. These patterns were then categorized to provide a framework for stakeholders, including policymakers and EV infrastructure providers. The goal is to enable them to classify communities based on their charging station utilization patterns and demographic characteristics, thereby making informed decisions regarding the placement of EV infrastructure.

The study concludes that communities should not be treated as homogenous entities. Instead, tailored approaches that address the unique needs of different communities must be developed to expand EV infrastructure and effectively promote EV adoption. Achieving this objective requires adapting current policy implications. The study offers several suggestions to adapt policies as a base for effective decision-making concerning EV infrastructure, ultimately reducing disparities in charging station distribution between DACs and non-DACs.

Download

Available for download on Friday, September 05, 2025

Share

COinS