Fairness and Equity in Electric Vehicle Charging With Mobile Charging Stations

The rising demand for electric vehicles (EVs) has highlighted the urgent need for innovative EV charging methods, given the numerous operational and technological challenges. This study introduces an innovative real-time energy allocation model aimed at optimizing the service quality of mobile charging stations (MCSs), an emerging EV charging concept, while ensuring fairness among EV users. We evaluate our approach through case studies considering varying numbers of charging demands, and road traffic congestion status. We incorporate a 24-node Sioux Falls transportation network and real EV parking lot data to ensure practicality. Our results demonstrate the effectiveness of the proposed strategy in terms of quality-of-service (QoS) and fairness scores, even during periods of traffic congestion and high energy demand. Additionally, we conduct sensitivity and scalability analyses to assess the algorithm's decision-making under uncertain EV user behavior regarding reservation requests on a larger scale.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Industry Applications
Published
2024-10-09
DOI
https://doi.org/10.1109/tia.2024.3477426
Citations
8
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
1.67
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fairness and Equity in Electric Vehicle Charging With Mobile Charging Stations

Muhammed Ali Beyazıt, Akın Taşçıkaraoğlu, Ayşe Kübra Erenoğlu
8 citations
IEEE Transactions on Industry Applications
Electric Vehicles and Infrastructure
1.67
article

Fairness and Equity in Electric Vehicle Charging With Mobile Charging Stations

Muhammed Ali Beyazıt, Akın Taşçıkaraoğlu, Ayşe Kübra Erenoğlu
article en
8 citations

Abstract

The rising demand for electric vehicles (EVs) has highlighted the urgent need for innovative EV charging methods, given the numerous operational and technological challenges. This study introduces an innovative real-time energy allocation model aimed at optimizing the service quality of mobile charging stations (MCSs), an emerging EV charging concept, while ensuring fairness among EV users. We evaluate our approach through case studies considering varying numbers of charging demands, and road traffic congestion status. We incorporate a 24-node Sioux Falls transportation network and real EV parking lot data to ensure practicality. Our results demonstrate the effectiveness of the proposed strategy in terms of quality-of-service (QoS) and fairness scores, even during periods of traffic congestion and high energy demand. Additionally, we conduct sensitivity and scalability analyses to assess the algorithm's decision-making under uncertain EV user behavior regarding reservation requests on a larger scale.

IEEE Transactions on Industry ApplicationsVol. 61(1)
Yıldız Technical University (TR), Muğla University (TR)
Openalex Percentile: Top 15%
Electric Vehicles and Infrastructure
1.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.