Optimizing EV Charging Infrastructure through Behavioral Analysis, Smart Charging, and V2G Integration

The rapid adoption of electric vehicles (EVs) underscores the pressing need for optimized charging infrastructure to meet growing demands. This study investigates the integration of behavioral analysis, innovative charging strategies, and vehicle-to-grid (V2G) technology to improve EV infrastructure efficiency and grid stability. This research identifies key factors that influence charging demand and usage by examining user-specific charging patterns, including differences between private and fleet users. Smart charging and dynamic pricing models are explored to alleviate peak load stress, while V2G solutions enhance energy distribution during demand fluctuations. The findings emphasize the significance of flexible infrastructure planning, which includes Level 1, Level 2, and DC fast chargers strategically deployed to cater to diverse EV user needs. This approach offers a pathway to a sustainable, scalable charging ecosystem, promoting both user convenience and grid resilience.

Authors

Institutions

Publication Details

Published
2025-02-10
DOI
https://doi.org/10.1109/tpec63981.2025.10907178
Citations
4
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
2.92
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing EV Charging Infrastructure through Behavioral Analysis, Smart Charging, and V2G Integration

Abu Shufian, Md Mukter Hossain Emon, Md. Ismail Hossain, Anup Nandi et al.
4 citations
Electric Vehicles and Infrastructure
2.92
article

Optimizing EV Charging Infrastructure through Behavioral Analysis, Smart Charging, and V2G Integration

Abu Shufian, Md Mukter Hossain Emon, Md. Ismail Hossain, Anup Nandi, Hasanur Zaman Anonto, Azad Shahriyar
article en
4 citations

Abstract

The rapid adoption of electric vehicles (EVs) underscores the pressing need for optimized charging infrastructure to meet growing demands. This study investigates the integration of behavioral analysis, innovative charging strategies, and vehicle-to-grid (V2G) technology to improve EV infrastructure efficiency and grid stability. This research identifies key factors that influence charging demand and usage by examining user-specific charging patterns, including differences between private and fleet users. Smart charging and dynamic pricing models are explored to alleviate peak load stress, while V2G solutions enhance energy distribution during demand fluctuations. The findings emphasize the significance of flexible infrastructure planning, which includes Level 1, Level 2, and DC fast chargers strategically deployed to cater to diverse EV user needs. This approach offers a pathway to a sustainable, scalable charging ecosystem, promoting both user convenience and grid resilience.

American International University-Bangladesh (BD), Lamar University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Electric Vehicles and Infrastructure
2.92
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.

Optimizing EV Charging Infrastructure through Behavioral Analysis, Smart Charging, and V2G Integration — Abu Shufian, Md Mukter Hossain Emon, et al. · (2025) | TGRS Research Map | TGRS