Abstract
This research introduces a queuing framework, denoted as M1/M2/c, to analyze the dynamics of electric vehicle (EV) charging stations. The framework considers non-uniform Poisson arrival rates (M1), influenced by road traffic conditions, and exponential service durations (M2), affected by factors such as battery size and charging habits. The variable "c"represents the number of chargers at the station. Using this framework, the study evaluates the charging demand and capacity of a single EV charging station. Results indicate that the station's capacity to simultaneously charge EVs is limited, despite varying arrival rates and charging durations. Additionally, the projected charging demand follows a similar trend to EV arrival rates, peaking during daytime hours. Overall, the study provides insights into managing EV charging infrastructure amidst fluctuating demand and limited capacity.
| Original language | English |
|---|---|
| Pages (from-to) | 434-439 |
| Number of pages | 6 |
| Journal | Transportation Research Procedia |
| Volume | 84 |
| DOIs | |
| State | Published - 2025 |
| Event | 1st Internation Conference on Smart Mobility and Logistics Ecosystems, SMiLE 2024 - Dhahran, Saudi Arabia Duration: 17 Sep 2024 → 19 Sep 2024 |
Bibliographical note
Publisher Copyright:© 2024 The Authors. Published by ELSEVIER B.V.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- EV
- EV charging station
- Queuing theory
ASJC Scopus subject areas
- Transportation
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