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Impacts of COVID-19 on Electric Vehicle Charging Behavior: Data Analytics, Visualization, and Clustering

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Department of Computer Science and Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates
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Author to whom correspondence should be addressed.
Appl. Syst. Innov. 2022, 5(1), 12; https://doi.org/10.3390/asi5010012
Received: 21 November 2021 / Revised: 20 December 2021 / Accepted: 4 January 2022 / Published: 7 January 2022
COVID-19 pandemic has infected millions and led to a catastrophic loss of lives globally. It has also significantly disrupted the movement of people, businesses, and industries. Additionally, electric vehicle (EV) users have faced challenges in charging their vehicles in public charging locations where there is a risk of COVID-19 exposure. However, a case study of EV charging behavior and its impacts during the SARS-CoV-2 is not addressed in the existing literature. This paper investigates the impacts of COVID-19 on EV charging behavior by analyzing the charging activity during the pandemic using a dataset from a public charging facility in the USA. Data visualization of charging behavior alongside significant timelines of the pandemic was utilized for analysis. Moreover, a cluster analysis using k-means, hierarchical clustering, and Gaussian mixture models was performed to identify common groups of charging behavior based on the vehicle arrival and departure times. Although the number of vehicles using the charging station was reduced significantly due to lockdown restrictions, the charging activity started to pick up again since May 2021 due to an increase in vaccination and easing of public restrictions. However, the charging activity currently still remains around half of the activity pre-pandemic. A noticeable decline in charging session length and an increase in energy consumption can be observed as well. Clustering algorithms identified three groups of charging behavior during the pandemic and their analysis and performance comparison using internal validation measures were also presented. View Full-Text
Keywords: low emission vehicles; COVID-19; cluster analysis; charging infrastructure; data analytics; mobility low emission vehicles; COVID-19; cluster analysis; charging infrastructure; data analytics; mobility
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MDPI and ACS Style

Shahriar, S.; Al-Ali, A.R. Impacts of COVID-19 on Electric Vehicle Charging Behavior: Data Analytics, Visualization, and Clustering. Appl. Syst. Innov. 2022, 5, 12. https://doi.org/10.3390/asi5010012

AMA Style

Shahriar S, Al-Ali AR. Impacts of COVID-19 on Electric Vehicle Charging Behavior: Data Analytics, Visualization, and Clustering. Applied System Innovation. 2022; 5(1):12. https://doi.org/10.3390/asi5010012

Chicago/Turabian Style

Shahriar, Sakib, and A. R. Al-Ali. 2022. "Impacts of COVID-19 on Electric Vehicle Charging Behavior: Data Analytics, Visualization, and Clustering" Applied System Innovation 5, no. 1: 12. https://doi.org/10.3390/asi5010012

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