Decision-Making System for Electric Vehicle Management by Integrating Smart Technologies and Local Characteristics

With the global shift to electric vehicles, countries face unique challenges and opportunities shaped by their geographical and economic contexts. This paper presents a system that leverages smart transport technologies, the Internet of Things, and decision-making algorithms, such as PROMETHEE, to optimize charging stations and their positioning in diverse urban and rural settings. The system addresses key obstacles, including managing charging infrastructure, balancing energy consumption, and enhancing transport accessibility. By analyzing local conditions, the proposed solution incorporates innovative algorithms for electricity demand forecasting, charging station management, and integration with urban transport systems. This approach ensures a flexible, scalable, and sustainable electric vehicle management system that aligns with international standards and evolving technological trends.

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Publication Details

Journal
Applied Sciences
Published
2024-11-29
DOI
https://doi.org/10.3390/app142311150
Citations
3
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.63
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article

Decision-Making System for Electric Vehicle Management by Integrating Smart Technologies and Local Characteristics

Yelena Chaiko, Rasa Brūzgienė, Мадина Мансурова, Roberts Grants et al.
3 citations
Applied Sciences
Electric Vehicles and Infrastructure
0.63
article

Decision-Making System for Electric Vehicle Management by Integrating Smart Technologies and Local Characteristics

Yelena Chaiko, Rasa Brūzgienė, Мадина Мансурова, Roberts Grants, Nadezhda Kunicina, Vladimir Beliaev, Raikhan Amanova
article en
3 citations

Abstract

With the global shift to electric vehicles, countries face unique challenges and opportunities shaped by their geographical and economic contexts. This paper presents a system that leverages smart transport technologies, the Internet of Things, and decision-making algorithms, such as PROMETHEE, to optimize charging stations and their positioning in diverse urban and rural settings. The system addresses key obstacles, including managing charging infrastructure, balancing energy consumption, and enhancing transport accessibility. By analyzing local conditions, the proposed solution incorporates innovative algorithms for electricity demand forecasting, charging station management, and integration with urban transport systems. This approach ensures a flexible, scalable, and sustainable electric vehicle management system that aligns with international standards and evolving technological trends.

Applied SciencesVol. 14(23)
Kaunas University of Technology (LT), Al-Farabi Kazakh National University (KZ), Riga Technical University (LV)
Openalex Percentile: Top 30%
Electric Vehicles and Infrastructure
0.63
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