In the context of critical challenges related to global warming and the necessity of reducing carbon footprint, the electric car sector is experiencing significant growth. This progress inevitably leads to the need for expansion and modernization of the charging station infrastructure. This article conducts a detailed analysis of how big data processing technologies can contribute to the optimization of this infrastructure’s use, the efficiency of charging stations, and the development of personalized services for electric vehicle users. Strategies for solving current problems, particularly in the areas of data security and standardization, are discussed, along with the impact of big data on the formation of new commercial models in the electric transport sector. Special attention is given to the analysis of existing scientific works and publications, which reveal a noticeable deficit of research focused on adapting big data technologies to specific regional conditions and analyzing the behavioral models of electric vehicle consumers. The article identifies key directions for future research aimed at exploring the potential of big data for the intelligent optimization of electric vehicle transport, particularly in areas such as demand forecasting, effective management of charging stations, development of new user services, and integration with broader urban transport management systems. Additionally, the article highlights challenges related to ensuring the confidentiality and security of collected data, the need to integrate diverse data and systems, and the current demand for qualified professionals in the field of big data analysis. The final section of the article focuses on the prospects of using big data in electric transport, their potential contribution to the development of smart city concepts, infrastructure improvement, and enhancing the quality of services for end consumers. Recommendations are provided for key stakeholders in the industry, with the aim of facilitating the adoption of strategic decisions that would take into account future opportunities and challenges. An analytical review of current literature sources and online publications is included, emphasizing the innovative nature of the research conducted.
- Oskaras Ilgauskas, Elizabeth Connelly, Andrew Daou, Alexandre Gouy, Mathilde Huismans, Hyeji Kim, Jean-Baptiste Le Marois, Shane McDonagh, Apostolos Petropoulos and Jacob Teter (2023, April). Global EV Outlook 2023. IEA. https://www.iea.org/reports/global-ev-outlook-2023
- Hussain, M. M., Beg, M. S., Alam, M. S., & Laskar, S. H. (2020). Big data analytics platforms for electric vehicle integration in transport oriented smart cities: Computing platforms for platforms for electric vehicle integration in smart cities. In Cyber warfare and terrorism: Concepts, methodologies, tools, and applications, 833– 854. IGI Global. https://doi.org/10.4018/IJDCF.2019070102
- Arias, M. B., & Bae, S. (2016). Electric vehicle charging demand forecasting model based on big data technologies. Applied energy, 183, 327–339. https://doi.org/10.1016/j.apenergy.2016.08.080
- Lee, J., Park, G. L., Han, Y., & Yoo, S. (2017, May). Big data analysis for an electric vehicle charging infrastructure using open data and software. In Proceedings of the eighth international conference on future energy systems, 252–253. https://doi.org/10.1145/3077839.3081670
- Rathore, H., Meena, H. K., & Jain, P. (2023, May). Forecasting of EVs Charging Behavior Using Deep Neural Networks. In 2023 International Conference on Communication, Circuits, and Systems (IC3S), 1–6. IEEE. https://doi.org/10.1109/IC3S57698.2023.10169211
- Kumar, M., Panda, K. P., Naayagi, R. T., Thakur, R., & Panda, G. (2023). Comprehensive Review of Electric Vehicle Technology and Its Impacts: Detailed Investigation of Charging Infrastructure, Power Management, and Control Techniques. Applied Sciences, 13(15), 8919. https://doi.org/10.3390/app13158919
- Li, Y., Luo, J., Chow, C. Y., Chan, K. L., Ding, Y., & Zhang, F. (2015, April). Growing the charging station network for electric vehicles with trajectory data analytics. In 2015 IEEE 31st international conference on data engineering, 1376–1387. IEEE. https://doi.org/10.1109/ICDE.2015.7113384
- Shahriar, S., Al-Ali, A. R., Osman, A. H., Dhou, S., & Nijim, M. (2020). Machine learning approaches for EV charging behavior: A review. IEEE Access, 8, 168980–168993. https://doi.org/10.1109/ACCESS.2020.3023388
- Kang, H. C., Kang, K. B., Ahn, H. K., Lee, S. H., Ahn, T. H., & Jwa, J. W. (2017). The smart EV charging system based on the big data analysis of the power consumption patterns. International Journal of Internet, Broadcasting and Communication, 9(2), 1–10. https://doi.org/10.7236/IJIBC.2017.9.2.1
- Soldan, F., Bionda, E., Mauri, G., & Celaschi, S. (2021). Short-term forecast of EV charging stations occupancy probability using big data streaming analysis. arXiv preprint arXiv:2104.12503. https://doi.org/10.48550/arXiv.2104.12503
- Rath, M. (2021, October 12). Big data analytics of ev charging stations. SlideShare. https://www.slideshare.net/MuskanRath1/big-data-analytics-of-ev-charging-stations
- Roberts, J. (2022, May 9). How Data Analytics Enables Growth for EV Manufacturers. Lhpes. https://www.lhpes.com/blog/how-data-analytics-enables-growth-for-ev-manufacturers
- McLoughlin, B. (2023, October 6). EV does it: How AI will transform charging infrastructure. HERE. https://www.here.com/learn/blog/ai-electric-vehicle-infrastructure
- Reszke, D. (2022, May 2). Trends in Electric Vehicle Charging Infrastructure. Codete. https://codete.com/blog/trends-in-electric-vehicle-charging-infrastructure
- Swallow, T. (2023, February 23). Top 10 technologies driving the shift to electric vehicles. EV.Magazine. https://evmagazine.com/top10/top-10-technologies-driving-the-shift-to-el...
- Schewel, D. L. (2023, August 8). Electric Vehicle Charger Deployment: 4 Ways Big Data Analytics Can Help With EV Infrastructure. StreetlightData. https://www.streetlightdata.com/4-ways-big-data-analytics-can-help- with-electric-vehicles-ev-charging-deployment/
- EV Plugs (2023, November 9). Unlocking Insights: The Power of Data Analysis in the EV Industry. Linkedin. https://www.linkedin.com/pulse/unlocking-insights-power-data-analysis-ev-industry-ev-plugs-uogaf/
- Impower Connection (2023, August 31) The Importance of Data Analytics in EV Charging Infrastructure. Impower Connection. https://impowerconnection.com/the-importance-of-data-analytics-in-ev-cha...
- Autoconsulting (2024, January 12). All news on the topic – Ukraine: How many charging stations are needed for electric cars in Ukraine. Autoconsulting. http://autoconsulting.ua/article.php?sid=55515
- (n. d.). Intelligent EV Analytics Platform. Smart EMobility. https://smartemobility.ai/solutions/ev-analytics