NONE 20260327074649637 wseas/wseas content-registration-form+ja@crossref.org content-registration-form WSEAS TRANSACTIONS ON POWER SYSTEMS 1790-5060 2224-350X Tsvetelin Stefanov nstitute of Robotics, Bulgarian Academy of Sciences, SOFIA, BULGARIA University of Library Studies and Information Technologies Sofia, BULGARIA Elena Blagoeva Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia, BULGARIA Denis Chikurtev Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia, BULGARIA https://orcid.org/0000-0003-4903-7544 This paper proposes two architectural solutions for Electric Vehicle Management Systems (EVMS), based on open-access FIWARE components. The first architecture implements a simple configuration for charging station management, while the second builds upon the first by expanding its functionalities by adding historical data support. Modeling a charging station in the context of FIWARE requires a smart data model. . The paper introduces an improved smart data model, used for the management of a physical charging station. To validate the proposed architectures, the article first presents the results of a charging session performed with the charging station and management platform. A simulation of ten charging sessions for each architecture demonstrates its capabilities and enables a comparative assessment. The obtained results confirm that the proposed architecture provides better scalability and performance compared to the standard system, based on HTTP communication. 12 31 2025 477 38 https://creativecommons.org/licenses/by/4.0/deed.en_US 10.37394/232016.2025.20.38 https://wseas.com/journals/ps/2025/a765116-022(2025).pdf Lee, Z. J., Lee, G., Lee, T., Jin, C., Lee, R., Low, Z., Chang, D., Ortega, C., & Low, S. H. (2021). Adaptive charging networks: A framework for smart electric vehicle charging. 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