Adaptive Charging Simulation Model for Different Electric Vehicles and Mobility Patterns

Bruno Knevitz Hammerschmitt (), Clodomiro Unsihuay-Vila, Jordan Passinato Sausen, Marcelo Bruno Capeletti, Alexandre Rasi Aoki, Mateus Duarte Teixeira, Carlos Henrique Barriquello and Alzenira da Rosa Abaide
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Bruno Knevitz Hammerschmitt: Graduate Program in Electrical Engineering, Federal University of Santa Maria, Santa Maria 97105-900, Rio Grande do Sul, Brazil
Clodomiro Unsihuay-Vila: Department of Electrical Engineering, Federal University of Paraná, Curitiba 81531-980, Paraná, Brazil
Jordan Passinato Sausen: Graduate Program in Electrical Engineering, Federal University of Santa Maria, Santa Maria 97105-900, Rio Grande do Sul, Brazil
Marcelo Bruno Capeletti: Graduate Program in Electrical Engineering, Federal University of Santa Maria, Santa Maria 97105-900, Rio Grande do Sul, Brazil
Alexandre Rasi Aoki: Department of Electrical Engineering, Federal University of Paraná, Curitiba 81531-980, Paraná, Brazil
Mateus Duarte Teixeira: Department of Electrical Engineering, Federal University of Paraná, Curitiba 81531-980, Paraná, Brazil
Carlos Henrique Barriquello: Graduate Program in Electrical Engineering, Federal University of Santa Maria, Santa Maria 97105-900, Rio Grande do Sul, Brazil
Alzenira da Rosa Abaide: Graduate Program in Electrical Engineering, Federal University of Santa Maria, Santa Maria 97105-900, Rio Grande do Sul, Brazil

Energies, 2024, vol. 17, issue 16, 1-21

Abstract: Electric mobility is a sustainable alternative for mitigating carbon emissions by replacing the conventional fleet. However, the low availability of data from charging stations makes planning energy systems for the integration of electric vehicles (EVs) difficult. Given this, this work focuses on developing an adaptive computational tool for charging simulation, considering many EVs and mobility patterns. Technical specifications data from many EVs are considered for charging simulation, such as battery capacity, driving range, charging time, charging standard for each EV, and mobility patterns. Different simulations of charging many EVs and analyses of weekly charging load profiles are carried out, portraying the characteristics of the different load profiles and the challenges that system planners expect. The research results denote the importance of considering different manufacturers and models of EVs in the composition of the aggregate charging load profile and mobility patterns of the region. The developed model can be adapted to any system, expanded with new EVs, and scaled to many EVs, supporting different research areas.

Keywords: electric vehicle; charging load profile; charging standard; electric mobility; scalability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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