2026-04-11T07:15:41Zhttps://ebiltegia.mondragon.edu/oai/request

oai:ebiltegia.mondragon.edu:20.500.11984/63982024-05-24T11:21:51Zcom_20.500.11984_1143col_20.500.11984_1148

Dorronsoro, Xabier GARAYALDE, ERIK IRAOLA, UNAI 2024-05-03T13:33:43Z 2024-05-03T13:33:43Z 2023 979-8-3503-4445-5 2769-4186 https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=174475 https://hdl.handle.net/20.500.11984/6398 This paper presents an energy management algorithm for an Electric Vehicle (EV) charging station equipped with solar energy generation and local battery-based storage. For this purpose, a practical electric, thermal, and aging model of a lithium-ion battery cell is developed. We then leverage this model to develop a Nonlinear Model Predictive Control (NL-MPC) to manage the energy flow between the battery, grid, solar generation and the EV charging loads. The NL-MPC aims to reduce the total operating electricity and battery depreciation costs, while taking into account temperature, state of charge, current and voltage constraints. Simulation results, based on a case study from a Spanish EV charging station, demonstrate the effectiveness of the proposed approach. eng © 2023 IEEE Electric vehicle Charging stations MPC Batteries cost optimization ODS 7 Energía asequible y no contaminante ODS 11 Ciudades y comunidades sostenibles ODS 13 Acción por el clima Model Predictive Control for EV Chargers Coupling Electro-Thermal and Degradation Battery Models http://purl.org/coar/resource_type/c_c94f