Resumen
Battery has a fundamental role in energy storage systems for hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV), electric vehicles (EV) and nowadays in smart grids. The battery state of charge (SOC) behavior is affected by operating temperature reducing its supply capacity or energy storage, therefore, it has been considered important to establish a mathematical model from experimental data of a electric vehicle during route tests. This article presents a metaheuristic optimization method based on accelerated particle swarm optimization (APSO) for SOC maximization during Lithium-ion (Li-ion) batteries charge and discharge states. The proposed optimization model reach to satisfy the balance between: current, temperature and time for the battery to supply the required amount of energy, minimizing the SOC reduction, subject to system specific restrictions. Simulation results show an improvement in the SOC without sacrificing the energy supply of the battery, which demonstrates the potential of the optimization technique in the EV.
Idioma original | Inglés |
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Título de la publicación alojada | 2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2019 |
Editorial | Institute of Electrical and Electronics Engineers Inc. |
ISBN (versión digital) | 9788887237436 |
DOI | |
Estado | Publicada - jul. 2019 |
Evento | 2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2019 - Turin, Italia Duración: 2 jul. 2019 → 4 jul. 2019 |
Serie de la publicación
Nombre | 2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2019 |
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Conferencia
Conferencia | 2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2019 |
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País/Territorio | Italia |
Ciudad | Turin |
Período | 2/07/19 → 4/07/19 |
Nota bibliográfica
Publisher Copyright:© 2019 AEIT.