Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/112234
Título: Application of NSGA-II to obtain the Charging Current-Time Tradeoff Curve in Battery Based Underwater Wireless Sensor Nodes
Autores/as: Rodriguez Garcia, Daniel
Montiel-Nelson, Juan A. 
Bautista Delgado, Tomás 
Sosa González, Carlos Javier 
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: Underwater wireless sensor node
Wireless power transfer
NSGA-II
Design optimization
Fecha de publicación: 2021
Proyectos: Sistema Sensor Para Jaulas de Piscifactorias 
Monitorización Estructural y Ambiental de Grandes Jaulas Offshore Para Acuicultura Atlántica (Jaulatlas) 
Publicación seriada: Sensors (Switzerland) 
Resumen: In this paper, a novel application of the Nondominated Sorting Genetic Algorithm II (NSGA II) is presented for obtaining the charging current–time tradeoff curve in battery based underwater wireless sensor nodes. The selection of the optimal charging current and times is a common optimization problem. A high charging current ensures a fast charging time. However, it increases the maximum power consumption and also the cost and complexity of the power supply sources. This research studies the tradeoff curve between charging currents and times in detail. The design exploration methodology is based on a two nested loop search strategy. The external loop determines the optimal design solutions which fulfill the designers’ requirements using parameters like the sensor node measurement period, power consumption, and battery voltages. The inner loop executes a local search within working ranges using an evolutionary multi-objective strategy. The experiments proposed are used to obtain the charging current–time tradeoff curve and to exhibit the accuracy of the optimal design solutions. The exploration methodology presented is compared with a bisection search strategy. From the results, it can be concluded that our approach is at least four times better in terms of computational effort than a bisection search strategy. In terms of power consumption, the presented methodology reduced the required power at least 3.3 dB in worst case scenarios tested.
URI: http://hdl.handle.net/10553/112234
ISSN: 1424-8220
DOI: 10.3390/s21165324
Fuente: Sensors (Switzerland) [ISSN 1424-8220], v. 21(16), 5324, (Agosto 2021)
Colección:Artículos
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