caa a22 4500 606209751 CHVBK 20210128101030.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s11220-015-0117-0 doi (NATIONALLICENCE)springer-10.1007/s11220-015-0117-0 Optimal Design of RF Energy Harvesting Device Using Genetic Algorithm [Elektronische Daten] [T. Mori, Y. Sato, R. Adriano, H. Igarashi] This paper presents optimal design of an RF energy harvesting device using genetic algorithm (GA). In the present RF harvester, a planar spiral antenna (PSA) is loaded with matching and rectifying circuits. On the first stage of the optimal design, the shape parameters of PSA are optimized using $$\mu {\rm GA}$$ μ GA . Then, the equivalent circuit of the optimized PSA is derived for optimization of the circuits. Finally, the parameters of RF energy harvesting circuit are optimized to maximize the output power using GA. It is shown that the present optimization increases the output power by a factor of five. The manufactured energy harvester starts working when the input electric field is greater than 0.5 V/m. Springer Science+Business Media New York, 2015 RF energy harvester nationallicence Antenna nationallicence FDTD nationallicence Genetic algorithm nationallicence Mori T. Graduate School of Information Science and Technology, Hokkaido University, 060-0814, Sapporo, Japan aut Sato Y. Graduate School of Information Science and Technology, Hokkaido University, 060-0814, Sapporo, Japan aut Adriano R. Departamento de Engenharia Eletrica, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Brazil aut Igarashi H. Graduate School of Information Science and Technology, Hokkaido University, 060-0814, Sapporo, Japan aut Sensing and Imaging Springer US; http://www.springer-ny.com 16/1(2015-12-01), 1-12 1557-2064 16:1<1 2015 16 11220 https://doi.org/10.1007/s11220-015-0117-0 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11220-015-0117-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Mori T. Graduate School of Information Science and Technology, Hokkaido University, 060-0814, Sapporo, Japan aut NATIONALLICENCE 700 1- Sato Y. Graduate School of Information Science and Technology, Hokkaido University, 060-0814, Sapporo, Japan aut NATIONALLICENCE 700 1- Adriano R. Departamento de Engenharia Eletrica, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte, Brazil aut NATIONALLICENCE 700 1- Igarashi H. Graduate School of Information Science and Technology, Hokkaido University, 060-0814, Sapporo, Japan aut NATIONALLICENCE 773 0- Sensing and Imaging Springer US; http://www.springer-ny.com 16/1(2015-12-01), 1-12 1557-2064 16:1<1 2015 16 11220