Hybrid Low Frequency Electromagnetic Field and Solar Energy Harvesting Architecture for Self-Powered Wireless Sensor System

Cao, Di; Jia, Jing-run; Xie, Mingxing; Lei, Yanjing; Li, Wei

doi:10.1007/978-3-030-23597-0_3

Cited by 5 publications

(2 citation statements)

References 16 publications

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“…with source transducer's (Thermoelectric (TEG), Photovoltaic (PV) and Piezoelectric (PZ)) & power converter's static analytical models. Other techniques presented in [17][18][19][20] viz. Complementary use of Energy Source, Multi-Input (Dual) Switched Capacitor and Multi-Input Boost Converter Topology etc.…”

Section: Introductionmentioning

confidence: 99%

SPICE modelling and analysis of hybrid energy harvester combiner topologies

SELVAKUMAR,

GHOSH

et al. 2023

IJEAT

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Harvesting energy from multiple hybrid sources and efficiently combining the harvested energies is critical for enabling self-powered devices. Designing an efficient energy combiner is a technical challenge and is non-trivial. Various factors viz. kinds of sources, harvestable energy level and range from the sources, electrical characteristics of sources (low current and high voltage, high current and low voltage, capacitive, inductive etc.), impedance matching (resistive, resistive-reactive, modulus, complex conjugate etc.) of sources, sources scheduling algorithms for combiner, sources switching and control/trigger circuit losses, power conversion and management etc. influence the overall energy combiner’s efficiency. Considering that, this article presents a SPICE modelling and simulation framework for analyzing hybrid energy harvester combiner topologies such as Inductor sharing, voltage level detection and powerORing for its power and energy flow characteristics, regulation, and energy combining efficiency. Such analysis through simulation enables arriving efficient combiner architecture for the chosen harvestable resources, source models, power management circuits and schemes etc. Based on a case study with three different kinds of sources, it has been observed that the voltage level detection technique with DC-DC converters results in the highest efficiency as compared with the other two topologies for such a scenario.

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Section: Introductionmentioning

confidence: 99%

SPICE modelling and analysis of hybrid energy harvester combiner topologies

SELVAKUMAR,

GHOSH

et al. 2023

IJEAT

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“…The device stores the energy in a supercapacitor [13]. Other systems mix more than one energy harvesting technique [14,15], such as solar and wind-based, in order to get enough energy to meet the demand of remote sensors and small-scale portable electronics; while solar and radio-frequency can be used to supply wireless sensor networks using dual storage with a supercapacitor and a battery. There is even a system-on-chip that implements all the techniques contemplated in this study to feed wireless sensor networks using a battery or supercapacitor [16].…”

Section: Introductionmentioning

confidence: 99%

Autonomous Active Tag Using Energy Harvesting Strategies

2020

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In this work, we present autonomous active tags. The power sources of these active tags employ energy harvesting techniques, specifically, solar and mechanical techniques. The integration of these techniques, and the storage of the energy obtained with a supercapacitor, converts the active tag into an autonomous device. These tags work in a low power mode in which they dynamically adjust their radio communication capabilities. Such a configuration depends on the application. We tested the tags in a real environment with testing parameters to check the modules, meaning more wake-ups over a longer time. Under these conditions, the tags gather enough energy to autonomously maintain standby operation on a sunny day for ten hours. In conclusion, this autonomous active tag is a demonstration that the integration of energy harvesting techniques, supercapacitor storage and the management of low power modes for transceivers, microcontrollers, and memories creates a device without energy dependencies that only depends on the requirements, and can be used in many applications related to, for instance, smart homes, smart cities, smart cars, and connected forests.

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