A Battery-free Asset Monitoring System based on RF Wireless Power Transfer

Rosa, Roberto La; Dehollain, Catherine; Pellitteri, Filippo; Miceli, R.; Livreri, Patrizia

doi:10.1109/melecon48756.2020.9140484

Cited by 6 publications

(4 citation statements)

References 64 publications

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“…RF energy sources, such as wireless routers and mobile base stations, are widely distributed in the environment and emit electromagnetic waves (RF energy) all the time. RF energy has become a research hotspot in self-powered WSN research due to its long-distance wireless transmission, wide distribution, and resistance to obstruction and environmental influences [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

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A Compact RF Energy Harvesting Wireless Sensor Node with an Energy Intensity Adaptive Management Algorithm

Liu,

Li,

Chen

et al. 2023

Sensors

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This paper presents a compact RF energy harvesting wireless sensor node with the antenna, rectifier, energy management circuits, and load integrated on a single printed circuit board and a total size of 53 mm × 59.77 mm × 4.5 mm. By etching rectangular slots in the radiation patch, the antenna area is reduced by 13.9%. The antenna is tested to have an S11 of −24.9 dB at 2.437 GHz and a maximum gain of 4.8 dBi. The rectifier has a maximum RF-to-DC conversion efficiency of 52.53% at 7 dBm input energy. The proposed WSN can achieve self-powered operation at a distance of 13.4 m from the transmitter source. To enhance the conversion efficiency under different input energy densities, this paper establishes an energy model for two operating modes and proposes an energy-intensity adaptive management algorithm. The experiments demonstrated that the proposed WSN can effectively distinguish between the two operating modes based on input energy intensity and realize efficient energy management.

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Section: Introductionmentioning

confidence: 99%

“…Based on the previous research, there are two main operating modes for RF-EH WSNs. Mode A involves continuous data acquisition and transmission until the energy storage components are depleted [7,8,[17][18][19][20][21]. Mode B involves periodic sleep, wake-up, data acquisition, and transmission [22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

A Compact RF Energy Harvesting Wireless Sensor Node with an Energy Intensity Adaptive Management Algorithm

Liu,

Li,

Chen

et al. 2023

Sensors

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“…BOOST circuits were constructed using discrete devices in [14,15]. In [16][17][18], an ultra-low power management chip was first used to boost the voltage, and then a DC-DC chip was used to convert and output the load voltage. In more studies, a single energy management chip was used to realize energy "store-and-release" and voltage boosting [7,[19][20][21].…”

Section: Introductionmentioning

confidence: 99%

A Compact Stacked RF Energy Harvester with Multi-Condition Adaptive Energy Management Circuits

Liu,

Li,

Chen

et al. 2023

Micromachines

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This paper presents a compact stacked RF energy harvester operating in the WiFi band with multi-condition adaptive energy management circuits (MCA-EMCs). The harvester is divided into antennas, impedance matching networks, rectifiers, and MCA-EMCs. The antenna is based on a polytetrafluoroethylene (PTFE) substrate using the microstrip antenna structure and a ring slot in the ground plane to reduce the antenna area by 13.7%. The rectifier, impedance matching network, and MCA-EMC are made on a single FR4 substrate. The rectifier has a maximum conversion efficiency of 33.8% at 5 dBm input. The MCA-EMC has two operating modes to adapt to multiple operating conditions, in which Mode 1 outputs 1.5 V and has a higher energy conversion efficiency of up to 93.56%, and Mode 2 supports a minimum starting input voltage of 0.33 V and multiple output voltages of 2.85–2.45 V and 1.5 V. The proposed RF energy harvester is integrated by multiple-layer stacking with a total size of 53 mm × 43.5 mm × 5.9 mm. The test results show that the proposed RF energy harvester can drive a wall clock (30 cm in diameter) at 10 cm distance and a hygrometer at 122 cm distance with a home router as the transmitting source.

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“…While these solutions can help alleviate maintenance and miniaturization problems, they cannot solve them altogether. Where feasible, such as in applications involving low duty-cycle sensors, it is far more preferable to implement battery-less devices, with the evident advantage of rendering them non-disposable, virtually unlimited in lifetime, more cost-efficient, and usable in environments where batteries can be dangerous [41][42][43][44][45]. For these reasons, battery-less solutions are gaining momentum [43,[46][47][48][49], with engineers increasingly opting for regenerative energy harvesting (EH), including RF EH and WPT.…”

Section: Introductionmentioning

confidence: 99%

Advanced Monitoring Systems Based on Battery-Less Asset Tracking Modules Energized through RF Wireless Power Transfer

Rosa

Dehollain

Livreri

2020

Sensors

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Asset tracking involving accurate location and transportation data is highly suited to wireless sensor networks (WSNs) featuring battery-less nodes that can be deployed in virtually any environment and require little or no maintenance. In response to the growing demand for advanced battery-less sensor tag solutions, this article presents a system for identifying and monitoring the speeds of assets in a WSN with battery-less tags that receive all their operating energy through radio frequency (RF) wireless power transfer (WPT) architecture, and a unique measurement approach to generate time-domain speed readouts. The assessment includes performance characteristics and key features of a system on chip (SoC) purposely designed to power a node through RF WPT. The result is an innovative solution for RF to DC conversion able to address the principal difficulties associated with maximum power conversion efficiency (PCE) with sensitivity and vice versa, a strategy, and a design optimization model to indicate the number of readers required for reliable asset identification and speed measurement. Model validation is performed through specific tests. Experimental results demonstrating the viability of the proposed advanced monitoring system are provided.

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A Battery-free Asset Monitoring System based on RF Wireless Power Transfer

Cited by 6 publications

References 64 publications

A Compact RF Energy Harvesting Wireless Sensor Node with an Energy Intensity Adaptive Management Algorithm

A Compact RF Energy Harvesting Wireless Sensor Node with an Energy Intensity Adaptive Management Algorithm

A Compact Stacked RF Energy Harvester with Multi-Condition Adaptive Energy Management Circuits

Advanced Monitoring Systems Based on Battery-Less Asset Tracking Modules Energized through RF Wireless Power Transfer

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