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Sensors and Systems with Energy Harvesting
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Sensors and Systems with Energy Harvesting

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (15 May 2020) | Viewed by 10273

Special Issue Editor

Prof. Dr. Erol Gelenbe

E-Mail Website
Guest Editor
Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100 Gliwice, Poland
Interests: energy optimization; energy packet networks; networked systems; physical and biological networks; probability models; natural computation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The wide-spread use of energy harvesting from photovoltaic, wind, water, mechanical vibrations and ambient electromagnetics has fully become a reality, with the ability to bring electrical power closer to the point of consumption, reducing the CO2 impact of energy, and benefits to widely different systems, including ICT in general, mobile communications, the Internet of Things (IoT), energy production for homes and businesses, transportation, and many different fields. However, its wide applicability poses problems of energy storage and requires new methods to adaptively match energy production and consumption, with the ability to rapidly adapt networks of intermittent energy sources, and energy storage units, including batteries and electric vehicles, with energy consumers including electric vehicles, data centers, businesses, telecommunications equipment, workplaces, and homes.

This special issue of the Open Access journal Sensors (IF = 3.031) will address research on all these aspects in a holistic manner, that address the relevant algorithms, the design, analysis, and simulation of intelligent integrated systems which combine sensors, actuators, fixed or mobile energy storage units, and smart decision algorithms and systems to take advantage of the increased flexibility introduced by widely available and widely varying sources of harvested energy. Topics of interest also include relevant mathematical models, energy packet networks, machine learning-based techniques, experimental system designs that minimize the consumption of nonrenewable energy sources, sensor networks that operate with renewable energy, and the use of sensor networks to control networks of renewable energy sources and energy consumers. 

The deadline for submitting original unpublished papers is 15 May 2020. However, incoming papers will be refereed and processed as soon as they are submitted.

Prof. Dr. Erol Gelenbe
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

16 pages, 2583 KiB  
Article
A Self-Adaptive and Self-Sufficient Energy Harvesting System
by Mario Mösch, Gerhard Fischerauer and Daniel Hoffmann
Sensors 2020, 20(9), 2519; https://doi.org/10.3390/s20092519 - 29 Apr 2020
Cited by 10 | Viewed by 3224
Abstract
Self-adaptive vibration energy harvesters convert the kinetic energy from vibration sources into electrical energy and continuously adapt their resonance frequency to the vibration frequency. Only when the two frequencies match can the system harvest energy efficiently. The harvesting of vibration sources with a [...] Read more.
Self-adaptive vibration energy harvesters convert the kinetic energy from vibration sources into electrical energy and continuously adapt their resonance frequency to the vibration frequency. Only when the two frequencies match can the system harvest energy efficiently. The harvesting of vibration sources with a time-variant frequency therefore requires self-adaptive vibration harvesting systems without human intervention. This work presents a self-adaptive energy harvesting system that works completely self-sufficiently. Using magnetic forces, the axial load on a bending beam is changed and thus the resonance frequency is set. The system achieves a relative tuning range of 23% at a center frequency of 36.4 Hz. Within this range, the resonance frequency of the harvester can be set continuously and precisely. With a novel optimized method for frequency measurement and with customized electronics, the system only needs 22 µW to monitor the external vibration frequency and is therefore also suitable for environments with low vibration amplitudes. The system was verified on a vibrational test bench and can easily be tailored to a specific vibration source. Full article
(This article belongs to the Special Issue Sensors and Systems with Energy Harvesting)
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22 pages, 495 KiB  
Article
Resource Allocation for Machine-Type Communication of Energy-Harvesting Devices in Wi-Fi HaLow Networks
by Dmitry Bankov, Evgeny Khorov, Andrey Lyakhov and Jeroen Famaey
Sensors 2020, 20(9), 2449; https://doi.org/10.3390/s20092449 - 25 Apr 2020
Cited by 11 | Viewed by 2387
Abstract
The recent Wi-Fi HaLow technology focuses on adopting Wi-Fi for the needs of the Internet of Things. A key feature of Wi-Fi HaLow is the Restricted Access Window (RAW) mechanism that allows an access point to divide the sensors into groups and to [...] Read more.
The recent Wi-Fi HaLow technology focuses on adopting Wi-Fi for the needs of the Internet of Things. A key feature of Wi-Fi HaLow is the Restricted Access Window (RAW) mechanism that allows an access point to divide the sensors into groups and to assign each group to an exclusively reserved time interval where only the stations of a particular group can transmit. In this work, we study how to optimally configure RAW in a scenario with a high number of energy harvesting sensor devices. For such a scenario, we consider a problem of device grouping and develop a model of data transmission, which takes into account the peculiarities of channel access and the fact that the devices can run out of energy within the allocated intervals. We show how to use the developed model in order to determine the optimal duration of RAW intervals and the optimal number of groups that provide the required probability of data delivery and minimize the amount of consumed channel resources. The numerical results show that the optimal RAW configuration can reduce the amount of consumed channel resources by almost 50%. Full article
(This article belongs to the Special Issue Sensors and Systems with Energy Harvesting)
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19 pages, 720 KiB  
Article
Outage Analysis of Parasitic Ambient Backscatter Communication in Decode-and-Forward Relay Networks with SWIPT
by Yanhong Tuo and Chao Zhang
Sensors 2020, 20(5), 1273; https://doi.org/10.3390/s20051273 - 26 Feb 2020
Cited by 5 | Viewed by 2073
Abstract
In this paper, we investigate the outage performance of simultaneous wireless information and power transfer (SWIPT) based Decode-and-Forward (DF) relay networks, where the relay needs to simultaneously forward information for two relaying links, primary relaying link and parasitic relaying link. The primary relaying [...] Read more.
In this paper, we investigate the outage performance of simultaneous wireless information and power transfer (SWIPT) based Decode-and-Forward (DF) relay networks, where the relay needs to simultaneously forward information for two relaying links, primary relaying link and parasitic relaying link. The primary relaying link is the traditional source-relay-destination relay system. While in the parasitic relaying link, the parasitic source, i.e., Internet-of-Things (IoT) tag, is not connected to the stable power source and thus has to backscatter the signals from the primary source to convey its information. The relay not only harvests energy from Radio Frequency (RF) signals from both sources but also forwards messages to their corresponding destinations. The primary source and destination are unaware of the parasitic backscatter transmission, but the relay and parasitic destination can employ successive interference cancellation (SIC) detector to eliminate the interference from the primary link and detect the message from the parasitic source. In order to investigate the interplay between the primary and parasitic relaying links, the outage probabilities of both relaying links are derived. Besides, the effects of system parameters, i.e., power splitting coefficient, forwarding power allocation coefficient and backscatter reflection coefficient, on the system performance are discussed. Simulation results verify our theoretical analysis. In the meanwhile, it is revealed that the advised relaying system has far larger sum throughput than the one with only primary relaying link and the parasitic relaying link can gain considerable throughput at the cost of negligible degradation of primary throughput. Full article
(This article belongs to the Special Issue Sensors and Systems with Energy Harvesting)
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18 pages, 3787 KiB  
Article
Investigation and Modeling of Multi-Node Body Channel Wireless Power Transfer
by Yuxuan Huang, Jian Zhao, Wenyu Sun, Huazhong Yang and Yongpan Liu
Sensors 2020, 20(1), 156; https://doi.org/10.3390/s20010156 - 25 Dec 2019
Cited by 3 | Viewed by 2122
Abstract
Insufficient power supply is a huge challenge for wireless body area network (WBAN). Body channel wireless power transfer (BC-WPT) is promising to realize multi-node high-efficiency power transmission for miniaturized WBAN nodes. However, the behavior of BC-WPT, especially in the multi-node scenario, is still [...] Read more.
Insufficient power supply is a huge challenge for wireless body area network (WBAN). Body channel wireless power transfer (BC-WPT) is promising to realize multi-node high-efficiency power transmission for miniaturized WBAN nodes. However, the behavior of BC-WPT, especially in the multi-node scenario, is still lacking in research. In this paper, the inter-degeneration mechanism of a multi-node BC-WPT is investigated based on the intuitive analysis of the existing circuit model. Co-simulation in the Computer Simulation Technology (CST) and Cadence platform and experiments in a general indoor environment verify this mechanism. Three key factors, including the distance between the source and the harvester, frequency of the source, and area of the ground electrodes, are taken into consideration, resulting in 15 representative cases for simulation and experiments studies. Based on the simulation parameters, an empirical circuit model to accurately predict the received power of multiple harvesters is established, which fits well with the measurement results, and can further provide guidelines for designs and research on multi-node BC-WPT systems. Full article
(This article belongs to the Special Issue Sensors and Systems with Energy Harvesting)
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