Wireless sensor network with energy harvesting: modeling and simulation based on a practical architecture using real radiation levels

Climent, Salvador; Sanchez, Alberto; Clavero, Sara; Capella, J.V.; Ors, R.

doi:10.1002/cpe.3151

Cited by 16 publications

(13 citation statements)

References 29 publications

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“…The first stage uses super capacitors to store energy, and the second stage uses lithium batteries to store energy. The management circuit in the circuit is mainly responsible for managing the charging and discharging of the lithium batteries, but cannot carry on the MPPT to the solar energy, and has not realized the full use of energy [1]. Compared with Prometheus system, C. Park and some scholars designed AmbiMax, which makes use of the method of maximum power point tracking to store the solar panel output energy in the capacitor, and the system also collects wind power for the charging of the super capacitors [2,3].…”

Section: Literature Reviewmentioning

confidence: 99%

Design of Solar Power Management Circuit Based on Wireless Sensor Network

Jianying

2017

Int. J. Onl. Eng.

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Abstract-To explore the design of solar power management circuit, the fuzzy logic control algorithm based on MPPT, which has fast control speed and good environment robustness, is adopted as the control algorithm. In addition, the MPPT solar battery charge and discharge power management circuit is designed and successfully applied in the on-line measurement projects of dielectric loss of wireless sensor network in Jilin Province LG Electronics Company. The results show that the charging efficiency of solar battery charge and discharge power management circuit can reach above 80%, and the current of static power management circuit is less than 1mA. In different light intensities, the dynamic power management is intelligently carried out. At last, it is concluded that the stability and reliability of circuit are quite high.Keywords-Wireless sensor, power management, circuit design IntroductionIn the research on solar power supply, the control algorithms of MPPT in the past are divided into the following three categories: indirect control method based on parameter selection, direct control method based on sampled data, and intelligent control method based on modern control theory. Among them, the algorithm based on parameter selection is comparatively simple, but it cannot adapt to the influence of environment change on the parameters of solar panel. The control method based on sampled data is dynamic, which makes the maximum power point tracking according to environmental conditions, but the tracking is too slow. The MPPT algorithm based on the modern control theory makes up for the shortcomings of the above two algorithms, and it can achieve better maximum power point tracking. Compared with the previous two algorithms, this algorithm is more complex. Fuzzy logic control algorithm has the characteristics of fast control speed, good environment robustness and simple algorithm realization. As a result, it is chosen as the control algorithm for further study.

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Section: Literature Reviewmentioning

confidence: 99%

Design of Solar Power Management Circuit Based on Wireless Sensor Network

Jianying

2017

Int. J. Onl. Eng.

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“…However, this only models the behaviour of the battery operating alternately — that is, in the charge or discharge modes. The authors in Reference presented a new energy‐harvesting model for a network simulator in the context of Wireless Sensor Networks (WSNs). This model is based on a typical energy‐harvesting circuit, calculating and managing the available energy on the actual capacitor, and taking into account its voltage, the current provided by a solar panel, and the current consumed by the system.…”

Section: Introductionmentioning

confidence: 99%

An analytical model to estimate the state of charge and lifetime for batteries with energy harvesting capabilities

et al. 2020

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Energy limitation is one of the major bottlenecks during the operation of many emerging applications, such as electric vehicles, water and gas meters and a number of sensors used in the context of the Internet of Things and cyberphysical systems. Energy harvesting techniques have arisen as a promising solution to minimize the energy issues found in these types of application domains. In energy harvesting systems, a critical challenge is the need to use battery models capable of accurately estimating both the input and output power of batteries. This article proposes a temperature-dependent analytical battery model capable of estimating some output quantitiesfor example, state of charge, voltage and lifetimeof batteries that use energy harvesting technologies. This model was validated by comparing its analytical results with a dataset called the Randomized Battery Usage Data Set, which is available at the data repository of the National Aeronautics and Space Administration (NASA) website. It is also presented a proof-of-concept application, demonstrating that the use of these technologies can serve as an effective means to extend the operating time of batteries, resulting in significant benefits for a number of applications. K E Y W O R D Swireless sensor network, battery modelling, energy harvesting, thermal effect

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“…In WSNs, the use of simulation has been deeply explored by several authors in the last ten years [6][7][8][9][10][11][12]. However, realistic simulation requires an accurate model not only of the EH device but also of every hardware component involved in the system plus a fast and accurate model of the communication channel.…”

Section: Introductionmentioning

confidence: 99%

A fast and accurate energy source emulator for wireless sensor networks

et al. 2016

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The capability to either minimize energy consumption in battery-operated devices, or to adequately exploit energy harvesting from various ambient sources, is central to the development and engineering of energy-neutral wireless sensor networks. However, the design of effective networked embedded systems targeting unlimited lifetime poses several challenges at different architectural levels. In particular, the heterogeneity, the variability, and the unpredictability of many energy sources, combined to changes in energy required by powered devices, make it difficult to obtain reproducible testing conditions, thus prompting the need of novel solutions addressing these issues. This paper introduces a novel embedded hardware-software solution aimed at emulating a wide spectrum of energy sources usually exploited to power sensor networks motes. The proposed system consists of a modular architecture featuring small factor form, low power requirements, and limited cost. An extensive experimental characterization confirms the validity of the embedded emulator in terms of flexibility, accuracy, and latency while a case study about the emulation of a lithium battery shows that the hardware-software platform does not introduce any measurable reduction of the accuracy of the model. The presented solution represents therefore a convenient solution for testing large-scale testbeds under realistic energy supply scenarios for wireless sensor networks.

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Wireless sensor network with energy harvesting: modeling and simulation based on a practical architecture using real radiation levels

Cited by 16 publications

References 29 publications

Design of Solar Power Management Circuit Based on Wireless Sensor Network

Design of Solar Power Management Circuit Based on Wireless Sensor Network

An analytical model to estimate the state of charge and lifetime for batteries with energy harvesting capabilities

A fast and accurate energy source emulator for wireless sensor networks

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