An Electro-Magnetic Energy Harvesting System With 190 nW Idle Mode Power Consumption for a BAW Based Wireless Sensor Node

2011 ◽  
Vol 46 (7) ◽  
pp. 1728-1741 ◽  
Author(s):  
Hannes Reinisch ◽  
Stefan Gruber ◽  
Hartwig Unterassinger ◽  
Martin Wiessflecker ◽  
Günter Hofer ◽  
...  
2016 ◽  
Vol 3 (3) ◽  
Author(s):  
Fariborz Entezami ◽  
Meiling Zhu ◽  
Christos Politis

AbstractThere is a big challenge for research and industrial engineers to apply energy harvesting powered wireless sensors for practical applications. This is because wireless sensors is very power hungry while current energy harvesting systems can only harvest very limited energy from the ambient environment. In order for wireless sensors to be operated based on the limited energy harvested, understanding of power consumption of wireless sensors is the first task for implementation of energy harvesting powered wireless sensors systems. In this research an energy consumption model has been introduced for wireless sensor nodes and the power consumption in the life cycle of wireless communication sensors, consisting of JN5148 microcontroller and custom built sensors: a 3-axial accelerometer, a temperature sensor and a light sensor, has been studied. All measurements are based on a custom-built test bed. The power required carrying out a life cycle of wireless sensing and transmission is analysed. This paper describes how to analyse the current consumption of the system in active mode and thus power Consumption for sleeping and deployed sensors mode. The results show how much energy needs to run the energy harvesting powered wireless sensor node with JN5148 microcontroller.


Author(s):  
Haiying Huang ◽  
Yayu Hew

This paper presents the implementation and characterization of a low power wireless vibration sensor that can be powered by a flash light. The wireless system consists of two components, namely the wireless sensor node and the wireless interrogation unit. The wireless sensor node includes a wireless strain gauge that consumes around 6 mW, a signal modulation circuit, and a light energy harvesting unit. To achieve ultra-low power consumption, the signal modulation circuit was implemented using a voltage-controlled oscillator (VCO) to convert the strain gauge output to an intermediate frequency (IF) signal, which is then used to alter the impedance of the sensor antenna and thus achieves amplitude modulation of the backscattered antenna signal. A generic solar panel with energy harvesting circuit is used to power the strain sensor node continuously. The wireless interrogation unit transmits the interrogation signal and receives the amplitude modulated antenna backscattering, which can be down-converted to recover the IF signal. In order to measure the strains dynamically, a Phase Lock Loop (PLL) circuit was implemented at the interrogator to track the frequency of the IF signal and provide a signal that is directly proportional to the measured strain. The system features ultra-low power consumption, complete wireless sensing, solar powering, and portability. The application of this low power wireless strain system for vibration measurement is demonstrated and characterized.


A novel self-powered wireless sensor node is proposed and prototyped to overcome the ambient energy lacking in the dual energy harvesting sources by including a secondary energy storage. Moreover, an energy-aware Event-Priority-Driven Dissemination (EPDD) management algorithm has been developed and implemented to control the WSN integrity and reducing the sensor node power consumption as well. EPDD was developed to manage the sensor node operation and to make the sink station able to detect a missing wireless node within the network, which will guarantee the nodes integrity detection. The evaluations revealed that the EPDD shows a good performance in reducing the node power consumption compared to the data push algorithm, whereby, EPDD node was operating 4 hours more than the data push node on the same power source. Regarding the WSN integrity, the EPDD algorithm outpaced the event trigger algorithm, whereby, the EPDD was easily able to detect a node down within the WSN at the contrary of the event trigger.


Author(s):  
Hannes Reinisch ◽  
Stefan Gruber ◽  
Martin Wiessflecker ◽  
Hartwig Unterassinger ◽  
Gunter Hofer ◽  
...  

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