scholarly journals A Nonlinear Electromagnetic Energy Harvesting System for Self-Powered Wireless Sensor Nodes

2019 ◽  
Vol 8 (1) ◽  
pp. 18 ◽  
Author(s):  
Kankan Li ◽  
Xuefeng He ◽  
Xingchang Wang ◽  
Senlin Jiang

The Internet of things requires long-life wireless sensor nodes powered by the harvested energy from environments. This paper proposes a nonlinear electromagnetic energy harvesting system which may be used to construct fully self-powered wireless sensor nodes. Based on a nonlinear electromagnetic energy harvester (EMEH) with high output voltage, the model of a nonlinear interface circuit is derived and a power management circuit (PMC) is designed. The proposed PMC uses a buck–boost direct current-direct current (DC–DC) converter to match the load resistance of the nonlinear interface circuit. It includes two open-loop branches, which is beneficial to the optimization of the impedance matching. The circuit is able to work even if the stored energy is completely drained. The energy harvesting system successfully powered a wireless sensor node. Experimental results show that, under base excitations of 0.3 g and 0.4 g (where 1 g = 9.8 m·s−2) at 8 Hz, the charging efficiencies of the proposed circuit are 172% and 28.5% higher than that of the classic standard energy-harvesting (SEH) circuit. The experimental efficiency of the PMC is 41.7% under an excitation of 0.3 g at 8 Hz.

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Yuan Dong ◽  
Dezhi Li ◽  
Benjamin Ducharne ◽  
Xiaohui Wang ◽  
Jun Gao ◽  
...  

Energy harvesting for self-powered wireless sensor networks (WSNs) is increasingly needed. In this paper, a self-powered WSN node scenario is proposed and realized by coupling the electric charge extraction interface circuit, power management module, and wireless communication module. Firstly, the output power of an optimized self-powered energy extraction circuit is compared with different energy extraction circuits under various loads and excitation amplitudes theoretically. Then, an energy-harvesting setup is established to validate the load-carrying capacity and working condition of the self-powered optimized synchronized switch harvesting on inductor (SP-OSSHI) circuit. It gives guidance to select and estimate the appropriate energy-consuming level for the sensor and modules. Finally, by connecting the energy-harvesting system, power management element, and sensing part together, a self-powered wireless sensor node is accomplished. Under 18 Hz resonant excitation, the whole self-powered system transmits 32 bytes of data every 30 seconds including the acceleration and environment temperature. This prototype strongly proves the feasibility of the self-powered WSN node. These research results have potential to be used in different application fields.


2016 ◽  
Vol 249 ◽  
pp. 77-84 ◽  
Author(s):  
Salar Chamanian ◽  
Hasan Uluşan ◽  
Özge Zorlu ◽  
Sajjad Baghaee ◽  
Elif Uysal-Biyikoglu ◽  
...  

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881446 ◽  
Author(s):  
Mingyuan Gao ◽  
Yunwu Li ◽  
Jun Lu ◽  
Yifeng Wang ◽  
Ping Wang ◽  
...  

The goal of this study is to develop a vibration-based electromagnetic energy harvesting prototype that provides power to rail-side monitoring equipment and sensors by collecting wheel-rail vibration energy when the train travels. This technology helps power rail–side equipment in off-grid and remote areas. This article introduces the principle, modeling, and experimental test of the system, including (1) an electromagnetic energy harvesting prototype with DC-DC boost converter and lithium battery charge management function, (2) wireless sensor nodes integrated with accelerometer and temperature/humidity sensor, and (3) a vehicle-track interaction model that considers wheel out-of-roundness. Field test results, power consumption, Littlewood–Paley wavelet transform method, and feasibility analysis are reported. An application case of the technology is introduced: the sensor nodes of the wireless sensor network are powered by the electromagnetic energy harvester and lithium battery with DC-DC boost converter, thereby continuously monitoring the railway track state; based on the Littlewood–Paley wavelet analysis of measured railway track acceleration data, the abnormal signal caused by the wheel out-of-roundness can be detected.


Energies ◽  
2014 ◽  
Vol 7 (10) ◽  
pp. 6323-6339 ◽  
Author(s):  
Salar Chamanian ◽  
Sajjad Baghaee ◽  
Hasan Ulusan ◽  
Özge Zorlu ◽  
Haluk Külah ◽  
...  

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