With the rise of the Internet of Things (IoT), ambient vibration energy harvesting technology using piezoelectric transducers has drawn much research interest in realizing the power supply for wireless sensor networks (WSNs). To improve the efficiency of energy harvesting, an interface circuit is required to operate energy management action. The synchronized switch harvesting on inductor (SSHI) method is the most efficient method of extracting energy from the piezoelectric transducer. This paper presents a self-powered piezoelectric energy harvesting (PEH) interface circuit, which integrates a SSHI rectifier with self-adaptive switch control. The proposed circuit includes an active diode in each LC resonant tank to reduce the reverse current of the inductor. The SSHI rectifier, therefore, has high adaptability to external inductors and piezoelectric transducers. The switch control circuit of this paper is directly powered by the rectified voltage to avoid an external power supply for higher integration. Compared with the conventional SSHI rectifier, the proposed implementation achieves high voltage flipping efficiency with a small flipping inductor. The proposed circuit is designed in 180nm CMOS process, and the chip area is 0.163mm2. The simulation result shows that the proposed circuit achieves cold start-up operation without any external power supply and can work with high efficiency when the external inductor is varying from 1 to 1000μH. The simulated maximum output power of the proposed design is 2.5× higher than that of the ideal full-bridge rectifier.
Today's technology has allowed us to have within our reach services and experiences that previously could only be offered by specialized centers due to their high cost of manufacture and acquisition. Therefore, there are devices with which it is possible to monitor our cardiac system, inadequate postures, muscular ailments and nervous activity, among others. Now that our habits have changed and work and studies are done from home due to the pandemic that happened, it is common to suffer ailments in various parts of our body, most commonly in the back, for this reason it is necessary to adopt healthy habits such as a correct body posture in order to reduce the risks related to our spine and the development of injuries that derive from this. This scientific article deals with the design, simulation and construction of a low-cost IoT posture corrector, with commercial electronic materials, its effectiveness was evaluated through the analysis of cost-benefit, comfort and efficiency of the device by means of a perception of part of some tests performed to a total of 12 people during the period of 8 weeks. Satisfactory results were obtained with 75% comfort of use and 75% effectiveness by means of a rating scale evaluation.
Wireless receivers with multiple modes and standards require highly linear Pre-filters to prevent strong out-of-band blocker signals from corrupting in-band signals. A prefaced SAW(surface acoustic wave) filter needed in conventional receiver structures is neither tunable nor fully integrated. However, when the multiple frequency bands demand to be supported, the combination of multiple SAW filters increases the circuit's size and cost. This paper introduces a fully integrated, reconfigurable wideband wireless receiver based on N-path technology. The circuit utilizes 65nm CMOS technology and applies the Gain-Boosted approach to reduce the noise factor to 3.3dB. The out-of-band suppression ability of the circuit is improved by N-path technology, and the out-of-band IIP3 is up to +33.51dBm. The circuit's power consumes 46-72mW at 0.5-2GHz frequency, and the layout area is 700*1000μm2.
Network status prediction and efficient routing play important roles in low earth orbit (LEO) satellite networks. It is necessary to establish an accurate network model for state prediction in LEO satellite networks with high mobility. According to the predicted state, route planning is needed to satisfy requirements. In this work, we propose a satellite network state prediction and route planning method combining the Message Passing Neutral Network (MPNN) algorithm and Q-Leaning. Firstly, a network topology establishment method is proposed based on the idea of Virtual Node (VN). Then, the satellite network status is accurately predicted based on the MPNN algorithm with the attention mechanism. Q-Learning is further applied to obtain the optimal routing path after prediction. Finally, through simulation experiments, the accuracy and generalization of our algorithm is verified, and the route policy can be obtained.
This paper proposes a power flow analytical technique for a networked microgrid for grid-connected and islanded operations. This technique is convenient for solving the power flow of different topologies due to the changes in the switching status of interconnected switches in the planning and operating stages. Furthermore, it can be used to calculate the bus voltage, line flow, and system loss for scheduling and dispatching the battery energy storage system in energy management systems. First, the bus and branch data of the sample system were established in the OpenDSS software. Next, the load, photovoltaic, and the battery energy storage system data from the database were obtained from the metering system. Second, the OpenDSS, InfluxDB database, and Grafana web-based visualization tool programs were integrated with Python language. Then, the OpenDSS can solve the power flow after the switching state is changed. Finally, the proposed approach was used to solve the power flow of a networked microgrid under different operating conditions. The numerical results demonstrate that the proposed analytical technique helps solve the power flow of networked microgrids.
