Energy Income Estimation for Solar Cell Powered Wireless Sensor Nodes

Mehne, Philipp; Leclerc, Dominik; Woias, Peter

doi:10.3390/proceedings2131514

Cited by 2 publications

(3 citation statements)

References 3 publications

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“…In the output of the current feedback amplifier, a resistance (R), a compensation capacitor (C eq1 ), and the selected transmitting coil (L 1c ) are connected in series. The resonance compensation capacitors on the resonant frequency of 140 kHz of both sides are Energies 2020, 13, 1244 6 of 23 obtained based on Equation (8). The current (I s ) generated by the proposed supply circuit depends on the generated voltage level and the connected load value as shown in Equation (9), which is maximal in the case of pure resonance.…”

Section: Design Of the Primary Side Multi-input Single Output Wirelesmentioning

confidence: 99%

“…Nowadays, the development of wireless sensor nodes (WSN) [1] has progressed from the implementing wake-up technologies [2] to the realization of even battery-free WSNs with low energy consumption. Battery-free based WSNs themselves can be supplied either by wireless power transfer (WPT) [3,4] or by adopting energy harvesting techniques to collect energy from one or several ambient sources [5][6][7][8]. However, energy harvesting solutions strongly depend on the availability of the ambient source in a certain environment and requires often a storage element, which help to over bridge periods of low energy availability.…”

Section: Introductionmentioning

confidence: 99%

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Multiplexed Supply of a MISO Wireless Power Transfer System for Battery-Free Wireless Sensors

et al. 2020

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Multi-input single output wireless power transmission (MISO-WPT) systems have decisive advantages concerning flexible receiver position in comparison to single coil systems. However, the supply of the primary side brings a large uncertainty in case of variable positions of the secondary side. In this paper, a compact multiplexed primary side electronic circuit is proposed, which includes only one signal generator, a passive peak detector, a communication module, and a compensation capacitor. The novel approach has been studied and evaluated for a MISO-WPT system having a 16 coils on primary side and one coil on secondary side having the double diameter. Results show that a standard microcontroller, in this case an STM32, is sufficient for the control of the whole system, so that the costs and the energy consumption are significantly reduced. An activation strategy has been proposed, which allows to determine the optimal transmitting coil for each position of the receiving coil and to switch it on. The time-to-start-charging at different positions of the receiving coil and different number of neighbors has been determined. It remains in all cases under 2.5 s.This reduces the size of the supply circuit relative to the previous solutions. In [19], a multi-coil system with multiplexed solution is presented with a singular supply circuit. However, the selection of the appropriate coil requires dual MOSFET switches, which presents some similarity to a switch-based multi-coil system. Nevertheless, the control of the multi-coil system switches needs microcontrollers with a high number of pins. For that, in case of a big number of transmitting coils, an FPGA [22] is proposed as processing unit, leading to an increase of both energy consumption and costs.In this paper, we investigate the feasibility of a multiplexed circuit on the primary side supply approach, with the aim to reduce the circuit size and to control the system by a simple microcontroller with a limited number of pins. The main objective is to significantly decrease both energy consumption and system costs. To this end, we propose to use receiving coils having the double diameter of the transmitting coils. This is important to cover at least a singular transmitting coil for different possible positions on the top of the pad to power the device for all the possible positions. In order to enable the detection and the powering of even battery-free wireless sensor nodes, we propose that the communication between the transmitting and receiving coil is started from the transmitting side and supplied from the transferred energy on the secondary side.The paper is organized as follows: In Section 2, the primary side supply circuit for a system is presented. The description of the proposed multi-coil system control algorithm is detailed in Section 3. The experimental evaluation of the developed algorithm are reported in Section 4. Section 5 shows the analysis of the required time to start the charging process. A conclusion is provided in Section 6. Design of the Primar...

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Section: Design Of the Primary Side Multi-input Single Output Wirelesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiplexed Supply of a MISO Wireless Power Transfer System for Battery-Free Wireless Sensors

et al. 2020

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“…This energy is counted as a nonfixed supplying energy [9,10]. Against this problem, predicting solar harvested energy has been adopted to overcome this obstacle [11]. In this regard, the prediction was used to fulfill an advanced knowledge about the collected energy to be a help index for organizing the operation of the sensor units in a way that ensures effective and sustainable work.…”

Section: Introductionmentioning

confidence: 99%

Optimal Neural Network for Predicting Solar Energy in Sensor Units Based on a Cascaded Input/Structure Direct Optimization

et al. 2022

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The sensor units are considered one of the significant technologies that use solar energy as an assistant power source to the batteries. Despite their advantages over the other forms of renewables, solar energy has an intermittent nature which negatively affects the operation of these units. Reaching an effective operation ensuring sustainable units requires a prior prediction of the harvested solar energy. Artificial neural networks (ANNs) appeared recently as a promising prediction approach with those units. This is attributed to the high accuracy compared to the conventional stochastic and statistical ones. Till now, the optimal neural network that fits with sensor units has not been precisely determined. This paper is aimed at finding the optimal neural network that would be applied with solar-supplied sensor units. This is performed by applying a cascaded input/structure direct optimization. The optimization process handles the aspects of accuracy, computational efforts, and complexity. It mainly identifies the type and number of parameters that would be utilized as inputs in the first stage. Then, it optimizes the structure by addressing the number of hidden layers and hidden neurons. The corresponding analysis has been implemented for premeasured real data over five-year time period. The results showed that the optimal neural network can be achieved by using three input parameters which are the air temperature (AT), the relative humidity (RH), and the zenith angle ( θ z ). For the structure, it has been concluded that the proposed optimal ANN should have two hidden layers with ten neurons in each of them. Lastly, the proposed optimal ANN was verified against the associated prediction error which is minimized to less than 2%.

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Energy Income Estimation for Solar Cell Powered Wireless Sensor Nodes

Cited by 2 publications

References 3 publications

Multiplexed Supply of a MISO Wireless Power Transfer System for Battery-Free Wireless Sensors

Multiplexed Supply of a MISO Wireless Power Transfer System for Battery-Free Wireless Sensors

Optimal Neural Network for Predicting Solar Energy in Sensor Units Based on a Cascaded Input/Structure Direct Optimization

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