scholarly journals Wireless Battery Charging Circuit Using Load Estimation Without Wireless Communication

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4489
Author(s):  
Lee ◽  
Choi ◽  
Kim ◽  
Kang

A wireless battery charging circuit is proposed, along with a new load estimation method. The proposed estimation method can predict the load resistance, mutual inductance, output voltage, and output current without any wireless communication between the transmitter and receiver sides. Unlike other estimation methods that sense the high-frequency AC voltage and current of the transmitter coil, the proposed method only requires the DC output value of the peak current detection circuit at the transmitter coil. The proposed wireless power transfer (WPT) circuit uses the estimated parameters, and accurately controls the output current and voltage by adjusting the switching phase difference of the transmitter side. The WPT prototype circuit using a new load estimation method was tested under various coil alignment and load conditions. Finally, the circuit was operated in a constant current and constant voltage modes to charge a 48-V battery pack. These results show that the proposed WPT circuit that uses the new load estimation method is well suited for charging a battery pack.

2021 ◽  
Vol 5 (4) ◽  
pp. 334-341
Author(s):  
D Venkata Ratnam ◽  
◽  
K Nageswara Rao ◽  

<abstract> <p>The advanced neural network methods solve significant signal estimation and channel characterization difficulties in the next-generation 5G wireless communication systems. The number of transmitted signal copies received through multiple paths at the receiver leads to delay spread, which intern causes interference in communication. These adverse effects of the interference can be mitigated with the orthogonal frequency division modulation (OFDM) technique. Furthermore, the proper signal detection methods optimal channel estimation enhances the performance of the multicarrier wireless communication system. In this paper, bi-directional long short-term memory (Bi-LSTM) based deep learning method is implemented to estimate the channel in different multipath scenarios. The impact of the pilots and cyclic prefix on the performance of Bi LSTM algorithm is analyzed. It is evident from the symbol-error rate (SER) results that the Bi-LSTM algorithm performs better than the state of art channel estimation methods known as the Minimum Mean Square and Error (MMSE) estimation method.</p> </abstract>


2013 ◽  
Vol 50 (3) ◽  
pp. 791-804 ◽  
Author(s):  
Sébastien Raymond ◽  
Alain Mailhot ◽  
Guillaume Talbot ◽  
Patrick Gagnon ◽  
Alain N. Rousseau ◽  
...  

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.


2019 ◽  
pp. 56-61
Author(s):  
Huang ChunXiang ◽  
Henadiy Pavlov ◽  
Mykhailo Pokrovskyi ◽  
Andriy Obrubov ◽  
Iryna Vinnychenko

The research object is the electromagnetic processes in the semiconductor power converters based on the schemes with circuit commutation and containing resonant circuits of reactive elements and transformers with a small coupling coefficient. The research aim is to develop a technology for a fast wireless battery charging for the use in clean energy vehicles, which would be based on a resonant converter with a pulse-count adjustment with a phase shift control. The latter provides a high energy performance in a wide range of regulation and a low sensitivity to changes in the magnetic system parameters. This is a final report. The report presents the results of the work performed in accordance with the Terms of Reference for the second stage of the scientific and research work. The following theoretical problems have been solved: development of a mathematical model of a series resonant converter with a pulse-count adjustment for contactless inductive energy transmission, which provided a high accuracy for the studies of the electromagnetic processes in the power section of multi-circuit resonant converters for contactless energy transmission, as well as an opportunity to assess the energy parameters of multi-circuit converters at pulse-count adjustment; compilation of mathematical dependencies of the average input and output current values on the number of half-cycles of resonant oscillations during energy transmission to the circuit and energy dissipation, the supply voltage and the resonant circuit’s parameters, which allowed assessing the converter’s energy parameters over a wide control range; compilation of the dependencies of the converter’s output power and coefficient of efficiency on the number of halfcycles of resonant oscillations during energy transmission to the circuit and energy dissipation, on supply voltage and on the resonant circuit’s parameters, which made it possible to evaluate the efficiency of the pulse-count adjustment of resonant converters for contactless energy transmission; realization of a dynamic model of a resonant converter for contactless energy transmission in the form of transfer functions for small disturbances caused by fluctuations in supply voltage, which made it possible to estimate the effect of its instability on the quality of output current stabilization.


Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 26
Author(s):  
David González-Ortega ◽  
Francisco Javier Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez

Driver’s gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens the scope of research studies as they can relate drivers’ gaze patterns to their features and performance. In this paper, we present two gaze region estimation modules integrated in a driving simulator. One uses the 3D Kinect device and another uses the virtual reality Oculus Rift device. The modules are able to detect the region, out of seven in which the driving scene was divided, where a driver is gazing at in every route processed frame. Four methods were implemented and compared for gaze estimation, which learn the relation between gaze displacement and head movement. Two are simpler and based on points that try to capture this relation and two are based on classifiers such as MLP and SVM. Experiments were carried out with 12 users that drove on the same scenario twice, each one with a different visualization display, first with a big screen and later with Oculus Rift. On the whole, Oculus Rift outperformed Kinect as the best hardware for gaze estimation. The Oculus-based gaze region estimation method with the highest performance achieved an accuracy of 97.94%. The information provided by the Oculus Rift module enriches the driving simulator data and makes it possible a multimodal driving performance analysis apart from the immersion and realism obtained with the virtual reality experience provided by Oculus.


2021 ◽  
Vol 13 (15) ◽  
pp. 2862
Author(s):  
Yakun Xie ◽  
Dejun Feng ◽  
Sifan Xiong ◽  
Jun Zhu ◽  
Yangge Liu

Accurately building height estimation from remote sensing imagery is an important and challenging task. However, the existing shadow-based building height estimation methods have large errors due to the complex environment in remote sensing imagery. In this paper, we propose a multi-scene building height estimation method based on shadow in high resolution imagery. First, the shadow of building is classified and described by analyzing the features of building shadow in remote sensing imagery. Second, a variety of shadow-based building height estimation models is established in different scenes. In addition, a method of shadow regularization extraction is proposed, which can solve the problem of mutual adhesion shadows in dense building areas effectively. Finally, we propose a method for shadow length calculation combines with the fish net and the pauta criterion, which means that the large error caused by the complex shape of building shadow can be avoided. Multi-scene areas are selected for experimental analysis to prove the validity of our method. The experiment results show that the accuracy rate is as high as 96% within 2 m of absolute error of our method. In addition, we compared our proposed approach with the existing methods, and the results show that the absolute error of our method are reduced by 1.24 m-3.76 m, which can achieve high-precision estimation of building height.


Author(s):  
Wei Yue ◽  
Cong-zhi Liu ◽  
Liang Li ◽  
Xiang Chen ◽  
Fahad Muhammad

This work is focused on designing a fractional-order [Formula: see text] observer and applying it into the state of charge (SOC) estimation for lithium-ion battery pack system. Firstly, a fractional order equivalent circuit model based on the fractional capacitor is established and identified. Secondly, the SOC estimation method based on the fractional-order [Formula: see text] observer is proposed. The nonlinear intrinsic relationship between the open-circuit voltage and SOC is described as a polynomial function, and its Lipschitz proposition has been discussed. Then, the nonlinear observer design criterion is established based on the Lyapunov method. Finally, the effectiveness of the proposed method is verified with high accuracy and robustness by the experiment results.


Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 700
Author(s):  
Belén Pérez-Sánchez ◽  
Martín González ◽  
Carmen Perea ◽  
Jose J. López-Espín

Simultaneous Equations Models (SEM) is a statistical technique widely used in economic science to model the simultaneity relationship between variables. In the past years, this technique has also been used in other fields such as psychology or medicine. Thus, the development of new estimating methods is an important line of research. In fact, if we want to apply the SEM to medical problems with the main goal being to obtain the best approximation between the parameters of model and their estimations. This paper shows a computational study between different methods for estimating simultaneous equations models as well as a new method which allows the estimation of those parameters based on the optimization of the Bayesian Method of Moments and minimizing the Akaike Information Criteria. In addition, an entropy measure has been calculated as a parameter criteria to compare the estimation methods studied. The comparison between those methods is performed through an experimental study using randomly generated models. The experimental study compares the estimations obtained by the different methods as well as the efficiency when comparing solutions by Akaike Information Criteria and Entropy Measure. The study shows that the proposed estimation method offered better approximations and the entropy measured results more efficiently than the rest.


Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2436 ◽  
Author(s):  
Jiajia Jiang ◽  
Xianquan Wang ◽  
Fajie Duan ◽  
Chunyue Li ◽  
Xiao Fu ◽  
...  

The covertness of the active sonar is a very important issue and the sonar signal waveform design problem was studied to improve covertness of the system. Many marine mammals produce call pulses for communication and echolocation, and existing interception systems normally classify these biological signals as ocean noise and filter them out. Based on this, a bio-inspired covert active sonar strategy was proposed. The true, rather than man-made sperm whale, call pulses were used to serve as sonar waveforms so as to ensure the camouflage ability of sonar waveforms. A range and velocity measurement combination (RVMC) was designed by using two true sperm whale call pulses which had excellent range resolution (RR) and large Doppler tolerance (DT). The range and velocity estimation methods were developed based on the RVMC. In the sonar receiver, the correlation technology was used to confirm the start and end time of sonar signals and their echoes, and then based on the developed range and velocity estimation method, the range and velocity of the underwater target were obtained. Then, the RVMC was embedded into the true sperm whale call-train to improve the camouflage ability of the sonar signal-train. Finally, experiment results were provided to verify the performance of the proposed method.


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