In this paper, an ultra-wideband and polarization-independent metasurface for radar cross section (RCS) reduction is proposed. The unit cell of the metasurface operates in a linear cross-polarization scheme in a broad band. The phase and amplitude of cross-polarized reflection can be separately controlled by its geometry and rotation angle. Based on the diffuse reflection theory, a 3-bit coding metasurface is designed to reduce the RCS in an ultra-wide band. The wideband property of the metasurface benefits from the wideband cross polarization conversion and flexible phase modulation. In addition, the polarization-independent feature of the metasurface is achieved by tailoring the rotation angle of each element. Both the simulated and measured results demonstrate that the proposed metasurface can reduce the RCS significantly in an ultra-wide frequency band for both normal and oblique incidences, which makes it promising in the applications such as electromagnetic cloaking.

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To facilitate voltage matching between the cell stack and power batteries in fuel-cell-powered vehicles, an implementation of a simple dual-switch boost DC-DC converter topology has been proposed in this paper. Compared with existing boost topologies, the one proposed herein reduces the number of components required and stress induced whilst maintaining a high-gain ratio. The results of experiments performed in this paper reveal that the corresponding to a duty ratio of 0.8, the proposed converter topology demonstrates the realization of a boost ratio of 6, thereby exceeding that the realized by conventional boost converters by nearly 73%. In addition, at an output voltage of 50 V, a maximum operating efficiency of 91% was achieved. These results demonstrate the effectiveness and feasibility of the proposed DC-DC converter topology for use in fuel-cell-powered vehicles.INDEX TERMS Fuel cell, DC/DC converter, topology, high gain ratio.

While both periodic narrowband noise and white noise are significant sources of interference in the detection and localization of partial discharge (PD) signals in power cables, existing research has focused nearly exclusively on white noise suppression. This paper addresses this issue by proposing a new signal extraction method for effectively detecting random PD signals in power cables subject to complex noise environments involving both white noise and periodic narrowband noise. Firstly, the power cable signal was decomposed using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and the periodic narrowband noise and frequency aliasing in the obtained signal components were suppressed using singular value decomposition. Then, signal components contributing significantly to the PD signal were determined according to the cross-correlation coefficient between each component and the original PD signal, and the PD signal was reconstructed solely from the obtained significant components. Finally, the wavelet packet threshold method was used to filter out residual white noise in the reconstructed PD signal. The performance of the proposed algorithm was demonstrated by its application to synthesized PD signals with complex noise environments composed of both Gaussian white noise and periodic narrowband noise. In addition, the time-varying kurtosis method was demonstrated to accurately determine the PD signal arrival time when applied to PD signals extracted by the proposed method from synthesized signals in complex noise environments with signal-to-noise ratio (SNR) values as low as −6 dB. When the SNR was reduced to −23 dB, the arrival time error of the PD signal was only one sampling point.

Abstract:In order to optimize the charging of lithium-ion batteries, a multi-stage charging method that considers the charging time and energy loss as optimization targets has been proposed in this paper. First, a dynamic model based on a first-order circuit has been established, and the model parameters have been identified. Second, on the basis of the established model, we treat the objective function of the optimization problem as a weighted sum of charging time and energy loss. Finally, a dynamic programming algorithm (DP) has been used to calculate the charging current of the objective function. Simulation and experimental results show that the proposed charging method could effectively reduce the charging time and decrease the energy loss, compared with the constant-current constant-voltage charging method, under the premise of exerting little influence on the attenuation of battery capacity.

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