Modern terahertz (THz) technology offers the advantage of enhanced target detection ability with high spatial and temporal resolutions in the THz band, which makes it a formidable threat to stealth targets. Consequently, THz absorbers have outstanding potential as an electromagnetic countermeasure. In this Letter, we design, fabricate, and characterize a THz absorber based on patterned graphene. We present the transfer, photolithography, and etching processes involved in graphene patterning, as well as the experimental measurements of the fabricated absorber. Our simulations show that with an increase in the Fermi energy, the performance of the designed absorber gradually improves and, finally, decreases slightly. Further, the absorption bandwidth first broadens and then narrows slightly. The effective bandwidth with absorption ≥90% ranges from 1.54 to 2.23 THz, with the relative bandwidth (RBW) reaching about 36.6%. Although the measured RBW (from ∼12% to ∼14% and then to ∼8%) slightly deviates from the simulated one, the position of the resonant frequency is well matched between theory and experiment. Moreover, we illuminate the absorption mechanism using the theory of destructive interference. This Letter can significantly contribute to the design, manufacture, and application of patterned graphene-based THz absorbers.
The state of charge (SOC) of power battery is an important parameter of battery state, and it plays a vital role in real-time accurate estimation, condition monitoring, improving battery life, and ensuring the safety of power supply. This paper presents the grey neural network model of the relation between the battery SOC and rebound voltage, discharge current. Based on this model, a new on-line SOC detection method using rebound voltage and discharge current in the discharge process is proposed. From the testing results, the model and algorithm were proved to be feasible and effective, and the estimated error is controlled within a range of ±8%.
Based on the advantage of battery energy storage system (BESS), which can work in four quadrants, it is proposed to utilize BESS to suppress low-frequency oscillation. Derive the model with BESS and make the simulation by using the Matlab. Simulation results show energy storage devices can effectively improve the system stability and increase the system damping when they are installed in the appropriate position.
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