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The detection of high frequency overvoltage and partial discharge is of great significance in evaluating the insulation condition of high-voltage power equipment. A wideband GHz electric field (E-field) sensor for electromagnetic pulse (EMP) signal measurement was proposed in this paper. An optical fiber transmission link was adopted in the design in order to implement high-voltage isolation and reduce electromagnetic interference during transmission. The designed sensor was mainly made up of a differential electric field (D-dot) antenna, transmitter, and receiver. The D-dot antenna was designed to detect high frequency E-field strength and generate a corresponding voltage signal, which was converted into an optical signal by the transmitter. The optical signal could be transmitted a large distance through an optical fiber without electromagnetic interference and changed back to a voltage signal again by a receiver. The design process of the sensor was introduced in detail, and experiments were performed using a gigahertz transverse electromagnetic (GTEM) cell and an EMP simulator to verify it. The results indicated that the designed sensor had a good performance besides an expectable delay due to the optional amplifier.

Lithium-ion batteries are an attractive power source in many scenarios. In some particular cases, including providing backup power for drones, frequency modulation, and powering electric tools, lithium-ion batteries are required to discharge at a high rate (2~20 C). In this work, we present a method to estimate the state of health (SOH) of lithium-ion batteries with a high discharge rate using the battery’s impedance at three characteristic frequencies. Firstly, a battery model is used to fit the impedance spectrum of twelve LiFePO4 batteries. Secondly, a basic estimation model is built to estimate the SOH of the batteries via the parameters of the battery model. The model is trained using the data of six batteries and is tested on another six. The RMS of relative error of the model is lower than 4.2% at 10 C and lower than 2.8% at 15 C, even when the low-frequency feature of the impedance spectrum is ignored. Thirdly, we adapt the basic model so that the SOH estimation can be performed only using the battery’s impedance at three characteristic frequencies without having to measure the entire impedance spectrum. The RMS of relative error of this adapted model at 10 C and 15 C is 3.11% and 4.25%, respectively.

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Lithium-bismuth liquid metal batteries have much potential for stationary energy storage applications, with characteristics such as a large capacity, high energy density, low cost, long life-span and an ability for high current charge and discharge. However, there are no publications on battery management systems or state-of-charge (SoC) estimation methods, designed specifically for these devices. In this paper, we introduce the properties of lithium-bismuth liquid metal batteries. In analyzing the difficulties of traditional SoC estimation techniques for these devices, we establish an equivalent circuit network model of a battery and evaluate three SoC estimation algorithms (the extended Kalman filter, the unscented Kalman filter and the particle filter), using constant current discharge, pulse discharge and hybrid pulse (containing charging and discharging processes) profiles. The results of experiments performed using the equivalent circuit battery model show that the unscented Kalman filter gives the most robust and accurate performance, with the least convergence time and an acceptable computation time, especially in hybrid pulse current tests. The time spent on one estimation with the three algorithms are 0.26 ms, 0.5 ms and 1.5 ms.