Based on batch experiments conducted on soil samples in the laboratory, the relationship between dielectric constant and water content based on electrical capacitance measurement was investigated. Factors that may affect the relationship, such as measurement frequency, electrode array methods, and soil particle sizes, were analyzed. A model fitting the relationship between dielectric constant and water content was proposed. The results clearly indicate that even with the use of rod-like sensors, the measured electrical capacitance with 1 kHz frequency can be used to construct a good relationship between dielectric constant and water content. Although the electrode array methods (parallel or non-parallel electrode pair) and soil particle sizes do affect the obtained absolute values of dielectric constant to some extent, the relationship between dielectric constant and water content remains unchanged. A clear characteristic is the increase reduction in the dielectric constant at near saturation condition, and the low increase speed when water content is small. The proposed modified VG model incorporated this characteristic into it and fitted the data better than the reported models. These results suggest that the electrical capacitance-based dielectric constant measurement can be extensively used and would be useful, especially in the situations where parallel sensor requirement is difficult to satisfy.

The process of soil freezing and thawing refers to the alternating phase change of liquid water and solid water in the soil, accompanied by a large amount of latent heat exchange. It plays a vital role in the land water process and is an important indicator of climate change. The Tibetan Plateau in China is known as the “roof of the world”, and it is one of the most prominent physical characteristics is the freezing and thawing process of the soil. For the first time, this paper utilizes the spaceborne GNSS-R mission, i.e., CYGNSS (Cyclone Global Navigation Satellite System), to study the feasibility of monitoring the soil freeze-thaw (FT) cycles on the Tibetan Plateau. In the theoretical analysis part, model simulations show that there are abrupt changes in soil permittivities and surface reflectivities as the soil FT occurs. The CYGNSS reflectivities from January 2018 to January 2020 are compared with the SMAP FT state. The relationship between CYGNSS reflectivity and SMAP soil moisture within this time series is analyzed and compared. The results show that the effect of soil moisture on reflectivity is very small and can be ignored. The periodic oscillation change of CYGNSS reflectivity is almost the same as the changes in SMAP FT data. Freeze-thaw conversion is the main factor affecting CYGNSS reflectivity. The periodical change of CYGNSS reflectivity in the 2 years indicates that it is mainly caused by soil FT cycles. It is feasible to use CYGNSS to monitor the soil FT cycles in the Tibetan Plateau. This research expands the current application field of CYGNSS and opens a new chapter in the study of cryosphere using spaceborne GNSS-R with high spatial-temporal resolution.

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In general, battery packs are monitored by the battery management system (BMS) to ensure the efficiency and reliability of the energy storage system. SOC and SOH represent the battery's energy and lifetime, respectively. ey are the core aspects of the battery BMS. e traditional method assumes that the SOC is determined by the integral of the current input and output from the battery over time, which is an open-loop-based approach and often accompanies by poor estimation accuracy and the accumulation of sensor errors. e contribution of this work is to establish a new equivalent circuit model based on the lithium battery external characteristic, and the battery parameters are identified by considering the influence of capacity fade, voltage rebound, and internal capacitance-resistance performance. e correlation between the ohmic internal resistance and real capacity is obtained by degradation test. en, the dual extended Kalman filter (DEKF) is used to perform real-time prediction of the lithium battery state. And through the simulation analysis and experiments, the feasibility and precision of the estimation method are well proved.

For signal processing of a Micro-Electro-Mechanical System (MEMS) Inertial Measurement Unit (IMU), a digital-analog hybrid system-on-chip (SoC) with small area and low power consumption was designed and implemented in this paper. To increase the flexibility of the processing circuit, the designed SoC integrates a low-power processor and supports three startup or debugging modes for different application scenarios. An application-specific computing module and communication interface are designed in the circuit to meet the requirements of IMU signal processing. The configurable clock allows users to dynamically balance computing speed and power consumption in their applications. The chip was taped out under SMIC 180 nm CMOS technology and tested for performance. The results show that the chip’s maximum running frequency is 105 MHz. The total area is 33.94 mm 2 . The dynamic and static power consumption are 0.65 mW/MHz and 0.30 mW/MHz, respectively. When the system clock is 25 MHz, the dynamic and static power consumption of the chip is 76 mW and 66 mW, and the dynamic and static power consumption of the FPGA level are 634 mW and 520 mW. The results verify the superiority of the application specific integrated circuit (ASIC) solution in terms of integration and low power consumption.