The electric vertical take-off and landing fixed-wing (FW-VTOL) unmanned aerial vehicle (UAV) combines the advantages of fixed-wing aircraft and multi-rotor aircraft. Based on the cell discharge characteristics and the power system features, this paper proposes a preliminary design and optimization method suitable for electric FW-VTOL UAVs. The purpose of this method is to improve the design accuracy of electric propulsion systems and overall parameters when dealing with the special power and energy requirements of this type of aircraft. The core of this method involves testing the performance data of the cell inside the battery pack, using small-capacity cells as the basic unit for battery sizing, thereby constructing a power battery performance model. Additionally, it establishes optimization design models for propellers and rotors and develops a brushless DC motor performance model based on a first-order motor model and statistical data, ultimately achieving optimized matching of the propulsion system and completing the preliminary design of the entire aircraft. Using a battery discharge model established based on real cell parameters and test data, the impact of the discharge process on battery performance is evaluated at the cell level, reducing the subjectivity of battery performance evaluation compared to the constant power/energy density method used in traditional battery sizing processes. Furthermore, matching the optimization design of power and propulsion systems effectively improves the accuracy of the preliminary design for FW-VTOL UAVs. A design case of a 30 kg electric FW-VTOL UAV is conducted, along with the completion of flight tests. The design parameters obtained using the proposed method show minimal discrepancies with the actual data from the actual aircraft, confirming the effectiveness of the proposed method.

With the accumulation of data, it is possible to study the long-term variation of Fluxgate Magnetometers (FGM) of High Precision Magnetometer (HPM) onboard the China Seismo-Electromagnetic Satellite (CSES). The calibration method of HPM depends on an assumption that the linear parameters of FGM, including the gain factors, the offsets, and nonorthogonal angles are stable. However, HPM exhibits some unexpected trends in the scalar residuals when processed according to the assumption. Study on the residual finds out that under changing space thermal conditions, the non-orthogonal angles of FGM change periodically, suggesting that the data calibration method we used before should be modified. A multi-dimensional polynomial model is established for defining the change of nonorthogonal angles of FGM as a function of the sun incidence angles, geographic latitude and sensor temperature. Apply the polynomial model to data from August 2018 to May 2021, the standard deviation of the scalar residuals is reduced to around 0.5 nT and tends to be more random and in line with the normal distribution. Meanwhile, the variation trend in gain factors and offset factors are eliminated. Results show that the model can correctly reflect the period variation of the non-orthogonal angles of FGM with the space thermal conditions.

This paper describes the development of the fluxgate magnetometer on the Fengyun-4B satellite. The Fengyun-4 is the second generation of China’s geostationary orbit satellite with the function of monitoring the space environment in GEO orbit. A fluxgate magnetometer (FGM) is deployed on this satellite to observe the magnetic field as a necessary input to space weather forecasting. This payload adopts three 3-axis fluxgate sensors to obtain space magnetic field data by excluding the satellite’s interference. Each three-axis fluxgate sensor has an independent signal processing circuit. FGM uses digital signal processing technology to acquire magnetic field signals. First, the analog signal is oversampled using a high-speed ADC, then digital signal processing, such as phase-sensitive demodulation, integration, and filtering, is performed inside the FPGA, and the feedback signal is output to the feedback coil through the DAC. This signal processing loop constitutes an ADC system, and the quantization accuracy of the output digital quantity can reach 18 bits. the FGM performs in-orbit calibration during satellite rotation maneuver and Alfven wave events. Comparison with the GOES-16 satellite and Tsyganenko magnetic field model proves FGM to be effective in monitoring the magnetic field of the space environment. Through joint observations with GOES-16 satellite and geomagnetic stations, FY-4B describes the development of a typical magnetic storm on November 4, 2021. The Ground calibration and in-orbit preliminary results show the FY-4B satellite magnetometer outputs 20 bits of digital resolution data at a 30 Hz sampling rate, with the noise lower than 3×10-4nT2/Hz@1Hz in the ±600nT range.