Improving the accuracy of wind power forecasting is an important measure to deal with the uncertainty and volatility of wind power. Wind speed and wind direction are the most important factors affecting the power generation of wind turbines. In this paper, we propose a wind power forecasting method that combines the sparrow search algorithm (SSA) with the deep extreme learning machine (DELM). Based on the DELM model, the length of the time series’ influence on the performance of the neural network is validated through the comparison of the forecast error indexes, and the optimal time series length of the wind power is determined. The sparrow search algorithm is used to optimize its parameters to solve the problem of random changes in model input weights and thresholds. The proposed SSA-DELM model is validated using the measured data of a certain wind turbine, and various forecasting indexes are compared with several current wind power forecasting methods. The experimental results show that the proposed model has better performance in ultra-short-term wind power forecasting, and its coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE) are 0.927, 69.803, and 115.446, respectively.

The ultra-high speed permanent magnet motor (UHSPM) for hydrogen fuel cell air compressor is characterized by high speed, high motor power density, small size, and high reliability. Compared to the conventional motor, the loss per unit volume is increased and therefore the calculation of the temperature field is more important than that of conventional motors. In this paper, a UHSPM with a rated speed of 90000 r/min is designed. Firstly, a finite element (FE) model of the UHSPM is established and the losses of each part of the high-speed motor are calculated, and the calculated losses are introduced into the fluid field in the form of a heat source for motor temperature analysis. The calculated losses were introduced into the fluid field in the form of a heat source and used in the motor temperature analysis. The temperature rise was then calculated for the unidirectional and bidirectional magneto-thermal coupling (MTC) respectively. The results show that the bidirectional magneto- thermal coupling (BMTC) simulation results are about 2-3 °C smaller than the experimental measured values, which can more accurately predict the motor temperature. The measurement results verify the accuracy of BMTC, and provide basic theoretical support for the subsequent cooling optimization scheme of high-speed motor.

The multidimensional motion ultrasonic motor with a single spherical stator is studied in this paper. It has the characteristics of miniaturization and can be used in precision motion applications. By bonding six identical pieces of piezoelectric ceramic onto the stator and applying the voltage signal of high frequency, the deformation of the inverse piezoelectric effect is used to excite the stator yaw vibration mode. The orthogonal superposition of the modes of the spherical stator on the driving foot produces elliptical trajectory around X, Y, and Z directions by different excitation methods. According to the yaw vibration mode of the spherical stator, 12 driving feet are designed to drive the rotation of the spherical rotor. The structure and mechanical characteristics of the motor are simulated by using simulation software, and the transient response of the stator driving foot was obtained, which proved its feasibility. Finally, the output performance of the motor in actual operation is given through experiments, which provides a new reference scheme in the field of precise multi-degree-of-freedom motion. At a voltage of 100 V and a frequency of 26.7 kHz, the prototype has a no-load speed of 73, 70, and 114 rpm around X, Y, and Z axes, respectively.

The pre-pressure device of the ultrasonic motor plays a vital role in the design of the entire motor structure, the contact state of the stator and rotor of the motor, dynamic properties of the stator, friction and wear characteristics of the rotor; even the mechanical behaviors of the entire electric machinery have a profound impact. Appropriate pre-pressure is conducive to the smooth operation of the ultrasonic motor, so that the output performance remains excellent, reducing wear and effectively extend the service life of the motor. Therefore, the research on pre-stress is of great significance, as it can better optimize the structure of the three-stator ultrasonic motor and lay the foundation for the stable operation of the motor. First, this paper introduces the construction of the motor as a whole and the pre-pressure device briefly described the working mechanism of the motor, and then introduces the influence of the pre-pressure on the stator and rotor contact models, the position of the constant velocity point, and the modal frequency. Finally, the motor output under different pre-pressures is discussed. The performance experiment has determined the optimal pre-pressure interval, which provides help for its subsequent optimization.