Permanent magnet eddy current couplers (PMECCs) have the characteristics of contactless torque transmission, removal of torque ripple, smooth dynamic process, and adjustable speed, and can be used as couplings, dampers, brakes, and speed governors. Their applications in industry, vehicles, and energy fields are gradually expanding. At the same time, the requirements for the torque density and dynamic performance of PMECCs are increasing. Therefore, a large amount of research work has focused on the fast and accurate modeling, design, and optimization of PMECCs. This paper provides a survey on the development of PMECCs technology. The main topics include the structure and classification of PMECCs, modeling methods, loss and heat transfer analysis modeling, and optimization design. In addition, this paper shows the future trends of PMECCs research. All the highlighted insights and suggestions of this review will hopefully lead to increasing efforts toward the model’s construction and the optimal design of PMECCs for future applications.
Accurate wind power prediction can increase the utilization rate of wind power generation and maintain the stability of the power system. At present, a large number of wind power prediction studies are based on the mean square error (MSE) loss function, which generates many errors when predicting original data with random fluctuation and non-stationarity. Therefore, a hybrid model for wind power prediction named IVMD-FE-Ad-Informer, which is based on Informer with an adaptive loss function and combines improved variational mode decomposition (IVMD) and fuzzy entropy (FE), is proposed. Firstly, the original data are decomposed into K subsequences by IVMD, which possess distinct frequency domain characteristics. Secondly, the sub-series are reconstructed into new elements using FE. Then, the adaptive and robust Ad-Informer model predicts new elements and the predicted values of each element are superimposed to obtain the final results of wind power. Finally, the model is analyzed and evaluated on two real datasets collected from wind farms in China and Spain. The results demonstrate that the proposed model is superior to other models in the performance and accuracy on different datasets, and this model can effectively meet the demand for actual wind power prediction.
In response to the era background of “comprehensive electrification” and “dual carbon plan” of electric vehicles, DC/DC converters have a good performance in terms of weight, volume, and efficiency and are widely used in fields such as solar power generation, UPS, communication, computers, and electric vehicles. At present, the DC bus voltage is an important indicator for measuring the safe and stable operation of high-voltage DC power systems in electric vehicles. Therefore, regulating the stability of bus voltage through converters has good economic benefits for the sustainable development of electric vehicles in terms of maintenance costs and effective energy management. In order to solve the problem of bus voltage resonance instability caused by negative impedance characteristics of constant power load in an electric vehicle DC power system, a sliding-mode control design strategy of three-phase interleaved bidirectional converter under constant power load was proposed. Firstly, a GPI observer was designed to estimate the state and concentrated disturbances of the system. Then, the estimated value was introduced into the controller for feedforward compensation, thereby achieving fast-tracking of the output voltage to the reference voltage. Finally, the simulation results show that the controller can effectively maintain the influence of disturbances and better improve tracking characteristics and robustness to disturbances and uncertainties.
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