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At present, there are few studies considering both nonlinear and fractional characteristics of suspension in vehicle systems. In this paper, a fractional nonlinear model of a quarter vehicle with two-degree-of-freedom (2-DOF) is innovatively proposed to describe the suspension system containing the viscoelastic material metal rubber. Given the lack of a general calculation scheme for the multi-degree-of-freedom fractional-order incremental harmonic balance method (IHBM), a general calculation scheme for the 2-DOF incremental harmonic balance method for nonlinear systems with fractional order is derived. The nonlinear dynamical properties of the presented model are acquired using this method. The accuracy of the proposed method is verified through a comparison with the power series expansion method. Afterward, the effects of the various parameters on the dynamic performance are analyzed. The vibration peak value of the fractional-order model is significantly higher than that of the integer-order model (IOM). Therefore, the suspension parameters should be designed with a margin when using IOM. [ABSTRACT FROM AUTHOR]

In this study, a new short‐term wind power prediction model based on a temporal convolutional network (TCN) and the Informer model is proposed to solve the problem of low prediction accuracy caused by large wind speed fluctuations in short‐term prediction. First, an input feature selection method based on the maximum information coefficient is proposed after considering the problem of information interference caused by excessively large input features. A dynamic time planning method is used to select the optimal input step of historical power. Then, the combined forecasting model composed of TCN and the Informer is constructed in accordance with the numerical weather forecast and historical power data. Lastly, the pinball loss function is used to expand the prediction model into a quantile regression model, measure the effect of volatility, quantify the volatility range of prediction, and finally, obtain a deterministic prediction result. The actual measured data of wind farms in the Bohai Sea area are selected for analysis and calculation. The results show that the prediction model proposed in this study achieves better accuracy in deterministic prediction and interval prediction than the traditional model. [ABSTRACT FROM AUTHOR]

In order to optimize the parameters of passive fractional-order electric vehicle suspension, four ride comfortability indexes including vertical acceleration off vehicle body, dynamic deflection off suspension, dynamic load off ire and verial acceleration off motor were introduced in this system. Nonlinear 1/4 model of electric vehicle with fractional passive control suspension system having three degrees of freedom was built, and the uncertainty of the suspension model parameters was simulated and analyzed by using the Monte Carlo algorithm. The parameters with high sensibility were selected, and the improved particle swarm optimization (PSO) algorithm was used to optimize and design the suspension parameters. Compared with the traditional PSO algorithm, the results show that the improved PSO algorithm can not only reduce the vibration acceleration of vehicle body, but also decrease the dynamic load of tire. [ABSTRACT FROM AUTHOR]