7 results on '"Chang, Yujian"'
Search Results
2. Dynamical analysis of a fractional-order nonlinear two-degree-of-freedom vehicle system by incremental harmonic balance method.
- Author
-
Chang, Yujian, Zhu, Yuxiao, Li, Yongkuan, and Wang, Meiqi
- Subjects
- *
NONLINEAR analysis , *VISCOELASTIC materials , *POWER series , *NONLINEAR systems , *MOTOR vehicle springs & suspension , *VEHICLE models , *SUSPENSION systems (Aeronautics) - Abstract
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]
- Published
- 2024
- Full Text
- View/download PDF
3. Short‐term prediction of wind power based on temporal convolutional network and the informer model.
- Author
-
Wang, Shuohe, Chang, Linhua, Liu, Han, Chang, Yujian, and Xue, Qiang
- Subjects
QUANTILE regression ,WIND power ,NUMERICAL weather forecasting ,INFORMERS ,FEATURE selection ,WIND power plants - Abstract
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]
- Published
- 2024
- Full Text
- View/download PDF
4. Sensitivity analysis and parameter optimization of electric vehicle suspension with fractional-order model.
- Author
-
CHANG Yujian, CHENG Lin, CHEN Enli, ZHANG Yuyu, and LI Shaohua
- Subjects
ELECTRIC suspension ,MOTOR vehicle springs & suspension ,ELECTRIC vehicles ,MULTI-degree of freedom ,PARTICLE swarm optimization - Abstract
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]
- Published
- 2022
5. Study on a Class of Piecewise Nonlinear Systems with Fractional Delay.
- Author
-
Wang, Meiqi, Ma, Wenli, Chen, Enli, and Chang, Yujian
- Subjects
NONLINEAR systems ,TIME delay systems ,HOPF bifurcations ,BIFURCATION theory ,DYNAMIC models - Abstract
In this paper, a dynamic model of piecewise nonlinear system with fractional-order time delay is simplified. The amplitude frequency response equation of the dynamic model of piecewise nonlinear system with fractional-order time delay under periodic excitation is obtained by using the average method. It is found that the amplitude of the system changes when the external excitation frequency changes. At the same time, the amplitude frequency response characteristics of the system under different time delay parameters, different fractional-order parameters, and coefficient are studied. By analyzing the amplitude frequency response characteristics, the influence of time delay and fractional-order parameters on the stability of the system is analyzed in this paper, and the bifurcation equations of the system are studied by using the theory of continuity. The transition sets under different piecewise states and the constrained bifurcation behaviors under the corresponding unfolding parameters are obtained. The variation of the bifurcation topology of the system with the change of system parameters is given. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
6. Threshold for horseshoe chaos in fractional-order hysteretic nonlinear suspension system of vehicle.
- Author
-
Chang, Yujian, Chen, Enli, Xing, Wuce, Li, Shaohua, and Wang, Meiqi
- Subjects
- *
AUTOMOBILE springs & suspension , *NONLINEAR systems , *LYAPUNOV exponents , *CHAOS theory , *HORSESHOES - Abstract
The chaotic behavior of a nonlinear vehicle suspension system with a fractional-order derivative is considered. A hysteretic nonlinear model of vehicle suspension with a fractional-order derivative term is established and the analytically necessary condition for heterotopic chaos is derived based on the Melnikov method. The largest Lyapunov exponents are compared. Then, the necessary condition is numerically verified by various simulation factors. The possibility of chaotic motion in vehicles should be higher for larger amplitude of road excitation. It is found that the coefficient and order of the fractional differential term, the stiffness coefficient, and the damping coefficient of the system all affect the necessary condition, and analysis on the effects of these parameters is presented individually. It has been shown that the larger the coefficient of the fractional differential term, or the stiffness and damping coefficients of the system, the lower the possibility of chaos in the system. Meanwhile, without considering the fractional order, the integer order suspension model obviously reduces the actual area where chaos may occur, so designing suspensions according to the fractional order model can avoid chaos more accurately than the integer order model. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
7. Threshold for Chaos of a Duffing Oscillator with Fractional-Order Derivative.
- Author
-
Xing, Wuce, Chen, Enli, Chang, Yujian, and Wang, Meiqi
- Subjects
DUFFING oscillators ,DUFFING equations ,PERIODIC motion ,BIFURCATION diagrams ,LYAPUNOV exponents ,NUMERICAL analysis ,DYNAMICAL systems - Abstract
In this paper, the necessary condition for the chaotic motion of a Duffing oscillator with the fractional-order derivative under harmonic excitation is investigated. The necessary condition for the chaos in the sense of Smale horseshoes is established based on the Melnikov method, and then the chaotic threshold curve is obtained. The largest Lyapunov exponents are provided, and some other typical numerical simulation results, including the time histories, frequency spectrograms, phase portraits, and Poincare maps, are presented and compared. From the analysis of the numerical simulation results, it could be found that, near the chaotic threshold curve, the system generates chaos via the period-doubling bifurcation, from single periodic motion to period-2 motion and period-4 motion to chaotic motion. The effects of fractional-order parameters, the stiffness coefficient, and the damping coefficient on the threshold value of the chaotic motion are analytically discussed. The results show that the coefficient of the fractional-order derivative has great effect on the threshold value of the chaotic motion, while the order of the fractional-order derivative has less. The analysis results reveal some new phenomena, and it could be useful for designing or controlling dynamic systems with the fractional-order derivative. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.