scholarly journals Finite Element Structure Analysis of Automobile Suspension Control Arm Based on Neural Network Control

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yixuan Li
Keyword(s):  
Neural Network ◽  
Finite Element ◽  
Ride Comfort ◽  
Network Control ◽  
Neural Network Control ◽  
Element Analysis ◽  
Front Suspension ◽  
Longitudinal Stiffness ◽  
Operation Stability ◽  
Strength And Stiffness

The control arm is an important transmission and guidance device in the Macpherson suspension system, which has an important impact on the ride comfort, operation stability, and safety of the vehicle, so it is necessary to study the structural performance of the control arm. In this paper, based on neural network control model, finite element analysis, and fatigue analysis theory, the strength, stiffness, and dynamic and fatigue performance of the control arm are studied and analyzed. Taking the ground contact force of the tire as the input condition, the static analysis of the front suspension is carried out, and the boundary condition of the load of the control arm is extracted. The finite element strength of the control arm is calculated in the OptiStruct solver under the conditions of uneven road, braking, and turning. At the same time, the longitudinal stiffness and lateral stiffness of the control arm are analyzed. The simulation results show that the control arm has better strength and stiffness performance.

Tail Deviation Mechanism and Neural Network Control of the Tandem Rolling Strap

2011 ◽  
Vol 103 ◽  
pp. 488-492
Author(s):  
Guang Bin Wang ◽  
Xian Qiong Zhao ◽  
Yi Lun Liu
Keyword(s):  
Neural Network ◽  
Finite Element ◽  
Finite Element Model ◽  
Control Policy ◽  
Element Model ◽  
Rolling Process ◽  
Network Control ◽  
Neural Network Control ◽  
The Neural Network ◽  
The Finite Element Model

In the rolling process, deviation is the phenomenon that the strap width direction's centerline deviates from rolling system setting centerline,serious deviation will cause product quality drop and rolling equipment fault. This paper has established the finite element model to the hot tandem rolling aluminum strap, analyzed the strap’s deviation rule under four kinds of incentives,obtained the neural network predictive model and the control policy of the tail deviation.The result to analyze a set of fact deviation data shows this method may control tail deviation in preconcerted permission range.

Study of Active Suspension Based on Fuzzy Neural Network Control

2012 ◽  
Vol 251 ◽  
pp. 201-205
Author(s):  
Chuan Yi Yuan ◽  
Ye Fang Teng ◽  
Xin Ye Yin
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Ride Comfort ◽  
Active Suspension ◽  
Sine Wave ◽  
Network Control ◽  
Vertical Acceleration ◽  
Neural Network Control ◽  
Vehicle Mass ◽  
Fuzzy Neural

Based on the established full-car active suspension model, fuzzy control theory was combined with neural network control, the fuzzy neural network control system of vehicle active suspension was designed, simulation and analysis of random road input and sine wave input were carried on. The results show that, by comparison with the traditional suspension system, the peak and standard deviation of vehicle mass vertical acceleration decreased by 55.38% and 59.04%, the peak of vehicle mass vertical acceleration decreased by 49.96% when vehicle go through the sine wave at the speed of 5m/s, the ride comfort was improved obviously.

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