Global Optimal Design and Dynamic Validation of an Independent Double Wishbone Air Suspension Using Genetic Algorithm

2014 ◽  
Vol 543-547 ◽  
pp. 374-378
Author(s):  
Jing Zhao ◽  
Pak Kin Wong ◽  
Tao Xu ◽  
Rui Deng ◽  
Cai Yang Wei ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Parametric Design ◽  
Dynamic Performance ◽  
Vehicle Performance ◽  
Air Suspension ◽  
Before And After ◽  
Wheel Alignment ◽  
Global Optimal ◽  
Suspension Structure

In view of the drawbacks of the traditional optimal methods in the suspension structure optimization, this paper elaborates a genetic algorithm (GA) based global optimal design so as to improve the vehicle performance. Firstly, an independent double wishbone air suspension (IDWAS) is constructed. After defining the linkage relation of the guide mechanism of the IDWAS, the model is verified followed with the parametric design. Furthermore, in consideration of the prescribed targets of the vehicle kinematics, the wheel alignment parameters (WAPs) are selected as the objectives of the optimal design of the vehicle kinematics. Apart from the kinematic analysis of the IDWAS, dynamic analysis before and after optimization as well as the traditional independent double wishbone suspension (TIDWS) are also conducted. Numerical results show that the changes of the WAPs are within a certain range and the guide mechanism follows the prescribed constraints. Simulation results show that the IDWAS is superior to the TIDWS, while the optimized IDWAS has a slight improvement as compared to the original IDWAS in dynamic performance of the suspension.

Study on Optimization Matching Algorithm for Automotive Powertrain

2014 ◽  
Vol 635-637 ◽  
pp. 1890-1894
Author(s):  
Feng Ping Cao ◽  
Li Fa Zhou ◽  
Yong Di Wang
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Fuel Economy ◽  
Dynamic Performance ◽  
Evaluation Index ◽  
Reduce Fuel Consumption ◽  
Matching Algorithm ◽  
Vehicle Simulation ◽  
Before And After ◽  
Automotive Powertrain

In order to reduce fuel consumption and ensure dynamic performance of the car, an automotive powertrain optimization algorithm was presented in the paper. Firstly, the evaluation index of automobile dynamic performance and fuel economy were introduced. Then, the objective function was built, and the transmission and main reducer transmission ratios were designed as variables, and parameters of the vehicle transmission system were optimized by using the genetic algorithm. Finally, a vehicle simulation model by SimulationX software was established, and the power and economy performance before and after optimization were compared and analyzed.

Joint Optimization Combining Genetic Algorithm and Numerical Algorithm Based on MATLAB

2014 ◽  
Vol 1065-1069 ◽  
pp. 3442-3445 ◽  
Author(s):  
Yan Hua Guo ◽  
Fei Fei Liu ◽  
Ning Zhang ◽  
Tao Wang
Keyword(s):  
Genetic Algorithm ◽  
Numerical Algorithm ◽  
Parametric Design ◽  
Optimal Solution ◽  
Mathematic Model ◽  
Optimization Method ◽  
Joint Optimization ◽  
Global Optimal ◽  
First Order Method ◽  
Quasi Newton

The mathematic model of a two-bar truss is built in MATLAB and the analysis is carried out by the genetic algorithm toolbox. The parametric model of the planar truss is established by the ANSYS Parametric Design Language. Solutions are obtained using the first-order method native. Genetic algorithms don’t always display better properties than others. Finally, a joint optimization method is proposed, which combines MATLAB genetic algorithm toolbox and the numerical algorithm based on the quasi-Newton method. The method is identified through the numerical example of the two-bar truss. The results indicate the joint optimization method can always converge to the global optimal solution.

Optimal Design of an Inflatable Knee Bolster Using Genetic Algorithms

2001 ◽  
Author(s):  
Yan Fu ◽  
R. J. Yang ◽  
Isheng Yeh
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Optimization Problems ◽  
Leg Injuries ◽  
Occupant Restraint System ◽  
Assessment Program ◽  
Chest Injuries ◽  
Genetic Algorithm Method ◽  
Global Optimal ◽  
Discrete Optimization Problems

Abstract An inflatable knee bolster (IKB) is an inflatable airbag cushion deployed in the knee area in conjunction with the frontal airbags to reduce the potential lower-leg injuries. It is conceivable that an IKB can reduce the femur loads. However, its effects on the occupant head and chest injuries and its interaction with the other components of the occupant restraint system are unknown. The goal of this study is to evaluate the potential application of an inflatable knee bolster to improve the occupant safety performance, such as the U.S. new car assessment program (NCAP) star rating. An efficient genetic algorithm method is developed for solving this type of large-scaled, combinatorial, and discrete optimization problems. Genetic algorithm works simultaneously on a population of solution strings according to the survivor of the fitness and provides a population of solutions, which gives more flexibility for engineering implementation and produces a potential global optimal design. The results demonstrate that the genetic algorithm is a useful and applicable tool to optimize design configurations for large-scaled occupant simulation problems.

scholarly journals Vision-Based Structural FE Model Updating Using Genetic Algorithm

2021 ◽  
Vol 11 (4) ◽  
pp. 1622
Author(s):  
Gun Park ◽  
Ki-Nam Hong ◽  
Hyungchul Yoon
Keyword(s):  
Genetic Algorithm ◽  
Model Updating ◽  
Structural Parameters ◽  
Fe Model ◽  
Structural Members ◽  
Stiffness Reduction ◽  
Before And After ◽  
Scale Test ◽  
Fe Model Updating ◽  
Story Building

Structural members can be damaged from earthquakes or deterioration. The finite element (FE) model of a structure should be updated to reflect the damage conditions. If the stiffness reduction is ignored, the analysis results will be unreliable. Conventional FE model updating techniques measure the structure response with accelerometers to update the FE model. However, accelerometers can measure the response only where the sensor is installed. This paper introduces a new computer-vision based method for structural FE model updating using genetic algorithm. The system measures the displacement of the structure using seven different object tracking algorithms, and optimizes the structural parameters using genetic algorithm. To validate the performance, a lab-scale test with a three-story building was conducted. The displacement of each story of the building was measured before and after reducing the stiffness of one column. Genetic algorithm automatically optimized the non-damaged state of the FE model to the damaged state. The proposed method successfully updated the FE model to the damaged state. The proposed method is expected to reduce the time and cost of FE model updating.

A Nonlinear Rail Vehicle Dynamics Computer Program SAMS/Rail: Part 1—Theory and Formulations

2009 ◽  
Author(s):  
Khaled E. Zaazaa ◽  
Brian Whitten ◽  
Brian Marquis ◽  
Erik Curtis ◽  
Magdy El-Sibaie ◽  
...  
Keyword(s):  
High Speed ◽  
Dynamic Performance ◽  
Three Dimensional ◽  
Contact Element ◽  
Contact Forces ◽  
Simulation Code ◽  
Vehicle Performance ◽  
Normal Contact ◽  
Advantages And Disadvantages ◽  
High Speed Trains

Accurate prediction of railroad vehicle performance requires detailed formulations of wheel-rail contact models. In the past, most dynamic simulation tools used an offline wheel-rail contact element based on look-up tables that are used by the main simulation solver. Nowadays, the use of an online nonlinear three-dimensional wheel-rail contact element is necessary in order to accurately predict the dynamic performance of high speed trains. Recently, the Federal Railroad Administration, Office of Research and Development has sponsored a project to develop a general multibody simulation code that uses an online nonlinear three-dimensional wheel-rail contact element to predict the contact forces between wheel and rail. In this paper, several nonlinear wheel-rail contact formulations are presented, each using the online three-dimensional approach. The methods presented are divided into two contact approaches. In the first Constraint Approach, the wheel is assumed to remain in contact with the rail. In this approach, the normal contact forces are determined by using the technique of Lagrange multipliers. In the second Elastic Approach, wheel/rail separation and penetration are allowed, and the normal contact forces are determined by using Hertz’s Theory. The advantages and disadvantages of each method are presented in this paper. In addition, this paper discusses future developments and improvements for the multibody system code. Some of these improvements are currently being implemented by the University of Illinois at Chicago (UIC). In the accompanying “Part 2” and “Part 3” to this paper, numerical examples are presented in order to demonstrate the results obtained from this research.

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