Automobile Shape Optimization Based On Genetic Algorithm

In this paper,the fastback automobile body shape is the research object.The body shape is satisfied with the requirements of three goals(the drag is minimization,the lift is 0N and the pressure of the roof is minimum).Through the optimization design of five important parameters of the body shape.Using data mining method to reveal the potential relationship between design variables and objectives,or the objective each other.This paper research contents cloud be separated into two departments: 1.To establish a fastback automobile numerical model and analysis the numerical simulation results of the external flow field;2.The body shape of the model was optimized by genetic algorithm,and using numerical simulation and wind tunnel test verified the optimized resultsIn the first part of the numerical simulation,the research method is based on the computational fluid dynamics.By analyzing the automobile external flow field and the surface pressure distribution of the body,We can have a deeper understanding of the characteristics of the flow field outside.Thus,it lays a theoretical foundation for the analysis of the influence of automobile body shape on the aerodynamic performance.It also provides the basis for optimizing the automobile body shape and improves the aerodynamic performance of the automobile.Secondly,the method of multi objective optimization is used to optimize the body shape of the model.When setting multiple goals,using the vehicle drag and lift to measure the aerodynamic performance after optimization,using the pressure of the skylight trailing edge to measure the ventilation performance.So,there are 3 optimization objectives.One is minimum vehicle resistance,other one is 0N lift force,the last one is the minimum pressure of the roof.The Latin hypercube sampling method is used to select samples from the design space in the specified design range.The samples is carried out by numerical simulation.Using the genetic algorithm of Kriging surrogate model to predict the objective results in the design space.At last,the optimal solution is obtained in the whole design space.Significance of data mining is to make the complicated relationship between the design variables and the objective function more intuitive,and the designers can seize the main design variables that affect the objective function.By genetic algorithm,Pareto optimal solution or optimal solution set is obtained to provide reference and selection of the optimal solution space.Using data mining to evaluate the relationship between five design variables and three objectives.Including the impact of the relationship between the objective function,the impact of a single or multiple design variables and objective function.This reveals the design variables for the objective function of the rule.At the same time,it also reveals that the objective function is independent of each other or positive and negative correlation,which provides convenience for the follow-up development or research.Finally,the aerodynamic performance of the optimized vehicle body is verified by the wind tunnel test.And the numerical simulation results of the optimization model are used to verify the accuracy of the multi-objective optimization method used in this research.At last,the result show that the multi-objective optimization method has high prediction accuracy and adaptability.The research of this paper can be applied to the aerodynamic design of the vehicle,which can provide important theoretical guidance for the design and optimization of automobile body shape in the future.