基于智能算法的汽车气动外形参数多目标优化

为了对汽车外形进行优化设计,利用CFD软件与智能算法相结合的方法,以在天窗微开高速行驶状态下的汽车为优化的对象,选取气动阻力最小、气动升力为0、天窗后缘压强最小为`优化目标,以汽车关键外形参数为设计变量,对汽车气动外形进行多目标优化设计.同时,应用了数据挖掘技术评价设计变量与3个目标函数的影响关系,选取优化后的最佳关键参数制作汽车模型并进行风洞试验验证.研究结果表明:通过遗传算法优化的车身外形,在其他设计目标满足要求的条件下成功地将阻力系数降低了9.5%,并通过风洞试验验证了该智能算法结果的准确性.基于智能算法的汽车气动外形设计具有指导意义与实际应用价值,为汽车气动外形的多目标优化设计提供了一种高效、精确、可靠的先进优化方法.

Multi-objective Optimization of Vehicle Aerodynamic Shape Parameters Based on an Intelligent Algorithm

Traditional optimization methods for the multi-objective problem are often transformed into a single objective optimization problem through some techniques. A certain degree of subjectivity due to these transformation processes needs to artificially define some parameters, and optimization results are usually more sensitive to the weighting coefficient. Additionally, because the objective function of multi-objective optimization problem is often nonlinear or discontinuous, using the traditional mathematical programming methods is relatively low efficiency. Especially in the field of automotive aerodynamics, when facing multi-objective optimization problems, a lot of work are required frequently and it is difficult to obtain ideal results. Therefore, a intelligent algorithm was adopted to solve multi-objective problem in this study. Combining CFD software and intelligent algorithm, the aerodynamic shape of SUV was optimized based on multi-objective optimization and design technique. The optimized object is a high-speed running SUV with a jar sunroof. The minimum aerodynamic drag, suitable aerodynamic lift ( here is 0 ) , and the minimum pressure on the trailing edge of the sunroof were taken as the optimization objective . The key shape parameters of the vehicle were selected as the design variables. The data mining technology was applied to evaluate the regulation and effects between design variables and three objective functions, and wind tunnel experiments were carried out to verify the validity of the algorithm method. Results show that through the non-dominated sorting genetic algorithmⅡ( NSAG-Ⅱ) method, under the premise of that other design objectives meet the design requirements, the aerodynamic drag of the optimized vehicle successfully decreases by 9. 5％, and the accuracy of the intelligent algorithm is verified by wind tunnel test. The research indicates that the aerodynamic design of automobile aerodynamic shape based on an intelligent algorithm has excellent applicability and practical significance, and provides an efficient, accurate and reliable aerodynamic shape optimization method for the multi-objective optimization and design.