基于遗传算法的轿车轮毂轴承数值优化

Numerical optimization design for automotive wheel bearings using genetic algorithm

为了提高设计效率和质量,优化系统性能指标,在给定的装配空间条件下满足几何和性能约束,以获得最大的疲劳寿命为目的,运用遗传算法对双列角接触球轴承结构的轿车轮毂轴承进行数值优化设计。并基于一个实际例子编制了优化程序,给出了运算结果。结果表明,遗传算法能够有效地解决离散变量全局寻优问题,全部约束得到满足并且优化设计方案在系统疲劳寿命方面显著优于当前设计方案。

In order to improve the efficiency of the design process and the quality,as well as to optimize the performance of system,it proposes a numerical optimization method,using the genetic algorithm, for determining design variables of automotive wheel bearings of the double - row angular contact ball bearing type. The desired performance to be maximized is the system fatigue life with satisfying the geometrical and operational constraints ,without enlarging the mounting space. A computer program is developed and applied to the design of a real wheel bearings model to evaluate the proposed design method. The optimum design results demonstrate the effectiveness of the design method proposed by showing that the system fatigue life of an optimally designed wheel bearing are enhanced in comparison with that of the current design without any constraint violations.