基于遗传算法汽车动力总成悬置系统解耦优化

为避免传统优化算法在对汽车动力总成悬置系统优化中陷入局部最优解,采用遗传算法对其进行优化。在深入分析设计变量选取、约束函数的提取及目标函数的选取原则基础上,以悬置刚度为优化变量、固有频率的范围和固有频率之差为约束函数、六自由度方向的解耦率为目标函数,利用MATLAB平台的遗传算法进行优化。开发基于遗传算法汽车动力总成悬置系统解耦优化系统,并对某型号汽车动力总成系统优化。优化结果表明:系统的固有频率的分配和解耦率得到极大的改善,效率和精度都得到很大的提升。

Decoupling Optimization of an Automotive Powertrain Mount System Based on Genetic Algorithm

To avoid the local optimal solution of the automotive powertrain system solved by traditional optimization algorithm, the system is optimized by genetic algorithm. After deep analysis the principle of selection of design variables, the extraction of constraint functions and the selection of the objective function, taking the stiffness parameters of the mounting system as the design variable, the scope and interval of natural frequency as the constraint function, and the decoupling rate of the six-degrees-freedom as the energy decoupling and the transmission rate, powertrain mounting system was optimized by genetic algorithm on MATLAB. The powertrain mounting system of a vehicle was optimized by the system which developed based on genetic algorithm to optimize powertrain mounting system. Optimization results show that the system of the distribution of the natural frequency and decoupling rate is greatly improved, and the efficiency and accuracy are greatly improvement.