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Optimization of Automotive Powertrain Mounting System Based on Adaptive Genetic Algorithm

There are many local optimization solutions to optimize the automotive powertrain mounting system with conventional optimum algorithms which are likely to get trapped in local minima. To overcome this fault, taking the kinetic energy decoupling level as the objective function, stiffness of each mounting served as the design variable, adaptive genetic algorithm which was programmed in the MATLAB software was applied. The corresponding simulation model was built in ADAMS software to verify the result of the adaptive genetic algorithm. The optimum results show that the decoupling effect has been improved.