Multi-objectives Robust Optimization Of Powertrain Mounting System Based On Kriging Model

Powertrain mounting system(PMS)plays an important role in isolating vibration of powertrain in engineering machinery,and has a significant effect on the vehicle NVH performance.How to effectively optimize the PMS is one of the most important subjects in the fields of controlling powertrain vibration.Consisting of loader vehicle modeling and multi-objectives optimization method of PMS,some basic theoretical researches are carried out.Adams is used to set up the loader virtual model,a combined method including Kriging approximation model and NSGA-II algorithm is used to find determined and robust Pareto solutions of PMS,which provides a new idea for the optimization of PMS.First,the vibration test of loader’s PMS is carried out,and the idle condition is set as example to analyze the isolation performance of PMS,which also provides the data support for the establishment and validation of vehicle virtual model.Meanwhile,a multi-body dynamics virtual model including cab,chassis,powertrain and tires is set up using the CAE and Adams software.The engine excitation is analyzed and added into the virtual model to simulate the vehicle works at idle.The decoupling rate of PMS and the vibration of vehicle can be got after the simulation.Subsequently,the accuracy of virtual model is verified by comparing the simulation data with test data.Next,aiming at the shortcomings of traditional multi-body dynamics model optimization method,which are time-consuming and inefficient,this paper proposed a combination of the Kriging approximation model and NSGA-II to find determined and robust solutions of PMS.In this method,the sampling points are first obtained by the optimal Latin Hypercube design,and the output of the sampling points is obtained by the virtual model.With the data obtained,the Kriging approximate is established to replace the virtual model.NSGA-II algorithm is used in the multi-objectives determined optimization,which taking the energy decoupling of the powertrain,the root mean square(RMS)values of floor’s vertical and the kinetic energy of chassis as objectives.Next,to consider the uncertainty of PMS,the stiffness of mountings is considered as normal distribution in order to investigate the effect of objectives.Monte Carlo Simulation is used to calculate the mean and standard deviation of each solution.Furthermore,the deterministic and robust solutions are presented for comparison.The result indicates that the method of the Kriging approximation model can optimize powertrain mounting system quickly and effectively.The ride comfort of the wheel loader model with optimized powertrain mounting system is largely improved.