基于Kriging模型的驾驶室悬置系统多目标优化

Multi-objective Optimization of Cab Suspension System Based on Kriging Model

为提高某国产自卸车行驶平顺性,采用多体动力学软件Adams建立重型自卸车整车虚拟样机分析模型,并通过行驶平顺性道路试验验证模型的正确性。选取驾驶室悬置刚度和阻尼参数为设计变量,以驾驶室地板垂向和座椅支撑面俯仰加权加速度均方根为优化目标,以驾驶室前后悬置动挠度为约束条件,结合最优拉丁方试验设计拟合Kriging近似模型,利用粒子群优化算法对自卸车行驶平顺性进行多目标优化,得到Pareto最优解集,并选取一个最优解进行整车行驶平顺性实车试验。结果表明,Kriging近似模型具有较高的拟合精度,可大幅提高自卸车行驶平顺性优化效率;基于Kriging近似模型的多目标优化结果可通过权重系数对各个优化目标进行权衡,有效改善了自卸车行驶平顺性。

In order to improve the ride comfort of a domestic self-dumping truck, a virtual prototype vehicle model was built through multi-body dynamics software Adams. And vehicle road test of ride comfort was implemented to verify the validity of this model. Taking the suspension stiffness and damp parameters of cab suspension as design variables, the root mean square （RMS） values of floor＇s vertical and seat＇s pitching weighted acceleration as optimization objectives, and the deflection of front and rear cab suspension as constraints, the Kriging approximation models were constructed based on optimal Latin hypereube design. On this basis, multi-objective optimization for self-dumping truck ride comfort was performed with particle swarm optimization algorithm, and the Pareto optimal set was obtained. Furthermore, a vehicle road test of ride comfort was conducted by using one of the optimal solutions. The results indicated that the Kriging approximation model with high fitting accuracy could significantly improve the efficiency of ride comfort optimization of self-dumping truck according to different weighting schemes of optimization objectives. The road test results showed that the overall weighted acceleration RMS values on the cab floor of the improved self-dumping truck were greatly reduced with a maximal reduction of 16.5%.