Lightweight Study On Light Truck Driving Axle

In recent years, energy shortage and environmental pollution are more and more serious, lightweight, as an effective technical means of energy saving and emission reduction, has become one of the frontiers and hotspots in the field of car development. More and more scholars being involved in the lightweight technology have made some achievements. Some components need to meet various requirements, which can be satisfied by using of coupling of multidisciplinary knowledge. In some common problems, there are certain similarities in the lightweight design flows, but some differences also exist between different components. The driving axle is one of the most important components, and many scholars have done corresponding lightweight researches, but most of them stay in the individual discipline optimization of single component, which brings about problems that the light structures can’t achieve modular design and they often meet one condition while ignoring other limitations. In all, the present lightweight design methods still have some limitations.Focused on the above problems, studies which have been done in the paper are shown as follows:1. The selection of study objects is discussed, then the concept of minimum assembly has been proposed, and the reasonable resolution of driving axle assembly has been done. This method makes the relationship between different assemblies more clear, and the interaction effects between different assemblies tend to minimum. The minimum assemblies are lightweight designed, which can reduce design time of driving axle lightweight and achieve structural modularization easily.2. Based on finite element method, the static structural analysis, fatigue analysis and modal analysis are done to the driving axle, through driving bench tests, the accuracy of analysis results are verified. In this paper, the bench test results are reasonable analyzed, and some referable experience have obtained.3. An approximation model with automatic optimization function is established through sparse grid meta-model. Based on probability and statistics theory, the response surface is constructed through sparse grid method. This method can simulate the whole optimization space using less sample points, add new sample points automatically in the large gradient zone of output variables, which can effectively reduce calculation numbers, save time and improve accuracy of approximation model.4. Based on the approximation model and Pareto law, the optimal structural solution set is obtained under the condition of multidisciplinary coupling. Parts of optimal parameters in the solution set are chosen to validate the model, and it is proved that the approximation model based on sparse grid meta-model has a good accuracy.It is a cooperative project between Shandong Wuzheng Group and Shandong University.