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A compiled method of the programmed load spectrum, which can simplify and accelerate the fatigue bench test of a car body, is proposed and its effectiveness is checked by the fatigue simulation. By using the multi-body dynamics model with a satisfactory accuracy, the virtual iteration is applied to cascade body loads from the wheel hubs. Based on the rain-flow counting method and statistics theory, the distributions of the body loads are analyzed, and then the programmed load spectrum is compiled and simplified. Through comparative study, the simulation results of random and programmed load spectrum are found to agree well with each other in terms of the damage distribution and fatigue life, which demonstrates the effectiveness of the presented method.

As a potential material for lightweight vehicle, polymethyl methacrylate (PMMA) has proven to perform well in optical behavior and weather resistance. However, the application in automotive glazing has seldom been studied. This paper investigates the defrost performance of PMMA rear window using both numerical and experimental methods. The finite element analysis (FEA) results were found to be in good agreement with the experimental data. Based on the validated finite element model, we further optimized the defrost efficiency by changing the arrangement of heating lines. The results demonstrated the frost layer on the vision-related region of PMMA rear window can melt within 30 minutes, which meets the requirement of defrost efficiency.