Stress analysis of overlapped crankshafts
The crankshaft is a complex component, and as such, the influence of its geometric parameters on stresses seen under service loads is not well understood. The objectives of this work are to investigate the effects of a wide range of geometric parameters on stresses in overlapped crankshafts, to find correlation between results and to formulate simple methods of predicting peak stress levels: It is intended to achieve this by use of the Finite Element (FE) and Boundary Element (BE) methods. Individual crankthrows are loaded under the important load cases of bending and torsion. Stress concentration factors are determined by normalising peak stresses with respect to the nominal stress occurring in the most appropriate section in the neck between the fillets. Analyses are carried out in 2D and 3D, making use of symmetry as far as possible. Many of the governing dimensions of the crankthrow are included in the analyses; crankpin and journal diameters, crankpin and journal overlap, and web thickness. Variations in SCF are plotted over a wide range for each of these parameters. Additionally, features such as fillet size and shape, bore-holes, dimples, cut-back webs and oil holes are investigated. It is found that the effects on stress of individual parameter changes can be superimposed to accurately predict the effect of combining various parameter changes in one model. The crankpin and journal fillet radii and the length of the minimum section between the fillets are shown to be the critical parameters in determining the peak stress levels in the crankshaft. SCFs obtained from the range of analyses performed show good agreement with the classical theory of SCFs in notched bars. Bore-holes and dimples are found to offer significant benefits in terms of peak stress reduction, in addition to their common usage of reducing the out of balance crankpin mass. The FE and BE methods give accurate results for stress analysis of crankshafts and offer several advantages over traditional experimental techniques; they are ideally suited to parametric analyses, can be carried out relatively quickly, results are repeatable because boundary conditions can be exactly defined, and the cost of analysis is significantly reduced.