| Energy and environment are two main research subjects of the automotive engineindustry in the21st century, engine noise and emission have been a challenging anduniversal attention problem.1/3~1/2of the total energy is consumed in the form offriction in world industrial, wear failure accountes for60%to80%failure ofmechanical parts,which results in huge direct and indirect economic losses.Therefore,through the basic research, experimental analysis, numerical algorithms, simulation,optimization analysis and other means, the lubrication mechanism and dynamics ofthe frictional pairs are analyzed. The main contents include:The optimization of the piston ring is carried with Design of Experiment (DOE)and BP neural network optimized by genetic algorithm, which is aimed at reducingfriction loss. Based on the traditional model, the cavitation without roughness andinter-asperity cavitation are built with the control volume theory. The change rule ofcavitation zone, oil film pressure distribution and friction performances are analysed.According to SVR wear tester, the effects of different boundary conditions on thefriction coefficient of cycles are studied, and the reasons that cause the large loss arealso summarized.The piston skirt lubrication equations are solved with finite element method, theeffect of each variable on dynamic characteristics and the friction loss are analysed.Based on lubrication model, weights of variables on friction power loss are evaluatedwith orthogonal experiment and regression algorithm, while regression forecastingwith linear and nonlinear model are compared. Loads of piston ring and thermaldeformation are considered in piston skirt lubrication, the effects of the piston ringloads and thermal deformation on piston skirt lubrication are compared.The thermal hydrodynamic lubrication model is established to analyze steppedshaft, and the effects of misalignement caused by unsymmetry deflection on the oilfilm pressure distribution and oil temperature field distribution are carried out.According to mass-conserving and control volume theory, lubrication characteristicssuch as oil film pressure distribution and density of classical model are compared bycavitation model without roughness and inter-asperity cavitation. The maximum oil film pressure and minimum film thickness are analysed withdouble orthogonal experiment in connecting rod lubrication, then according to theexperimental results, combined with the linear regression and stepwise regression topredict average effective pressure, the maximum oil film pressure and minimum filmthickness, surface response analysis are also carried out, SVM is used to identify theasperity contact, the result shows that SVM can accurately identify the asperitycontact, so it has a positive significance in avoiding dry friction.The dynamic model of crankshaft-bearing model is built with NONL, HD andEHD to analyze the crankshaft stress and the torsion angle, the results show that it isimportant to improve the stress and do fatigue analysis accurately with precise model.Based on the EHD model, the mechanism of lubrication parameters on main bearingcharacteristics are carried out; orthogonal experiment and neural network arecombinated to identify asperity contact and optimize the main bearing friction loss.Based on the theory of modal reduction theory, the dynamic model of engineblock is built, and the vibration and noise of the engine with NONL, HD or EHDmodels are studied. It shows that there is rarely difference when predicted thevibration, while there is a little difference in noise distribution. The probable reason isthat the load-chansfer path. The dynamic model is also built with rigid crankshaft andflexible block, the rigid crankshaft easily causes the vibration of belt pulley andflywhee to be larger. |
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