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A new method for predicting the piston slap noise has been developed. Although using conventional methods, piston slap noise was estimated by using kinetic energy or the vibration of the cylinder liner using the piston secondary motion simulation, predictive accuracy was low and it lacked in reliability. In this paper the distortion of the cylinder liner at the low temperature, the dynamic stiffness of the piston and the cylinder block, and an oil film model enhancement were taken into consideration. Furthermore, comparison with the measured data of piston motions proved that prediction of a high-precision liner vibration is possible. And it proved that the relative change of the cylinder liner vibration and the subjective evaluation had high correlation with the measurement results of a real engine. As a result, piston slap noise prediction of practical sufficient accuracy was attained.

Recently, the eigenvalue analysis and the frequency response analysis using the finite element method (FEM) is commonly used, since the vibration characteristic of the powertrain is an important specification which causes the influence on the booming noise and the durability of each parts. However, the eigenvalue analysis and the frequency response analysis cannot take into account of the dynamic behavior of the cranktrain and thenonlinear characteristics. This paper presents a new approach which considers the dynamic behavior of the crankshaft and thenonlinear oil film characteristics of the main bearings and the engine mounts for accurately predicting the vibration level at the engine mounting points under running conditions. By applying this approach to an in-line four cylinder engine, the predicted vibration level is reasonably comparable with experimental result.

Recently, for the purposes of shortening the development period, the estimation of powerplant vibration has become more important in the early design stage, and eigenvalue analysis by FEM is commonly used to solve this problem. Eigenvalue analysis cannot directly predict vibration levels that affect the durability of each component and the vibration of a car body, however it is necessary to predict powerplant vibration in order to estimate exciting force under running conditions. Another factor adding to the difficulty of prediction is the instability of exciting force and various other non-linear characteristics. This paper presents a new approach using FRF data from FE models for accurate prediction of engine vibration under running conditions. By applying this approach to an in-line four cylinder engine, the predicted vibration is reasonably comparable with experimental results.