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Riding comfort on the seat is one of the important factors for vehicle comfort. To analyze riding comfort, there were some models for predicting human vibrations in the past studies. On the other hand, it is strongly affected by human body motion caused by vehicle excitation during driving especially low frequency, but it is difficult to predict human motion due to an unclear mechanism of muscle reflex. The purpose of this study is to construct virtual riding comfort testing simulation based on virtual prototyping of the seat. In this study, a virtual occupant model that predicts occupant motion on the seat against external excitation including muscle reflex for maintaining sitting posture constructed. The whole body was modeled as 15 segments biomechanical model (1D) with wobbling mass. Each joint has passive elastic torque and damping torque springs. Human body surface was modeled as rigid shape.

This paper describes the design measures taken to develop the noise and vibration performance of a new rear suspension and a new drivetrain system for rear-wheel-drive vehicles. The new rear suspension is designed to solve trade-off issues between road noise and handling performance. Despite higher drive torque, booming noise is greatly reduced by the new rear suspension and drivetrain without increasing the vehicle weight or sacrificing fuel economy.

A new tire modeling method, called the discretized standing-wave tire (DST) model method, is described. It is based on an assumption that the modes obtained with our modal analysis method are standing waves. This method regards the tread surface as uniformly continuous in the circumferential direction. Our DST model is also used to conduct a prediction analysis of the transmissibility of the suspension, and the results are compared with experimental data to validate the model. The experimental and predicted results are compared for situations where two different types of tires are mounted on a double-wishbone front suspension to demonstrate the prediction accuracy of the DST model.